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ScanCode is a tool to scan code and detect licenses, copyrights and more.

Why ScanCode?

Discovering the origin and license for a software component is important, but it is often much harder to accomplish than it should be because:

  • A typical software project may reuse tens or hundreds of third-party software components

  • Software authors do not always provide copyright and license information

  • Copyright and license information that is provided may be hard to find and interpret

ScanCode tries to address this issue by offering:

  • A comprehensive code scanner that can detect origin or license information inside codebase files

  • A simple command line approach that runs on Windows, Linux, and Mac

  • Your choice of JSON or other output formats (SPDX, HTML, CSV) for integration with other tools

  • ScanCode workbench for Visualization

  • Well-tested, easy to hack, and well-documented code

  • Release of the code and reference data under attribution licenses (Apache 2.0 and CC-BY-1.0)

  • Plugin System for easily adding new Functionality to Scans.

  • Python 3 Unicode Capabilities for better supporting users from 100+ languages.

  • Extensive Documentation Support.

What does ScanCode Toolkit do?

ScanCode finds the origin history information that is in your codebase with a focus on:

  • Copyright and other origin clues (emails, urls, authors etc)

  • License notices and license text with reference information about detected licenses.

Using this data you can:

  • Discover the origin and license of the open source and third-party software components that you use,

  • Create a software component Inventory for your codebase, and

  • Use this data to comply with open source license obligations such as attribution and redistribution.

How does it work?

Given a codebase in a directory, ScanCode will:

  • Collect an inventory of the code files and classify the code using file types

  • Extract files from any archive using a general purpose extractor

  • Extract texts from binary files if needed

  • Use an extensible rules engine to detect open source license text and notices

  • Use a specialized parser to capture copyright statements

  • Identify packaged code and collect metadata from packages

  • Report the results in the formats of your choice (JSON, SPDX, etc.) for integration with other tools

  • Browse the results using the ScanCode Workbench companion app to assist your analysis.

ScanCode should enable you to identify the “easy” cases on your own, but a software development team will probably need to build internal expertise or use outside experts (like nexB) in many cases.

ScanCode is written in Python and also uses other open source packages.

Alternatives?

There are several utilities that do some of what ScanCode does - e.g. You can grep files for copyright and license text. This may work well for simple cases - e.g. at the single file level, but we created ScanCode for ourselves because this approach does not help you to see the recurring patterns of licenses and other origin history clues.

Or you can consider other tools such as:

  • FOSSology (open source, written in C, Linux only, GPL-licensed)

  • Ninka (open source, written in Perl, GPL-licensed)

  • Commercially-licensed tools, most of them written in Java

History

ScanCode was originally created by nexB to support our software audit consulting services. We have used and continuously enhanced the underlying toolkit for six years. We decided to release ScanCode as open source software to give software development teams the opportunity to perform as much of the software audit function as they like on their own.

If you have questions or are interested in nexB-provided training or support for ScanCode, please send us a note at info@scancode.io or visit http://www.nexb.com/.

We are part of nexB Inc. and most of us are located in the San Francisco Bay Area. Our mission is to provide the tools and services that enable and accelerate component-based software development. Reusing software components is essential for the efficient delivery of software products and systems in every industry.

Thank you for giving ScanCode a try!

Comprehensive Installation

The fastest way to install Scancode-Toolkit is by using pip. You can also install ScanCode-Toolkit by compiling it from source or by Downloading and Configuring the latest release from GitHub.

Note

After pip install, you can perform a scan using only:

scancode [OPTIONS] <OUTPUT FORMAT OPTION(s)> <SCAN INPUT>

This is unlike other install methods where path to scancode is provided by using path/to/scancode, or by using ./scancode inside the Scancode install directory.

Before Installing

ScanCode requires either Python 3.6.x or Python 2.7.x and is tested on Linux, Mac, and Windows. Make sure Python 2.7 or Python 3.6 is installed first.

System Requirements
  • Hardware : ScanCode will run best with a modern X86 processor and at least 2GB of RAM and 250MB of disk.

  • Supported operating systems : ScanCode should run on these OSes:

    1. Linux: on most recent 64-bit Linux distributions (32-bit distros are only partially supported),

    2. Mac: on recent Mac OSX (10.6.8 and up),

    3. Windows: on Windows 7 and up (32- or 64-bit) using a 32-bit Python.

Prerequisites

ScanCode needs a Python 3.6 or a Python 2.7 interpreter.

Note

ScanCode currently doesn’t support Python 3.7.x, though support will be added soon.

  • On Linux: Use your package manager to install python2.7 or python3.6. If they are not available from your package manager, you must compile it from sources. For instance, visit https://github.com/dejacode/about-code-tool/wiki/BuildingPython27OnCentos6 for instructions to compile Python 2.7 from sources on Centos.

  • On Ubuntu 12.04, 14.04 and 16.04, you will need to install these packages first: python-dev bzip2 xz-utils zlib1g libxml2-dev libxslt1-dev

  • On Debian and Debian-based distros you will need to install these packages first: python-dev libbz2-1.0 xz-utils zlib1g libxml2-dev libxslt1-dev

  • On RPM-based distros, you will need to install these packages first: python-devel zlib bzip2-libs xz-libs libxml2-devel libxslt-devel

  • On Windows:

    Use the Python 2.7 32-bit (e.g. The Windows x86 MSI installer) for X86 regardless of whether you run Windows on 32-bit or 64-bit. DO NOT USE Python X86_64 installer even if you run 64 bit Windows. Download Python from this url: https://www.python.org/ftp/python/2.7.13/python-2.7.13.msi

    Install Python on the c: drive and use all default installer options (scancode will try to find python just in c:python27python.exe). See the Windows installation section for more installation details.

Note

64-bit Python interpreters (x86) are currently not supported by Scancode for Python 2.7 in Windows. Use 32-bit Python isntead, even with 64-bit Windows.

Warning

Do not use Unicode, non-ASCII in your installation Path if you are using a Python 2.7 interpreter.

Installation by pip

Scancode Toolkit can be easily installed using pip. The steps are:

  1. Create a Python 2.7 or Python 3.6 Virtual Environment:

    virtualenv -p /usr/bin/python3.6 venv-scancode
    
  2. Activate the Virtual Environment you just created:

    source venv-scancode/bin/activate
    
  3. Run pip install scancode-toolkit to Install Scancode.

Note

If you use Python 2.7, scancode-toolkit Version 3.0.2 is installed by default. For Python 3 the latest version of Scancode Toolkit is installed by default.

Warning

Requesting a specific version through pip install for Python 3 will give Errors if the Version isn’t 3.1.x or later.

To uninstall, run pip uninstall scancode-toolkit.

Download and Configure latest Release
Installation on Linux and Mac

Get the Scancode Toolkit tarball or zip archive of a specific Version by going to the GitHub Release Page

For example, Version 3.1.1 tarball or .zip archive can be obtained from Toolkit Release 3.1.1 under assets options. Download and extract the Archive from command line:

For .zip archive:

unzip scancode-toolkit-3.1.1.zip

For .tar.bz2 archive:

tar -xvf scancode-toolkit-3.1.1.tar.bz2

Or Right Click and select “Extract Here”.

Check whether the Prerequisites are installed. Open a terminal in the extracted directory and run:

./scancode --help

This will configure ScanCode and display the command line Help text.

Installation on Windows
  • Download the latest ScanCode release zip file from https://github.com/nexB/scancode-toolkit/releases/

  • In Windows Explorer (called File Explorer on Windows 10), select the downloaded ScanCode zip and right-click.

  • In the pop-up menu select ‘Extract All…’

  • In the pop-up window ‘Extract zip folders’ (‘Extract Compressed (Zipped) Folders’ on Windows 10) use the default options to extract.

  • Once the extraction is complete, a new Windows Explorer/File Explorer window will pop up.

  • In this Explorer window, select the new folder that was created and right-click.

Note

On Windows 10, double-click the new folder, select one of the files inside the folder (e.g., ‘setup.py’), and right-click.

  • In the pop-up menu select ‘Properties’.

  • In the pop-up window ‘Properties’, select the Location value. Copy this to the clipboard and close the ‘Properties’ window.

  • Press the start menu button (On Windows 10, click the search box or search icon in the taskbar.)

  • In the search box type:

    cmd
    
  • Select ‘cmd.exe’ listed in the search results. (On Windows 10, you may see ‘Command Prompt’ instead – select that.)

  • A new ‘cmd.exe’ window (‘Command Prompt’ on Windows 10) pops up.

  • In this window (aka a ‘command prompt’), type the following (i.e., ‘cd’ followed by a space):

    cd
    
  • Right-click in this window and select Paste. This will paste the path where you extracted ScanCode.

  • Press Enter.

  • This will change the current location of your command prompt to the root directory where ScanCode is installed.

  • Then type:

    scancode -h
    
  • Press enter. This will configure your ScanCode installation.

  • Several messages are displayed followed by the scancode command help.

  • The installation is complete.

Un-installation
  • Delete the directory in which you extracted ScanCode.

  • Delete any temporary files created in your system temp directory under a ScanCode directory.

Build From Source

You can also download the Scancode Toolkit Source Code and build from it yourself. This is how you would want to do it if:

  • You are Adding new patches to Scancode and want to test it.

  • You want to test a specific Version/Checkpoint/Branch from the VCS

Download the ScanCode-Toolkit Source Code

If you don’t have the ScanCode Toolkit Source Code downloaded, get it from it’s official Repository (Downloaded as a .zip file) or run the following:

git clone https://github.com/nexB/scancode-toolkit.git
cd scancode-toolkit

Now, by default the files are checked out to the develop branch, but you can jump to any checkpoint using the following command:

git checkout master

Here, master branch has the latest release of Scancode-Toolkit. You can also check out to any of the following:

  • Branches (Locally created or already present)

  • Tags (essentially Version Numbers) [Example - v3.1.1, v3.1.0 etc]

  • Commits (use the shortened commit hash) [Example - 4502055, f276398 etc]

Configure the build

ScanCode use the Configure scripts to install a virtualenv, install required packaged dependencies as pip requirements and more configure tasks such that ScanCode can be installed in a self-contained way with no network connectivity required.

Open a terminal, clone the scancode-toolkit repository, cd to the clone directory and run:

./configure

On Windows open a command prompt, cd to the clone directory and run instead:

configure

Now you are ready to use the freshly configured scancode-toolkit.

IDE Configuration

The instructions below assume that you followed the Contributing to Code Development including a python virtualenv.

PyCharm

Open the settings dialog and navigate to “Project Interpreter”. Click on the gear button in the upper left corner and select “Add Local”. Find the python binary in the virtualenv (bin/python in the repository root) and confirm. Open a file that contains tests and set a breakpoint. Right click in the test and select “Debug <name of test>”. Afterwards you can re-run the same test in the debugger using the appropriate keyboard shortcut (e.g. Shift-F9, depending on platform and configured layout).

Visual Studio Code

Install the Python extension from Microsoft.

The configure script should have created a VSCode workspace directory with a basic settings.json. To do this manually, add to or create the workspace settings file .vscode/settings.json:

"python.pythonPath": "${workspaceRoot}/bin/python",
"python.unitTest.pyTestEnabled": true

If you created the file, also add { and } on the first and last line respectively.

When you open the project root folder in VSCode, the status bar should show the correct python interpreter and, after a while, a “Run Tests” button. If not, try restarting VSCode.

Open a file that contains tests (e.g. tests/cluecode/test_copyrights.py). Above the test functions you should now see “Run Test” and “Debug Test”. Set a breakpoint in a test function and click on “Debug Test” above it. The debugger panel should show up on the left and show the program state at the breakpoint. Stepping over and into code seems not to work. Clicking one of those buttons just runs the test to completion. As a workaround, navigate to the function you want to step into, set another breakpoint and click on “continue” instead.

What’s New in This Release?

A new release of Scancode-Toolkit is here!

Quick Summary
  • Version - 3.1.1

  • Tag - “v.3.1.1”

  • Date - 5th September 2019

  • Type - Pre-Release

  • Comments - Release v3.1.1 which the release candidate 2 of 3.1.x

Main New Features

This is the first 3.1 release with the best, fastest and most efficient ScanCode ever released.

This release contains many improvements, fixes and new features including breaking API changes (when compared to 2.2.x). See the CHANGELOG for details.

This release also comes with a Full Documentation hosted at aboutcode.readthedocs.io.

To install, download scancode-toolkit-3.1.1.zip or scancode-toolkit-3.1.1.tar.bz2 from the Downloads section below and follow installation instructions in the README.

This is also available as a Python library from Pypi with pip install scancode-toolkit.

You can also download the corresponding source code for bundled pre-built third-party binaries from these locations:

Brief Summary Of Changes
Documentation Support

From Scancode 3.1.1 Scancode comes with improved and comprehensive Documentation Support.

The documentation is available both offline (distributed with Scancode) and online, at scancode-toolkit.readthedocs.io/en/latest/. The documentation in GitHub wiki’s will be deprecated hereafter. The new documentation has improved support in terms of:

  1. Consistent with the Latest Version

  2. Command Line Interface Reference

  3. Getting Started Support for Newcomers

  4. Restructured to fit into the recommended 4 Category Doc Format

  5. Updated Tutorials/How To’s

  6. Updated Plugin Support

This results in a much better documentation experience in Users and even contributors.

pip install Support

Now, pip install is the recommended install method, across all platforms. This greatly simplifies the install process, and is much faster and easier than the Download and Configure method, for non-developer users.

Python 3 Support

Python 3 is now officially supported by Scancode-Toolkit.

This also means improved Unicode support, so it’s easy to translate strings from Unicode to other languages. And as Scancode has users in more than 100 languages, this is a major improvement.

Are you new to Scancode-Toolkit?

This is the perfect place to start, if you are new to ScanCode-Toolkit. Have a quick look at the table of contents below, as these are the main sections you might need help on. These sections have extensive links to other important documentation pages, and make sure you go through them all.

Try ScanCode Toolkit

This section is about using the Scancode-Toolkit, i.e. Performing a scan on a codebase/files to determine their license, copyrights and other information, according to your requirements.

  1. The :ref:` newcomer_scan_codebase` section helps you with configuring your virtual environment, installing Scancode and performing a basic scan, and subsequently visualize the results.

  2. The Use ScanCode Better section helps you customize the scan according to your requirements, and better understand the advanced features you can use.

  3. The All Tutorials/How-Tos is essentially an exhaustive list of all Tutorials and How To’s with a brief description on what they help you to achieve.

Before you start using Scancode
  1. You need to make sure Prerequisites are installed, and a virtualenv is created.

  2. Now you can either run pip install scancode-toolkit like that in the Installation by pip documentation, or follow the instructions for the Download and Configure latest Release method. Alternatively, you can also Build From Source.

  3. Run scancode -h to make sure Scancode was installed properly. If this shows any Error, refer the Common Installation Errors Issue for common errors. The documentation also has tips on IDE Configuration.

Note

Refer Quickstart to make sure you are using the scan command correctly.

Scan a Codebase

Once you are all set up with Scancode Toolkit, i.e. Running scancode -h shows the Help text, you can start scanning files or a codebase.

  1. Refer Quickstart for commonly used scan commands, and commonly used Output Formats. (The recommended output format is JSON)

  2. Refer this section for Extractcode Options.

  3. How to Run a Scan is a sample tutorial for absolute beginners, to walk them through the process of running a scan. Follow this tutorial and perform a scan on the sample folder distributed with ScanCode, or any file/folder of your choice. Avoid advanced options, and just follow the basic instructions.

  4. ScanCode generates output files with scan results. You can visualize JSON result files using Scancode Workbench. Follow this tutorial How to Visualize Scan results to visualize the scan results.

Use ScanCode Better
  1. Go through all the options in the page All Available Options, to know about Scancode Command Line options. You can then modify the Scan according to your requirements.

ScanCode Versions
  1. You can see all Scancode Toolkit versions on the GitHub release page.

  2. Refer What’s New in This Release? to know more about the latest release.

  3. You can also refer the CHANGELOG for more information on specific releases.

  4. If you want to use/test a specific version of Scancode Toolkit, you can follow the instructions in Build From Source docs.


Learn more about ScanCode Toolkit

Here we give an introduction on the Scancode Toolkit Documentation Sections that can help you to learn more about Scancode Toolkit.

CLI Reference

This section contains a complete guide to ScanCode Toolkit Command Line options, i.e. What the command-line options are, how different options affect the scan and outputs, how to use these options and examples of their use cases.

Now this section has three types of pages:

  1. The Synopsis page and the How to Run a Scan page as summaries.

  2. An exhaustive list of all Command Line Options at All Available Options

  3. All the other pages detailing the Type of Options

Note that the page for one type of options also has a short list of all the options detailed on that page in the beginning. The All Available Options page just has all of them together, and also the extractcode options.

How Scancode Works

This section has documentation on How does ScanCode work?.

Plugins

Plugins are an integral part of ScanCode Toolkit in the sense they are used to easily extend Scancode capabilities, and developers can code their own plugins according to their requirements.

This section has documentation on:

  1. The Plugin Architecture

  2. The License Policy Plugin

  3. All Plugin Tutorials


Contribute

If you are looking to Contribute to Scancode Toolkit, this is where you start.

General Information
  1. Also refer the Contribution page here.

  2. For more Project Ideas, refer Contributor Project Ideas.

  3. Before committing your work, make sure you have read this post on Writing good Commit Messages.

Contribute Code

If you haven’t contributed to Scancode Toolkit refer Good First Issues.

To determine where to contribute, you can refer:

  1. ScanCode Toolkit tracks issues via the GitHub Issue tracker

  2. Broad milestones for upcoming versions are also maintained.

And documentation related to contributing code can be referred at Contributing to Code Development. The main sections are:

  1. Code layout and conventions

  2. Running tests

  3. pip requirements and the configure script

Good First Issues

A good first issue means it’s recommended for people who haven’t contributed to Scancode Toolkit before.

  1. Refer the detailed documentation for Good First Issue.

  2. Important Links for Good First issues are also compiled.

  3. What you should understand before Solving a Good First Issue

  4. Step by Step Workflow : Contributor’s Tasks

A first timers only issue means we’ve worked to make it more legible to folks who either haven’t contributed to our codebase before, or even folks who haven’t contributed to open source before.

Refer the detailed documentation for First Timers Only.

Add new Functionality/Enhancement to ScanCode

There are two main paths you can follow to add a new functionality to Scancode. They are:

  1. Add the functionality to Scancode itself.

  2. Add plugins if the functionality is very much application dependent.

Refer enhancement issues for the first type of enhancements. If you want to add a plugin to implement the functionality, refer all the Plugin Tutorials.

Update our Documentation

Maintaining a comprehensive, accurate, updated and effective documentation is very important as that directly affects the acceptability of Scancode Toolkit.

To contribute to Scancode Toolkit Documentation, first refer the Contributing to the Documentation section.

The sections in this page cover the following:

  1. Setup Local Build

  2. Share Document Improvements

  3. Continuous Integration system for the Documentation

  4. Style Checks Using Doc8

  5. Interspinx

  6. Style Conventions for the Documentaion

You can contribute to the following Open Issues on documentation.

  1. Issues with label Documentation

  2. Documentation Inconsistencies Tracker

  3. ScanCode Toolkit Documentation Roadmap

  4. First Timers Only Issues List

Note

Refer Something Missing? to report Documentation Errors or to request Improvements.

Also, consider contributing to other Aboutcode Project Documentations, as they need more support.

Participate in GSoC/GSoD

If you want to participate in any of the two programs:

Then:

  1. Keep an eye out for Application Timelines.

  2. Solve multiple of these Good First Issue to demonstrate your skills, and improve your chances of selection.

  3. Refer the Projects Ideas list for details on tentative projects.

  4. Remain active in Gitter and talk with the organization mentors well ahead of the deadlines.

  5. Select projects according to your skills and finalize project proposals.

  6. Discuss your proposals extensively with corresponding mentors.

  7. Apply for the Programs well before the Deadline.

Command Line Interface Reference

Synopsis

ScanCode detects licenses, copyrights, package manifests and direct dependencies and more, both in source code and binary files, by scanning the files. This page introduces you to the ScanCode Toolkit Command Line Interface in the following sections:

  • Installation

  • Quickstart

  • Type of Options

  • Output Formats

  • Other Important Documentation

Installation

Scancode-Toolkit installation can be installed from pip, the default Python Package Manager. However, there are more ways to perform an installation, and refer the following sections for detailed Instructions on the each of the Installation Methods.

Quickstart

The basic command to perform a scan, if Scancode is installed from pip:

scancode [OPTIONS] <OUTPUT FORMAT OPTION(s)> <SCAN INPUT>

The basic usage in case of a download and configure installation (on Linux/MacOS) is:

path/to/scancode [OPTIONS] <OUTPUT FORMAT OPTION(s)> <SCAN INPUT>

Tip

On Windows use scancode instead of path/to/scancode, irrespective of the installation method.

Here Scancode scans the <SCAN INPUT> file or directory for license, origin and packages and saves results to FILE(s) using one or more output format option. Error and progress are printed to stdout.

To scan the samples directory distributed with ScanCode-Toolkit, the command will be:

scancode -clpieu --json-pp path/to/output.json path/to/samples

Note

The <OUTPUT FORMAT OPTION(s)> includes both the output option and output file name. For example in the command scancode -clpieu --json-pp output.json samples, --json-pp output.json is <OUTPUT FORMAT OPTION(s)>.

Warning

There isn’t a “Default” output option in Versions 3.x onwards, you have to specify <OUTPUT FORMAT OPTION(s)> explicitly.

Alternatively, in case of download and configure installations, where path/to/scancode is used (the path from root of file system) we can go into the scancode directory (like scancode-toolkit-3.1.1) and then use ./scancode. The same applies for input and output options. To scan a folder samples inside ScanCode directory, and output to a file output.json in the same directory, the command will be:

./scancode -clpieu --json-pp output.json samples

While a scan using absolute paths from the file system root will look like:

home/ayansm/software/scancode-toolkit-3.1.1/scancode -clpieu --json-pp home/ayansm/scan_scan_results/output.json home/ayansm/codebases/samples/

Commands similar to scancode --clpi --json-pp output.json samples will be used as examples throughout the documentation. Here we are inside the virtualenv where Scancode-Toolkit was installed by pip, and the default samples folder is being scanned, which is distributed by default with Scancode-Toolkit.

Type of Options

ScanCode Toolkit Command Line options can be divided into these major sections:

Refer the individual pages which are linked to above, for detailed discussions on the Command Line Options listed under each section.

Output Formats

The output file format is set by using the various output options. The recommended output format is JSON. If --json is used, the entire file being in one line, without whitespace characters.

The following example scans will show you how to run a scan with each of the result formats. For the scans, we will use the samples directory provided with the ScanCode Toolkit.

Tip

You can also output to stdout instead of a file. For more information refer Print to stdout (Terminal).

JSON file output

Scan the samples directory and save the scan to a JSON file (pretty-printed)::

scancode -clpieu --json-pp output.json samples

A sample JSON output file structure will look like:

{
  "headers": [
    {
      "tool_name": "scancode-toolkit",
      "tool_version": "3.1.1",
      "options": {
        "input": [
          "samples/"
        ],
        "--copyright": true,
        "--email": true,
        "--info": true,
        "--json-pp": "output.json",
        "--license": true,
        "--package": true,
        "--url": true
      },
      "notice": "Generated with ScanCode and provided on an \"AS IS\" BASIS, WITHOUT WARRANTIES\nOR CONDITIONS OF ANY KIND, either express or implied. No content created from\nScanCode should be considered or used as legal advice. Consult an Attorney\nfor any legal advice.\nScanCode is a free software code scanning tool from nexB Inc. and others.\nVisit https://github.com/nexB/scancode-toolkit/ for support and download.",
      "start_timestamp": "2019-10-19T191117.292858",
      "end_timestamp": "2019-10-19T191219.743133",
      "message": null,
      "errors": [],
      "extra_data": {
        "files_count": 36
      }
    }
  ],
  "files": [
    {
      "path": "samples",
      "type": "directory",
      ...
      ...
      ...
      "scan_errors": []
    },
    {
      "path": "samples/README",
      "type": "file",
      "name": "README",
      "base_name": "README",
      "extension": "",
      "size": 236,
      "date": "2019-02-12",
      "sha1": "2e07e32c52d607204fad196052d70e3d18fb8636",
      "md5": "effc6856ef85a9250fb1a470792b3f38",
      "mime_type": "text/plain",
      "file_type": "ASCII text",
      "programming_language": null,
      "is_binary": false,
      "is_text": true,
      "is_archive": false,
      "is_media": false,
      "is_source": false,
      "is_script": false,
      "licenses": [],
      "license_expressions": [],
      "copyrights": [],
      "holders": [],
      "authors": [],
      "packages": [],
      "emails": [],
      "urls": [],
      "files_count": 0,
      "dirs_count": 0,
      "size_count": 0,
      "scan_errors": []
    },
    ...
    ...
    ...
    {
      "path": "samples/zlib/iostream2/zstream_test.cpp",
      "type": "file",
      "name": "zstream_test.cpp",
      "base_name": "zstream_test",
      "extension": ".cpp",
      "size": 711,
      "date": "2019-02-12",
      ...
      ...
      ...
      "scan_errors": []
    }
  ]
}

A sample JSON output for an individual file will look like:

{
  "path": "samples/zlib/iostream2/zstream.h",
  "type": "file",
  "name": "zstream.h",
  "base_name": "zstream",
  "extension": ".h",
  "size": 9283,
  "date": "2019-02-12",
  "sha1": "fca4540d490fff36bb90fd801cf9cd8fc695bb17",
  "md5": "a980b61c1e8be68d5cdb1236ba6b43e7",
  "mime_type": "text/x-c++",
  "file_type": "C++ source, ASCII text",
  "programming_language": "C++",
  "is_binary": false,
  "is_text": true,
  "is_archive": false,
  "is_media": false,
  "is_source": true,
  "is_script": false,
  "licenses": [
    {
      "key": "mit-old-style",
      "score": 100.0,
      "name": "MIT Old Style",
      "short_name": "MIT Old Style",
      "category": "Permissive",
      "is_exception": false,
      "owner": "MIT",
      "homepage_url": "http://fedoraproject.org/wiki/Licensing:MIT#Old_Style",
      "text_url": "http://fedoraproject.org/wiki/Licensing:MIT#Old_Style",
      "reference_url": "https://enterprise.dejacode.com/urn/urn:dje:license:mit-old-style",
      "spdx_license_key": null,
      "spdx_url": "",
      "start_line": 9,
      "end_line": 15,
      "matched_rule": {
        "identifier": "mit-old-style_cmr-no_1.RULE",
        "license_expression": "mit-old-style",
        "licenses": [
          "mit-old-style"
        ],
        "is_license_text": true,
        "is_license_notice": false,
        "is_license_reference": false,
        "is_license_tag": false,
        "matcher": "2-aho",
        "rule_length": 71,
        "matched_length": 71,
        "match_coverage": 100.0,
        "rule_relevance": 100
      }
    }
  ],
  "license_expressions": [
    "mit-old-style"
  ],
  "copyrights": [
    {
      "value": "Copyright (c) 1997 Christian Michelsen Research AS Advanced Computing",
      "start_line": 3,
      "end_line": 5
    }
  ],
  "holders": [
    {
      "value": "Christian Michelsen Research AS Advanced Computing",
      "start_line": 3,
      "end_line": 5
    }
  ],
  "authors": [],
  "packages": [],
  "emails": [],
  "urls": [
    {
      "url": "http://www.cmr.no/",
      "start_line": 7,
      "end_line": 7
    }
  ],
  "files_count": 0,
  "dirs_count": 0,
  "size_count": 0,
  "scan_errors": []
},
Static HTML output

Scan the samples directory for licenses and copyrights and save the scan results to an HTML file. When the scan is done, open samples.html in your web browser.

scancode -clpieu --html output.html samples
_images/scancode-toolkit-static-html1.png _images/scancode-toolkit-static-html2.png
Getting Help from the Command Line

ScanCode-Toolkit Command Line Interface can help you to search for specific options or use cases from the command line itself. These are two options are --help and --examples, and are very helpful if you need a quick glance of the options or use cases. Or it can be useful when you can’t access, the more elaborate online documentation.

All Documentation/Help Options
-h, --help

Show the Help text and exit.

--examples

Show the Command Examples Text and exit.

--about

Show information about ScanCode and licensing and exit.

--version

Show the version and exit.

--list-packages

Show the list of supported package types and exit.

--plugins

Show the list of available ScanCode plugins and exit.

--print-options

Show the list of selected options and exit.

Help text

The Scancode-Toolkit Command Line Interface has a Help option displaying all the options. It also displays basic usage, and some simple examples. The command line option for this is --help.

Tip

You can also use the shorter -h option, which does the same.

To see the help text from the Terminal, execute the following command:

$ scancode --help

Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.

The Following Help Text is displayed, i.e. This is the help text for Scancode Version 3.1.1

Usage: scancode [OPTIONS] <OUTPUT FORMAT OPTION(s)> <input>...

scan the <input> file or directory for license, origin and packages
and save results to FILE(s) using one or more output format option.

Error and progress are printed to stderr.

Options:

primary scans:
  -l, --license    Scan <input> for licenses.
  -p, --package    Scan <input> for package manifests and packages.
  -c, --copyright  Scan <input> for copyrights.

other scans:
  -i, --info   Scan <input> for file information (size, checksums, etc).
  --generated  Classify automatically generated code files with a flag.
  -e, --email  Scan <input> for emails.
  -u, --url    Scan <input> for urls.

scan options:
  --license-score INTEGER      Do not return license matches with a
                               score lower than this score. A number
                               between 0 and 100.  [default: 0]
  --license-text               Include the detected licenses matched
                               text.
  --license-text-diagnostics   In the matched license text, include
                               diagnostic highlights surrounding with
                               square brackets [] words that are not
                               matched.
  --license-url-template TEXT  Set the template URL used for the license
                               reference URLs. Curly braces ({}) are
                               replaced by the license key.  [default: h
                               ttps://enterprise.dejacode.com/urn/urn:dj
                               e:license:{}]
  --max-email INT              Report only up to INT emails found in a
                               file. Use 0 for no limit.  [default: 50]
  --max-url INT                Report only up to INT urls found in a
                               file. Use 0 for no limit.  [default: 50]

output formats:
  --json FILE             Write scan output as compact JSON to FILE.
  --json-pp FILE          Write scan output as pretty-printed JSON to
                          FILE.
  --json-lines FILE       Write scan output as JSON Lines to FILE.
  --csv FILE              Write scan output as CSV to FILE.
  --html FILE             Write scan output as HTML to FILE.
  --custom-output FILE    Write scan output to FILE formatted with the
                          custom Jinja template file.
  --custom-template FILE  Use this Jinja template FILE as a custom
                          template.
  --spdx-rdf FILE         Write scan output as SPDX RDF to FILE.
  --spdx-tv FILE          Write scan output as SPDX Tag/Value to FILE.
  --html-app FILE         (DEPRECATED: use the ScanCode Workbench app
                          instead ) Write scan output as a mini HTML
                          application to FILE.

output filters:
  --ignore-author <pattern>       Ignore a file (and all its findings)
                                  if an author contains a match to the
                                  <pattern> regular expression. Note
                                  that this will ignore a file even if
                                  it has other findings such as a
                                  license or errors.
  --ignore-copyright-holder <pattern>
                                  Ignore a file (and all its findings)
                                  if a copyright holder contains a match
                                  to the <pattern> regular expression.
                                  Note that this will ignore a file even
                                  if it has other scanned data such as a
                                  license or errors.
  --only-findings                 Only return files or directories with
                                  findings for the requested scans.
                                  Files and directories without findings
                                  are omitted (file information is not
                                  treated as findings).

output control:
  --full-root   Report full, absolute paths.
  --strip-root  Strip the root directory segment of all paths. The
                default is to always include the last directory segment
                of the scanned path such that all paths have a common
                root directory.

pre-scan:
  --ignore <pattern>         Ignore files matching <pattern>.
  --include <pattern>        Include files matching <pattern>.
  --classify                 Classify files with flags telling if the
                             file is a legal, or readme or test file,
                             etc.
  --facet <facet>=<pattern>  Add the <facet> to files with a path
                             matching <pattern>.

post-scan:
  --consolidate            Group resources by Packages or license and
                           copyright holder and return those groupings
                           as a list of consolidated packages and a list
                           of consolidated components. This requires the
                           scan to have/be run with the copyright,
                           license, and package options active
  --filter-clues           Filter redundant duplicated clues already
                           contained in detected license and copyright
                           texts and notices.
  --is-license-text        Set the "is_license_text" flag to true for
                           files that contain mostly license texts and
                           notices (e.g over 90% of the content).
                           [EXPERIMENTAL]
  --license-clarity-score  Compute a summary license clarity score at
                           the codebase level.
  --license-policy FILE    Load a License Policy file and apply it to
                           the scan at the Resource level.
  --mark-source            Set the "is_source" to true for directories
                           that contain over 90% of source files as
                           children and descendants. Count the number of
                           source files in a directory as a new
                           source_file_counts attribute
  --summary                Summarize license, copyright and other scans
                           at the codebase level.
  --summary-by-facet       Summarize license, copyright and other scans
                           and group the results by facet.
  --summary-key-files      Summarize license, copyright and other scans
                           for key, top-level files. Key files are top-
                           level codebase files such as COPYING, README
                           and package manifests as reported by the
                           --classify option "is_legal", "is_readme",
                           "is_manifest" and "is_top_level" flags.
  --summary-with-details   Summarize license, copyright and other scans
                           at the codebase level, keeping intermediate
                           details at the file and directory level.

core:
  --timeout <secs>         Stop an unfinished file scan after a timeout
                           in seconds.  [default: 120 seconds]
  -n, --processes INT      Set the number of parallel processes to use.
                           Disable parallel processing if 0. Also
                           disable threading if -1. [default: 1]
  --quiet                  Do not print summary or progress.
  --verbose                Print progress as file-by-file path instead
                           of a progress bar. Print verbose scan
                           counters.
  --from-json              Load codebase from an existing JSON scan
  --max-in-memory INTEGER  Maximum number of files and directories scan
                           details kept in memory during a scan.
                           Additional files and directories scan details
                           above this number are cached on-disk rather
                           than in memory. Use 0 to use unlimited memory
                           and disable on-disk caching. Use -1 to use
                           only on-disk caching.  [default: 10000]

miscellaneous:
  --reindex-licenses  Check the license index cache and reindex if
                      needed and exit.

documentation:
  -h, --help       Show this message and exit.
  --about          Show information about ScanCode and licensing and
                   exit.
  --version        Show the version and exit.
  --examples       Show command examples and exit.
  --list-packages  Show the list of supported package types and exit.
  --plugins        Show the list of available ScanCode plugins and exit.
  --print-options  Show the list of selected options and exit.

Examples (use --examples for more):

Scan the 'samples' directory for licenses and copyrights.
Save scan results to the 'scancode_result.json' JSON file:

    scancode --license --copyright --json-pp scancode_result.json
    samples

Scan the 'samples' directory for licenses and package manifests. Print scan
results on screen as pretty-formatted JSON (using the special '-' FILE to print
to on screen/to stdout):

    scancode --json-pp - --license --package  samples

Note: when you run scancode, a progress bar is displayed with a
counter of the number of files processed. Use --verbose to display
file-by-file progress.
Command Examples Text

The Scancode-Toolkit Command Line Interface has an --examples option which displays some basic examples (more than the basic synopsis in --help). These examples include the following aspects of code scanning:

  • Scanning Single File/Directory

  • Output Scan results to stdout (as JSON) or HTML/JSON file

  • Scanning for only Copyrights/Licenses

  • Ignoring Files

  • Using GLOB Patterns to Scan Multiple Files

  • Using Verbose Mode

The command line option for displaying these basic examples is --examples.

To see the help text from the Terminal, execute the following command:

$ scancode --examples

Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.

The Following Text is displayed, i.e. This is the examples for Scancode Version 3.1.1

Scancode command lines examples:

(Note for Windows: use '\' back slash instead of '/' forward slash for paths.)

Scan a single file for copyrights. Print scan results to stdout as pretty JSON:

    scancode --copyright samples/zlib/zlib.h --json-pp -

Scan a single file for licenses, print verbose progress to stderr as each
file is scanned. Save scan to a JSON file:

    scancode --license --verbose samples/zlib/zlib.h --json licenses.json

Scan a directory explicitly for licenses and copyrights. Redirect JSON scan
results to a file:

    scancode --license --copyright samples/zlib/ --json - > scan.json

Scan a directory while ignoring a single file. Scan for license, copyright and
package manifests. Use four parallel processes.
Print scan results to stdout as pretty formatted JSON.

    scancode -lc --package --ignore README --processes 4 --json-pp - samples/

Scan a directory while ignoring all files with .txt extension.
Print scan results to stdout as pretty formatted JSON.
It is recommended to use quotes around glob patterns to prevent pattern
expansion by the shell:

    scancode --json-pp - --ignore "*.txt" samples/

Special characters supported in GLOB pattern:
- *       matches everything
- ?       matches any single character
- [seq]   matches any character in seq
- [!seq]  matches any character not in seq

For a literal match, wrap the meta-characters in brackets.
For example, '[?]' matches the character '?'.
For details on GLOB patterns see https://en.wikipedia.org/wiki/Glob_(programming).

Note: Glob patterns cannot be applied to path as strings.
For example, this will not ignore "samples/JGroups/licenses".

    scancode --json - --ignore "samples*licenses" samples/


Scan a directory while ignoring multiple files (or glob patterns).
Print the scan results to stdout as JSON:

    scancode --json - --ignore README --ignore "*.txt" samples/

Scan a directory for licenses and copyrights. Save scan results to an
HTML file:

    scancode --license --copyright --html scancode_result.html samples/zlib

To extract archives, see the 'extractcode' command instead.
Plugins Help Text

The command line option for displaying all the plugins is:

  • --plugins

To see the help text from the Terminal, execute the following command:

$ scancode --plugins

Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.

Note

Plugins that are shown by using --plugins include the following:

  1. Post-Scan Plugins

  2. Pre-Scan Plugins

  3. Output Options

  4. Output Control

  5. Basic Scan Options

The Following Text is displayed, i.e. This is the available plugins for Scancode Version 3.1.1

--------------------------------------------
Plugin: scancode_output:csv  class: formattedcode.output_csv:CsvOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: csv: --csv
      help: Write scan output as CSV to FILE.
  doc: None

--------------------------------------------
Plugin: scancode_output:html  class: formattedcode.output_html:HtmlOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: html: --html
      help: Write scan output as HTML to FILE.
  doc: None

--------------------------------------------
Plugin: scancode_output:html-app  class: formattedcode.output_html:HtmlAppOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: html_app: --html-app
      help: (DEPRECATED: use the ScanCode Workbench app instead ) Write scan output as a mini HTML application to FILE.
  doc:
    Write scan output as a mini HTML application.

--------------------------------------------
Plugin: scancode_output:json  class: formattedcode.output_json:JsonCompactOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: output_json: --json
      help: Write scan output as compact JSON to FILE.
  doc: None

--------------------------------------------
Plugin: scancode_output:json-pp  class: formattedcode.output_json:JsonPrettyOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: output_json_pp: --json-pp
      help: Write scan output as pretty-printed JSON to FILE.
  doc: None

--------------------------------------------
Plugin: scancode_output:jsonlines  class: formattedcode.output_jsonlines:JsonLinesOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: output_json_lines: --json-lines
      help: Write scan output as JSON Lines to FILE.
  doc: None

--------------------------------------------
Plugin: scancode_output:spdx-rdf  class: formattedcode.output_spdx:SpdxRdfOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: spdx_rdf: --spdx-rdf
      help: Write scan output as SPDX RDF to FILE.
  doc: None

--------------------------------------------
Plugin: scancode_output:spdx-tv  class: formattedcode.output_spdx:SpdxTvOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: spdx_tv: --spdx-tv
      help: Write scan output as SPDX Tag/Value to FILE.
  doc: None

--------------------------------------------
Plugin: scancode_output:template  class: formattedcode.output_html:CustomTemplateOutput
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output formats, name: custom_output: --custom-output
      help: Write scan output to FILE formatted with the custom Jinja template file.
    help_group: output formats, name: custom_template: --custom-template
      help: Use this Jinja template FILE as a custom template.
  doc: None

--------------------------------------------
Plugin: scancode_output_filter:ignore-copyrights  class: cluecode.plugin_ignore_copyrights:IgnoreCopyrights
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output filters, name: ignore_copyright_holder: --ignore-copyright-holder
      help: Ignore a file (and all its findings) if a copyright holder contains a match to the <pattern> regular expression. Note that this will ignore a file even if it has other scanned data such as a license or errors.
    help_group: output filters, name: ignore_author: --ignore-author
      help: Ignore a file (and all its findings) if an author contains a match to the <pattern> regular expression. Note that this will ignore a file even if it has other findings such as a license or errors.
  doc:
    Filter findings that match given copyright holder or author patterns.
    Has no effect unless the --copyright scan is requested.

--------------------------------------------
Plugin: scancode_output_filter:only-findings  class: scancode.plugin_only_findings:OnlyFindings
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: output filters, name: only_findings: --only-findings
      help: Only return files or directories with findings for the requested scans. Files and directories without findings are omitted (file information is not treated as findings).
  doc:
    Filter files or directories without scan findings for the requested scans.

--------------------------------------------
Plugin: scancode_post_scan:classify-package  class: summarycode.classify:PackageTopAndKeyFilesTagger
  codebase_attributes:
  resource_attributes:
  sort_order: 0
  required_plugins:
  options:
  doc:
    Tag resources as key or top level based on Package-type specific settings.

--------------------------------------------
Plugin: scancode_post_scan:consolidate  class: scancode.plugin_consolidate:Consolidator
  codebase_attributes: consolidated_components, consolidated_packages
  resource_attributes: consolidated_to
  sort_order: 8
  required_plugins:
  options:
    help_group: post-scan, name: consolidate: --consolidate
      help: Group resources by Packages or license and copyright holder and return those groupings as a list of consolidated packages and a list of consolidated components. This requires the scan to have/be run with the copyright, license, and package options active
  doc:
    A ScanCode post-scan plugin to return consolidated components and consolidated
    packages for different types of codebase summarization.

    A consolidated component is a group of Resources that have the same origin.
    Currently, consolidated components are created by grouping Resources that have
    the same license expression and copyright holders and the files that contain
    this license expression and copyright holders combination make up 75% or more of
    the files in the directory where they are found.

    A consolidated package is a detected package in the scanned codebase that has
    been enhanced with data about other licenses and holders found within it.

    If a Resource is part of a consolidated component or consolidated package, then
    the identifier of the consolidated component or consolidated package it is part
    of is in the Resource's ``consolidated_to`` field.

--------------------------------------------
Plugin: scancode_post_scan:filter-clues  class: cluecode.plugin_filter_clues:RedundantCluesFilter
  codebase_attributes:
  resource_attributes:
  sort_order: 1
  required_plugins:
  options:
    help_group: post-scan, name: filter_clues: --filter-clues
      help: Filter redundant duplicated clues already contained in detected license and copyright texts and notices.
  doc:
    Filter redundant clues (copyrights, authors, emails, and urls) that are already
    contained in another more important scan result.

--------------------------------------------
Plugin: scancode_post_scan:is-license-text  class: licensedcode.plugin_license_text:IsLicenseText
  codebase_attributes:
  resource_attributes: is_license_text
  sort_order: 80
  required_plugins:
  options:
    help_group: post-scan, name: is_license_text: --is-license-text
      help: Set the "is_license_text" flag to true for files that contain mostly license texts and notices (e.g over 90% of the content). [EXPERIMENTAL]
  doc:
    Set the "is_license_text" flag to true for at the file level for text files
    that contain mostly (as 90% of their size) license texts or notices.
    Has no effect unless --license, --license-text and --info scan data
    are available.

--------------------------------------------
Plugin: scancode_post_scan:license-clarity-score  class: summarycode.score:LicenseClarityScore
  codebase_attributes: license_clarity_score
  resource_attributes:
  sort_order: 110
  required_plugins:
  options:
    help_group: post-scan, name: license_clarity_score: --license-clarity-score
      help: Compute a summary license clarity score at the codebase level.
  doc:
    Compute a License clarity score at the codebase level.

--------------------------------------------
Plugin: scancode_post_scan:license-policy  class: licensedcode.plugin_license_policy:LicensePolicy
  codebase_attributes:
  resource_attributes: license_policy
  sort_order: 9
  required_plugins:
  options:
    help_group: post-scan, name: license_policy: --license-policy
      help: Load a License Policy file and apply it to the scan at the Resource level.
  doc:
    Add the "license_policy" attribute to a resouce if it contains a
    detected license key that is found in the license_policy.yml file

--------------------------------------------
Plugin: scancode_post_scan:mark-source  class: scancode.plugin_mark_source:MarkSource
  codebase_attributes:
  resource_attributes: source_count
  sort_order: 8
  required_plugins:
  options:
    help_group: post-scan, name: mark_source: --mark-source
      help: Set the "is_source" to true for directories that contain over 90% of source files as children and descendants. Count the number of source files in a directory as a new source_file_counts attribute
  doc:
    Set the "is_source" flag to true for directories that contain
    over 90% of source files as direct children.
    Has no effect unless the --info scan is requested.

--------------------------------------------
Plugin: scancode_post_scan:summary  class: summarycode.summarizer:ScanSummary
  codebase_attributes: summary
  resource_attributes:
  sort_order: 10
  required_plugins:
  options:
    help_group: post-scan, name: summary: --summary
      help: Summarize license, copyright and other scans at the codebase level.
  doc:
    Summarize a scan at the codebase level.

--------------------------------------------
Plugin: scancode_post_scan:summary-by-facet  class: summarycode.summarizer:ScanByFacetSummary
  codebase_attributes: summary_by_facet
  resource_attributes:
  sort_order: 200
  required_plugins:
  options:
    help_group: post-scan, name: summary_by_facet: --summary-by-facet
      help: Summarize license, copyright and other scans and group the results by facet.
  doc:
    Summarize a scan at the codebase level groupping by facets.

--------------------------------------------
Plugin: scancode_post_scan:summary-keeping-details  class: summarycode.summarizer:ScanSummaryWithDetails
  codebase_attributes: summary
  resource_attributes: summary
  sort_order: 100
  required_plugins:
  options:
    help_group: post-scan, name: summary_with_details: --summary-with-details
      help: Summarize license, copyright and other scans at the codebase level, keeping intermediate details at the file and directory level.
  doc:
    Summarize a scan at the codebase level and keep file and directory details.

--------------------------------------------
Plugin: scancode_post_scan:summary-key-files  class: summarycode.summarizer:ScanKeyFilesSummary
  codebase_attributes: summary_of_key_files
  resource_attributes:
  sort_order: 150
  required_plugins:
  options:
    help_group: post-scan, name: summary_key_files: --summary-key-files
      help: Summarize license, copyright and other scans for key, top-level files. Key files are top-level codebase files such as COPYING, README and package manifests as reported by the --classify option "is_legal", "is_readme", "is_manifest" and "is_top_level" flags.
  doc:
    Summarize a scan at the codebase level for only key files.

--------------------------------------------
Plugin: scancode_pre_scan:classify  class: summarycode.classify:FileClassifier
  codebase_attributes:
  resource_attributes: is_legal, is_manifest, is_readme, is_top_level, is_key_file
  sort_order: 50
  required_plugins:
  options:
    help_group: pre-scan, name: classify: --classify
      help: Classify files with flags telling if the file is a legal, or readme or test file, etc.
  doc:
    Classify a file such as a COPYING file or a package manifest with a flag.

--------------------------------------------
Plugin: scancode_pre_scan:facet  class: summarycode.facet:AddFacet
  codebase_attributes:
  resource_attributes: facets
  sort_order: 20
  required_plugins:
  options:
    help_group: pre-scan, name: facet: --facet
      help: Add the <facet> to files with a path matching <pattern>.
  doc:
    Assign one or more "facet" to each file (and NOT to directories). Facets are
    a way to qualify that some part of the scanned code may be core code vs.
    test vs. data, etc.

--------------------------------------------
Plugin: scancode_pre_scan:ignore  class: scancode.plugin_ignore:ProcessIgnore
  codebase_attributes:
  resource_attributes:
  sort_order: 100
  required_plugins:
  options:
    help_group: pre-scan, name: ignore: --ignore
      help: Ignore files matching <pattern>.
    help_group: pre-scan, name: include: --include
      help: Include files matching <pattern>.
  doc:
    Include or ignore files matching patterns.

--------------------------------------------
Plugin: scancode_scan:copyrights  class: cluecode.plugin_copyright:CopyrightScanner
  codebase_attributes:
  resource_attributes: copyrights, holders, authors
  sort_order: 4
  required_plugins:
  options:
    help_group: primary scans, name: copyright: -c, --copyright
      help: Scan <input> for copyrights.
  doc:
    Scan a Resource for copyrights.

--------------------------------------------
Plugin: scancode_scan:emails  class: cluecode.plugin_email:EmailScanner
  codebase_attributes:
  resource_attributes: emails
  sort_order: 8
  required_plugins:
  options:
    help_group: other scans, name: email: -e, --email
      help: Scan <input> for emails.
    help_group: scan options, name: max_email: --max-email
      help: Report only up to INT emails found in a file. Use 0 for no limit.
  doc:
    Scan a Resource for emails.

--------------------------------------------
Plugin: scancode_scan:generated  class: summarycode.generated:GeneratedCodeDetector
  codebase_attributes:
  resource_attributes: is_generated
  sort_order: 50
  required_plugins:
  options:
    help_group: other scans, name: generated: --generated
      help: Classify automatically generated code files with a flag.
  doc:
    Tag a file as generated.

--------------------------------------------
Plugin: scancode_scan:info  class: scancode.plugin_info:InfoScanner
  codebase_attributes:
  resource_attributes: date, sha1, md5, mime_type, file_type, programming_language, is_binary, is_text, is_archive, is_media, is_source, is_script
  sort_order: 0
  required_plugins:
  options:
    help_group: other scans, name: info: -i, --info
      help: Scan <input> for file information (size, checksums, etc).
  doc:
    Scan a file Resource for miscellaneous information such as mime/filetype and
    basic checksums.

--------------------------------------------
Plugin: scancode_scan:licenses  class: licensedcode.plugin_license:LicenseScanner
  codebase_attributes:
  resource_attributes: licenses, license_expressions
  sort_order: 2
  required_plugins:
  options:
    help_group: primary scans, name: license: -l, --license
      help: Scan <input> for licenses.
    help_group: scan options, name: license_score: --license-score
      help: Do not return license matches with a score lower than this score. A number between 0 and 100.
    help_group: scan options, name: license_text: --license-text
      help: Include the detected licenses matched text.
    help_group: scan options, name: license_text_diagnostics: --license-text-diagnostics
      help: In the matched license text, include diagnostic highlights surrounding with square brackets [] words that are not matched.
    help_group: scan options, name: license_url_template: --license-url-template
      help: Set the template URL used for the license reference URLs. Curly braces ({}) are replaced by the license key.
    help_group: scan options, name: license_diag: --license-diag
      help: (DEPRECATED: this is always included by default now). Include diagnostic information in license scan results.
    help_group: miscellaneous, name: reindex_licenses: --reindex-licenses
      help: Check the license index cache and reindex if needed and exit.
  doc:
    Scan a Resource for licenses.

--------------------------------------------
Plugin: scancode_scan:packages  class: packagedcode.plugin_package:PackageScanner
  codebase_attributes:
  resource_attributes: packages
  sort_order: 6
  required_plugins: scan:licenses
  options:
    help_group: primary scans, name: package: -p, --package
      help: Scan <input> for package manifests and packages.
    help_group: documentation, name: list_packages: --list-packages
      help: Show the list of supported package types and exit.
  doc:
    Scan a Resource for Package manifests and report these as "packages" at the
    right file or directory level.

--------------------------------------------
Plugin: scancode_scan:urls  class: cluecode.plugin_url:UrlScanner
  codebase_attributes:
  resource_attributes: urls
  sort_order: 10
  required_plugins:
  options:
    help_group: other scans, name: url: -u, --url
      help: Scan <input> for urls.
    help_group: scan options, name: max_url: --max-url
      help: Report only up to INT urls found in a file. Use 0 for no limit.
  doc:
    Scan a Resource for URLs.
--list-packages Option

This shows all the types of packages that can be scanned using Scancode. These are located in packagedcode i.e. Code used to parse various package formats.

All Available Options

This section contains an exhaustive list of all Scancode options, arranged in various sections. The sections are as follows:

  • Basic Scan Options

  • Core Scan Options

  • Output Formats

  • Controlling Output and Filters

  • Pre-Scan Options

  • Post-Scan Options

There’s also another section for extractcode options.

The order of the sections and all their options is the same as in the :ref:’cli_help_text’, available in the command line.

Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.

All “Basic” Scan Options

Option lists are two-column lists of command-line options and descriptions, documenting a program’s options. For example:

-c, --copyright

Scan <input> for copyrights.

Sub-Options:

  • --consolidate

-l, --license

Scan <input> for licenses.

Sub-Options:

  • --consolidate

  • --license-score INT

  • --license-text

  • --license-url-template TEXT

  • --license-text-diagnostics

  • --is-license-text

-p, --package

Scan <input> for packages.

Sub-Options:

  • --consolidate

-e, --email

Scan <input> for emails.

Sub-Options:

  • --max-email INT

-u, --url

Scan <input> for urls.

Sub-Options:

  • --max-url INT

-i, --info

Include information such as:

  • Size,

  • Type,

  • Date,

  • Programming language,

  • sha1 and md5 hashes,

  • binary/text/archive/media/source/script flags

  • Additional options through more CLI options

Sub-Options:

  • --mark-source

Note

Unlike previous 2.x versions, -c, -l, and -p are not default. If any of combination of these options are used, ScanCode only performs that specific task, and not the others. scancode -e only scans for emails, and doesn’t scan for copyright/license/packages/general information.

Note

These options, i.e. -c, -l, -p, -e, -u, and -i can be used together. As in, instead of scancode -c -i -p, you can write scancode -cip and it will be the same.

--generated

Classify automatically generated code files with a flag.

--max-email INT

Report only up to INT emails found in a file. Use 0 for no limit. [Default: 50]

Sub-Option of - --email

--max-url INT

Report only up to INT urls found in a file. Use 0 for no limit. [Default: 50]

Sub-Option of - --url

--license-score INTEGER

Do not return license matches with scores lower than this score. A number between 0 and 100. [Default: 0] Here, a bigger number means a better match, i.e. Setting a higher license score translates to a higher threshold (with equal or less number of matches).

Sub-Option of - --license

--license-text

Include the matched text for the detected licenses in the output report.

Sub-Option of - --license

Sub-Options:

  • --license-text-diagnostics

  • --is-license-text

--license-url-template TEXT

Set the template URL used for the license reference URLs.

In a template URL, curly braces ({}) are replaced by the license key. [Default: https://enterprise.dejacode.com/urn/urn:dje:license:{}]

Sub-Option of - --license

--license-text-diagnostics

In the matched license text, include diagnostic highlights surrounding with square brackets [] words that are not matched.

Sub-Option of - --license and --license-text


All Extractcode Options

This is intended to be used as an input preparation step, before running the scan. Archives found in an extracted archive are extracted recursively by default. Extraction is done in-place in a directory named ‘-extract’ side-by-side with an archive.

To extract the packages in the samples directory

extractcode samples

This extracts the zlib.tar.gz package:

_images/extractcode.png
--shallow

Do not extract recursively nested archives (e.g. Not archives in archives).

--verbose

Print verbose file-by-file progress messages.

--quiet

Do not print any summary or progress message.

-h, --help

Show the extractcode help message and exit.

--about

Show information about ScanCode and licensing and exit.

--version

Show the version and exit.


All “Core” Scan Options
-n, --processes INTEGER

Scan <input> using n parallel processes. [Default: 1]

--verbose

Print verbose file-by-file progress messages.

--quiet

Do not print summary or progress messages.

--timeout FLOAT

Stop scanning a file if scanning takes longer than a timeout in seconds. [Default: 120]

--reindex-licenses

Force a check and possible reindexing of the cached license index.

--from-json

Load codebase from an existing JSON scan

--max-in-memory INTEGER

Maximum number of files and directories scan details kept in memory during a scan. Additional files and directories scan details above this number are cached on-disk rather than in memory. Use 0 to use unlimited memory and disable on-disk caching. Use -1 to use only on-disk caching. [Default: 10000]

Note

All the Core Options are independent options, i.e. They don’t depend on other options.


All Scan Output Options
--json FILE

Write scan output as compact JSON to FILE.

--json-pp FILE

Write scan output as pretty-printed JSON to FILE.

--json-lines FILE

Write scan output as JSON Lines to FILE.

--csv FILE

Write scan output as CSV to FILE.

--html FILE

Write scan output as HTML to FILE.

--custom-output

Write scan output to FILE formatted with the custom Jinja template file.

Mandatory Sub-option:

  • --custom-template FILE

--custom-template FILE

Use this Jinja template FILE as a custom template.

Sub-Option of: --custom-output

--spdx-rdf FILE

Write scan output as SPDX RDF to FILE.

--spdx-tv FILE

Write scan output as SPDX Tag/Value to FILE.

--html-app FILE

Write scan output as a mini HTML application to FILE.

Warning

The html-app feature has been deprecated and you should use Scancode Workbench instead to visualize scan results. The official Repository link. Also refer How to Visualize Scan results.


All “Output Control” Scan Options
--strip-root

Strip the root directory segment of all paths.

--full-root

Report full, absolute paths.

Note

The options --strip-root and --full-root can’t be used together, i.e. Any one option may be used in a single scan.

Note

The default is to always include the last directory segment of the scanned path such that all paths have a common root directory.

--ignore-author <pattern>

Ignore a file (and all its findings) if an author contains a match to the <pattern> regular expression.

--ignore-copyright-holder <pattern>

Ignore a file (and all its findings) if a copyright holder contains a match to the <pattern> regular expression.

Note

Note that this both the options --ignore-author and --ignore-copyright-holder will ignore a file even if it has other scanned data such as a license or errors.

--only-findings

Only return files or directories with findings for the requested scans. Files and directories without findings are omitted (file information is not treated as findings).


All “Pre-Scan” Options
--ignore <pattern>

Ignore files matching <pattern>.

--include <pattern>

Include files matching <pattern>.

--classify

Classify files with flags telling if the file is a legal, or readme or test file, etc.

Sub-Options:

  • --license-clarity-score

  • --summary-key-files

--facet <facet_pattern>

Here <facet_pattern> represents <facet>=<pattern>. Add the <facet> to files with a path matching <pattern>.

Sub-Options:

  • --summary-by-facet


All “Post-Scan” Options
--mark-source

Set the “is_source” flag to true for directories that contain over 90% of source files as direct children and descendants. Count the number of source files in a directory as a new “source_file_counts” attribute

Sub-Option of - --url

--consolidate

Group resources by Packages or license and copyright holder and return those groupings as a list of consolidated packages and a list of consolidated components.

Sub-Option of - --copyright, --license and --packages.

--filter-clues

Filter redundant duplicated clues already contained in detected licenses, copyright texts and notices.

--is-license-text

Set the “is_license_text” flag to true for files that contain mostly license texts and notices (e.g. over 90% of the content).

Sub-Option of - --info and --license-text.

Warning

--is-license-text is an experimental Option.

--license-clarity-score

Compute a summary license clarity score at the codebase level.

Sub-Option of - --classify.

--license-policy FILE

Load a License Policy file and apply it to the scan at the Resource level.

--summary

Summarize license, copyright and other scans at the codebase level.

Sub-Options:

  • --summary-by-facet

  • --summary-key-files

  • --summary-with-details

--summary-by-facet

Summarize license, copyright and other scans and group the results by facet.

Sub-Option of - --summary and --facet.

--summary-key-files

Summarize license, copyright and other scans for key, top-level files. Key files are top- level codebase files such as COPYING, README and package manifests as reported by the --classify option “is_legal”, “is_readme”, “is_manifest” and “is_top_level” flags.

Sub-Option of - --classify and --summary.

--summary-with-details

Summarize license, copyright and other scans at the codebase level, keeping intermediate details at the file and directory level.

How to Run a Scan

In this simple tutorial example, we perform a basic scan on the samples directory distributed by default with Scancode.

Prerequisites

Refer Prerequisites to make sure the correct Python Interpreters and other prerequisites are satisfied.

Setting up a Virtual Environment

ScanCode Toolkit supports Python 3 in 3.2.x and later versions, so if you are using 3.2.x or later versions, you should create a virtual environment using the Virtualenv tool with a python 3.6 interpreter.

The following commands set up and activate the Virtual Environment venv-scancode-py3:

virtualenv -p /usr/bin/python3.6 venv-scancode-py3
source venv-scancode-py3/bin/activate

If you are using Scancode Toolkit 3.1.0 and earlier versions, they are not compatible with Python 3.x so you should create the virtual environment with a python 2.7 interpreter:

virtualenv -p /usr/bin/python2.7 venv-scancode-py2
source venv-scancode-py2/bin/activate
Setting up Scancode Toolkit

Get ScanCode Toolkit from pip:

pip install scancode-toolkit

Note

You can install a specific version of Scancode Toolkit like scancode-toolkit==3.1.1.

Looking into Files

As mentioned previously, we are going to perform the scan on the samples directory distributed by default with Scancode Toolkit. Here’s the directory structure and respective files:

_images/files_sample.png

We notice here that the sample files contain a package zlib.tar.gz. So we have to extract the archive before running the scan, to also scan the files inside this package.

Performing Extraction

To extract the packages inside samples directory:

extractcode samples

This extracts the zlib.tar.gz package:

_images/extractcode.png

Note

--shallow option can be used to recursively extract packages.

Deciding Scan Options

These are some common scan options you should consider using before you start the actual scan, according to your requirements.

  1. The Basic Scan options, i.e. -c, -l, -p, -e, -u, and -i are to be decided, according to your requirements. If you do not need one specific type of information (say, licenses), consider removing it, because the more things you scan for, longer it will take for the scan to complete.

Note

You have to select these options explicitly, as they are not default anymore from versions 3.x, unlike earlier versions having -clp as default.

  1. --license-score INTEGER is to be set if license matching accuracy is desired (Default is 0, and increasing this means a more accurate match). Also, using --license-text includes the matched text to the result.

  2. -n INTEGER option can be used to speed up the scan using multiple parallel processes.

  3. --timeout FLOAT option can be used to skip a file taking a lot of time to scan.

  4. --ignore <pattern> can be used to skip certain group of files.

  5. <OUTPUT FORMAT OPTION(s)> is also a very important decision when you want to use the output for specific tasks/have requirements. Here we are using json as ScanCode Workbench imports json files only.

For the complete list of options, refer All Available Options.

Running The Scan

Now, run the scan with the options decided:

scancode -clpeui -n 2 --ignore "*.java" --json-pp sample.json samples

A Progress report is shown:

Setup plugins...
Collect file inventory...
Scan files for: info, licenses, copyrights, packages, emails, urls with 2 process(es)...
[####################] 29
Scanning done.
Summary:        info, licenses, copyrights, packages, emails, urls with 2 process(es)
Errors count:   0
Scan Speed:     1.09 files/sec. 40.67 KB/sec.
Initial counts: 49 resource(s): 36 file(s) and 13 directorie(s)
Final counts:   42 resource(s): 29 file(s) and 13 directorie(s) for 1.06 MB
Timings:
  scan_start: 2019-09-24T203514.573671
  scan_end:   2019-09-24T203545.649805
  setup_scan:licenses: 4.30s
  setup: 4.30s
  scan: 26.62s
  total: 31.14s
Removing temporary files...done.
Basic Options
All “Basic” Scan Options

Option lists are two-column lists of command-line options and descriptions, documenting a program’s options. For example:

-c, --copyright

Scan <input> for copyrights.

Sub-Options:

  • --consolidate

-l, --license

Scan <input> for licenses.

Sub-Options:

  • --consolidate

  • --license-score INT

  • --license-text

  • --license-url-template TEXT

  • --license-text-diagnostics

  • --is-license-text

-p, --package

Scan <input> for packages.

Sub-Options:

  • --consolidate

-e, --email

Scan <input> for emails.

Sub-Options:

  • --max-email INT

-u, --url

Scan <input> for urls.

Sub-Options:

  • --max-url INT

-i, --info

Include information such as:

  • Size,

  • Type,

  • Date,

  • Programming language,

  • sha1 and md5 hashes,

  • binary/text/archive/media/source/script flags

  • Additional options through more CLI options

Sub-Options:

  • --mark-source

Note

Unlike previous 2.x versions, -c, -l, and -p are not default. If any of combination of these options are used, ScanCode only performs that specific task, and not the others. scancode -e only scans for emails, and doesn’t scan for copyright/license/packages/general information.

Note

These options, i.e. -c, -l, -p, -e, -u, and -i can be used together. As in, instead of scancode -c -i -p, you can write scancode -cip and it will be the same.

--generated

Classify automatically generated code files with a flag.

--max-email INT

Report only up to INT emails found in a file. Use 0 for no limit. [Default: 50]

Sub-Option of - --email

--max-url INT

Report only up to INT urls found in a file. Use 0 for no limit. [Default: 50]

Sub-Option of - --url

--license-score INTEGER

Do not return license matches with scores lower than this score. A number between 0 and 100. [Default: 0] Here, a bigger number means a better match, i.e. Setting a higher license score translates to a higher threshold (with equal or less number of matches).

Sub-Option of - --license

--license-text

Include the matched text for the detected licenses in the output report.

Sub-Option of - --license

Sub-Options:

  • --license-text-diagnostics

  • --is-license-text

--license-url-template TEXT

Set the template URL used for the license reference URLs.

In a template URL, curly braces ({}) are replaced by the license key. [Default: https://enterprise.dejacode.com/urn/urn:dje:license:{}]

Sub-Option of - --license

--license-text-diagnostics

In the matched license text, include diagnostic highlights surrounding with square brackets [] words that are not matched.

Sub-Option of - --license and --license-text


Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.


--generated Options

The --generated option classifies automatically generated code files with a flag.

An example of using --generated in a scan:

scancode -clpieu --json-pp output.json samples --generated

In the results, for each file the following attribute is added with it’s corresponding true/false value

"is_generated": true

In the samples folder, the following files have a true value for their is_generated attribute:

"samples/zlib/dotzlib/LICENSE_1_0.txt"
"samples/JGroups/licenses/apache-2.0.txt"

--max-email Options

Dependency

The option --max-email is a sub-option of and requires the option --email.

If in the files that are scanned, in individual files, there are a lot of emails (i.e lists) which are unnecessary and clutter the scan results, --max-email option can be used to report emails only up to a limit in individual files.

Some important INTEGER values of the --max-email INTEGER option:

  • 0 - No limit, include all emails.

  • 50 - Default.

An example usage:

scancode -clpieu --json-pp output.json samples --max-email 5

This only reports 5 email addresses per file and ignores the rest.


--max-url Options

Dependency

The option --max-url is a sub-option of and requires the option --url.

If in the files that are scanned, in individual files, there are a lot of links to other websites (i.e url lists) which are unnecessary and clutter the scan results, --max-url option can be used to report urls only up to a limit in individual files.

Some important INTEGER values of the --max-url INTEGER option:

  • 0 - No limit, include all urls.

  • 50 - Default.

An example usage:

scancode -clpieu --json-pp output.json samples --max-url 10

This only reports 10 urls per file and ignores the rest.


--license-score Options

Dependency

The option --license-score is a sub-option of and requires the option --license.

License matching strictness, i.e. How closely matched licenses are detected in a scan, can be modified by using this --license-score option.

Some important INTEGER values of the --license-score INTEGER option:

  • 0 - Default and Lowest Value, All matches are reported.

  • 100 - Highest Value, Only licenses with a much better match are reported

Here, a bigger number means a better match, i.e. Setting a higher license score translates to a higher threshold for matching licenses (with equal or less number of license matches).

An example usage:

scancode -clpieu --json-pp output.json samples --license-score 70

Here’s the license results on setting the integer value to 100, Vs. the default value 0. This is visualized using ScanCode workbench in the License Info Dashboard.

License scan results of Samples Directory.
_images/core_lic_score_0.png

License Score 0 (Default).

_images/core_lic_score_100.png

License Score 100.


--license-text Options

Dependency

The option --license-text is a sub-option of and requires the option --license.

Sub-Option

The option --license-text-diagnostics and --is-license-text are sub-options of --license-text. --is-license-text is a Post-Scan Option.

With the --license-text option, the scan results attribute “matched text” includes the matched text for the detected license.

An example Scan:

scancode -cplieu --json-pp output.json samples --license-text

An example matched text included in the results is as follows:

"matched_text":
 "  This software is provided 'as-is', without any express or implied
 warranty.  In no event will the authors be held liable for any damages
 arising from the use of this software.
 Permission is granted to anyone to use this software for any purpose,
 including commercial applications, and to alter it and redistribute it
 freely, subject to the following restrictions:
 1. The origin of this software must not be misrepresented; you must not
 claim that you wrote the original software. If you use this software
 in a product, an acknowledgment in the product documentation would be
 appreciated but is not required.
 2. Altered source versions must be plainly marked as such, and must not be
 misrepresented as being the original software.
 3. This notice may not be removed or altered from any source distribution.

 Jean-loup Gailly        Mark Adler
 jloup@gzip.org          madler@alumni.caltech.edu"
  • The file in which this license was detected: samples/arch/zlib.tar.gz-extract/zlib-1.2.8/zlib.h

  • License name: “ZLIB License”


--license-url-template Options

Dependency

The option --license-url-template is a sub-option of and requires the option --license.

The --license-url-template option sets the template URL used for the license reference URLs.

The default template URL is : [https://enterprise.dejacode.com/urn/urn:dje:license:{}] In a template URL, curly braces ({}) are replaced by the license key.

So, by default the license reference URL points to the dejacode page for that license.

A scan example using the --license-url-template TEXT option

scancode -clpieu --json-pp output.json samples --license-url-template https://github.com/nexB/scancode-toolkit/tree/develop/src/licensedcode/data/licenses/{}.yml

In a normal scan, reference url for “ZLIB License” is as follows:

"reference_url": "https://enterprise.dejacode.com/urn/urn:dje:license:zlib",

After using the option in the following manner:

``--license-url-template https://github.com/nexB/scancode-toolkit/tree/develop/src/licensedcode/data/licenses/{}``

the reference URL changes to this zlib.yml file:

"reference_url": "https://github.com/nexB/scancode-toolkit/tree/develop/src/licensedcode/data/licenses/zlib.yml",

The reference URL changes for all detected licenses in the scan, across the scan result file.


--license-text-diagnostics Options

Dependency

The option --license-text-diagnostics is a sub-option of and requires the options --license and --license-text.

In the matched license text, include diagnostic highlights surrounding with square brackets [] words that are not matched.

In a normal scan, whole lines of text are included in the matched license text, including parts that are possibly unmatched.

An example Scan:

scancode -cplieu --json-pp output.json samples --license-text --license-text-diagnostics

Running a scan on the samples directory with --license-text --license-text-diagnostics options, causes the following difference in the scan result of the file samples/JGroups/licenses/bouncycastle.txt.

Without Diagnostics:

"matched_text":
"License Copyright (c) 2000 - 2006 The Legion Of The Bouncy Castle
(http://www.bouncycastle.org) Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation files (the \"Software\"),
to deal in the Software without restriction

With Diagnostics on:

"matched_text":
"License [Copyright] ([c]) [2000] - [2006] [The] [Legion] [Of] [The] [Bouncy] [Castle]
([http]://[www].[bouncycastle].[org]) Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation files (the \"Software\"),
to deal in the Software without restriction,
Core Options
All “Core” Scan Options
-n, --processes INTEGER

Scan <input> using n parallel processes. [Default: 1]

--verbose

Print verbose file-by-file progress messages.

--quiet

Do not print summary or progress messages.

--timeout FLOAT

Stop scanning a file if scanning takes longer than a timeout in seconds. [Default: 120]

--reindex-licenses

Force a check and possible reindexing of the cached license index.

--from-json

Load codebase from an existing JSON scan

--max-in-memory INTEGER

Maximum number of files and directories scan details kept in memory during a scan. Additional files and directories scan details above this number are cached on-disk rather than in memory. Use 0 to use unlimited memory and disable on-disk caching. Use -1 to use only on-disk caching. [Default: 10000]

Note

All the Core Options are independent options, i.e. They don’t depend on other options.


Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.


Comparing Progress Message Options

Default Progress Message:

Scanning files for: infos, licenses, copyrights, packages, emails, urls with 1 process(es)...
Building license detection index...Done.
Scanning files...
[####################] 43
Scanning done.
Scan statistics: 43 files scanned in 33s.
Scan options:    infos, licenses, copyrights, packages, emails, urls with 1 process(es).
Scanning speed:  1.4 files per sec.
Scanning time:   30s.
Indexing time:   2s.
Saving results.

Progress Message with ``–verbose``:

Scanning files for: infos, licenses, copyrights, packages, emails, urls with 1 process(es)...
Building license detection index...Done.
Scanning files...
Scanned: screenshot.png
Scanned: README
...
Scanned: zlib/dotzlib/ChecksumImpl.cs
Scanned: zlib/dotzlib/readme.txt
Scanned: zlib/gcc_gvmat64/gvmat64.S
Scanned: zlib/ada/zlib.ads
Scanned: zlib/infback9/infback9.c
Scanned: zlib/infback9/infback9.h
Scanned: arch/zlib.tar.gz
Scanning done.
Scan statistics: 43 files scanned in 29s.
Scan options:    infos, licenses, copyrights, packages, emails, urls with 1 process(es).
Scanning speed:  1.58 files per sec.
Scanning time:   27s.
Indexing time:   2s.
Saving results.

So, with --verbose enables, progress messages for individual files are shown.

With the ``–quiet`` option enabled, nothing is printed on the Command Line.


--timeout Option

This option sets scan timeout for each file (and not the entire scan). If some file scan exceeds the specified timeout, that file isn’t scanned anymore and the next file scanning starts. This helps avoiding very large/long files, and saves time.

Also the number (timeout in seconds) to be followed by this option can be a floating point number, i.e. 1.5467.


--reindex-licenses Option

ScanCode maintains a license index to search for and detect licenses. When Scancode is configured for the first time, a license index is built and used in every scan thereafter.

This --reindex-licenses option rebuilds the license index. Running a scan with this option displays the following message to the terminal in addition to what it normally shows:

Checking and rebuilding the license index...

--from-json Option

If you want to input scan results from a .json file, and run a scan again on those same files, with some other options/output format, you can do so using the --from-json option.

An example scan command using --from-json:

scancode --from-json sample.json --json-pp sample_2.json --classify

This inputs the scan results from sample.json, runs the post-scan plugin --classify and outputs the results for this scan to sample_2.json.


--max-in-memory Option

During a scan, as individual files are scanned, the scan details for those files are kept on memory till the scan is completed. Then after the scan is completed, they are written in the specified output format.

Now, if the scan involves a very large number of files, they might not fit in the memory during the scan. For this reason, disk-caching can be used for some/all of the files.

Some important INTEGER values of the --max-in-memory INTEGER option:

  • 0 - Unlimited Memory, store all the file/directory scan results on memory

  • -1 - Use only Disk-Caching, store all the file/directory scan results on disk

  • 10000 - Default, store 10,000 file/directory scan results on memory and the rest on disk

An example usage:

scancode -clieu --json-pp sample.json samples --max-in-memory -1
Scancode Output Formats

Scan results generated by Scancode are available in different formats, to be specified by the following options.

All Scan Output Options
--json FILE

Write scan output as compact JSON to FILE.

--json-pp FILE

Write scan output as pretty-printed JSON to FILE.

--json-lines FILE

Write scan output as JSON Lines to FILE.

--csv FILE

Write scan output as CSV to FILE.

--html FILE

Write scan output as HTML to FILE.

--custom-output

Write scan output to FILE formatted with the custom Jinja template file.

Mandatory Sub-option:

  • --custom-template FILE

--custom-template FILE

Use this Jinja template FILE as a custom template.

Sub-Option of: --custom-output

--spdx-rdf FILE

Write scan output as SPDX RDF to FILE.

--spdx-tv FILE

Write scan output as SPDX Tag/Value to FILE.

--html-app FILE

Write scan output as a mini HTML application to FILE.

Warning

The html-app feature has been deprecated and you should use Scancode Workbench instead to visualize scan results. The official Repository link. Also refer How to Visualize Scan results.

Note

You can Output Scan Results in two different file formats simultaniously in one Scan. An example - scancode -clpieu --json-pp output.json --html output.html samples.

Note

All the examples and snippets that follows heas been generated by scanning the samples folder distributed with scancode-toolkit.


Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.



--json FILE

Among the ScanCode Output Formats, json is the most important one, and is recommended over others. Scancode Workbench and other applications that use Scancode Result data as input accept only the json format.

Note

There isn’t any default output option in Scancode Versions 3.x, unlike 2.x versions (which had json as default).

The following code performs a scan on the samples directory, and publishes the results in json format:

scancode -clpieu --json output.json samples

Note

The default json format prints the whole report without line breaks/spaces/indentations, which can be ugly to look at.

_images/json_ugly.png

The entire JSON file is structured in the following manner:

At first some general information on the scan, what options were used, the number of files etc. And then all the files follow.

{
  "headers": [
    {
      "tool_name": "scancode-toolkit",
      "tool_version": "3.1.1",
      "options": {
        "input": [
          "samples/"
        ],
        "--copyright": true,
        "--email": true,
        "--info": true,
        "--json-pp": "output.json",
        "--license": true,
        "--package": true,
        "--url": true
      },
      "notice": "Generated with ScanCode and provided on an \"AS IS\" BASIS, WITHOUT WARRANTIES\nOR CONDITIONS OF ANY KIND, either express or implied. No content created from\nScanCode should be considered or used as legal advice. Consult an Attorney\nfor any legal advice.\nScanCode is a free software code scanning tool from nexB Inc. and others.\nVisit https://github.com/nexB/scancode-toolkit/ for support and download.",
      "start_timestamp": "2019-10-19T191117.292858",
      "end_timestamp": "2019-10-19T191219.743133",
      "message": null,
      "errors": [],
      "extra_data": {
        "files_count": 36
      }
    }
  ],
  "files": [
    {
      "path": "samples",
      "type": "directory",
      ...
      ...
      ...
      "scan_errors": []
    },
    {
      "path": "samples/README",
      "type": "file",
      "name": "README",
      "base_name": "README",
      "extension": "",
      "size": 236,
      "date": "2019-02-12",
      "sha1": "2e07e32c52d607204fad196052d70e3d18fb8636",
      "md5": "effc6856ef85a9250fb1a470792b3f38",
      "mime_type": "text/plain",
      "file_type": "ASCII text",
      "programming_language": null,
      "is_binary": false,
      "is_text": true,
      "is_archive": false,
      "is_media": false,
      "is_source": false,
      "is_script": false,
      "licenses": [],
      "license_expressions": [],
      "copyrights": [],
      "holders": [],
      "authors": [],
      "packages": [],
      "emails": [],
      "urls": [],
      "files_count": 0,
      "dirs_count": 0,
      "size_count": 0,
      "scan_errors": []
    },
    ...
    ...
    ...
    {
      "path": "samples/zlib/iostream2/zstream_test.cpp",
      "type": "file",
      "name": "zstream_test.cpp",
      "base_name": "zstream_test",
      "extension": ".cpp",
      "size": 711,
      "date": "2019-02-12",
      ...
      ...
      ...
      "scan_errors": []
    }
  ]
}

--json-pp FILE

json-pp stands for JSON Pretty-Print format. In the previous format, i.e. Simple json, the whole output is printed in one line, which isn’t well suited for getting information if you’re looking at the file itself (or printing at stdout). So this option formats the output results in json but in a properly spaced and indented manner, and is easy to look at.

The following code performs a scan on the samples directory, and publishes the results in json-pp format:

scancode -clpieu --json-pp output.json samples

A sample JSON output for an individual file will look like:

{
  "path": "samples/zlib/iostream2/zstream.h",
  "type": "file",
  "name": "zstream.h",
  "base_name": "zstream",
  "extension": ".h",
  "size": 9283,
  "date": "2019-02-12",
  "sha1": "fca4540d490fff36bb90fd801cf9cd8fc695bb17",
  "md5": "a980b61c1e8be68d5cdb1236ba6b43e7",
  "mime_type": "text/x-c++",
  "file_type": "C++ source, ASCII text",
  "programming_language": "C++",
  "is_binary": false,
  "is_text": true,
  "is_archive": false,
  "is_media": false,
  "is_source": true,
  "is_script": false,
  "licenses": [
    {
      "key": "mit-old-style",
      "score": 100.0,
      "name": "MIT Old Style",
      "short_name": "MIT Old Style",
      "category": "Permissive",
      "is_exception": false,
      "owner": "MIT",
      "homepage_url": "http://fedoraproject.org/wiki/Licensing:MIT#Old_Style",
      "text_url": "http://fedoraproject.org/wiki/Licensing:MIT#Old_Style",
      "reference_url": "https://enterprise.dejacode.com/urn/urn:dje:license:mit-old-style",
      "spdx_license_key": null,
      "spdx_url": "",
      "start_line": 9,
      "end_line": 15,
      "matched_rule": {
        "identifier": "mit-old-style_cmr-no_1.RULE",
        "license_expression": "mit-old-style",
        "licenses": [
          "mit-old-style"
        ],
        "is_license_text": true,
        "is_license_notice": false,
        "is_license_reference": false,
        "is_license_tag": false,
        "matcher": "2-aho",
        "rule_length": 71,
        "matched_length": 71,
        "match_coverage": 100.0,
        "rule_relevance": 100
      }
    }
  ],
  "license_expressions": [
    "mit-old-style"
  ],
  "copyrights": [
    {
      "value": "Copyright (c) 1997 Christian Michelsen Research AS Advanced Computing",
      "start_line": 3,
      "end_line": 5
    }
  ],
  "holders": [
    {
      "value": "Christian Michelsen Research AS Advanced Computing",
      "start_line": 3,
      "end_line": 5
    }
  ],
  "authors": [],
  "packages": [],
  "emails": [],
  "urls": [
    {
      "url": "http://www.cmr.no/",
      "start_line": 7,
      "end_line": 7
    }
  ],
  "files_count": 0,
  "dirs_count": 0,
  "size_count": 0,
  "scan_errors": []
},

This is the recommended Output option for Scancode Toolkit.


--json-lines FILE

ScanCode also has a --json-lines format option, where each report of a file scanned is formatted in one line.

The following code performs a scan on the samples directory, and publishes the results in json-lines format:

scancode -clpieu --json-lines output.json samples

Here is a sample line from a report generated by the jsonlines format:

{"files":[{"path":"samples/zlib/ada",licenses":[],"copyrights":[],"packages":[]}]}

The header information is also formatted in one line (i.e. The First Line of the file).

The whole Output file looks like:

{"headers":[{"tool_name":"scancode-toolkit","tool_version":"3.1.1","options":{"input":["samples/"],"--copyright":true,"--email":true,"--info":true,"--json-lines":"output.json","--license":true,"--package":true,"--url":true},"notice":"Generated with ScanCode and provided on an \"AS IS\" BASIS, WITHOUT WARRANTIES\nOR CONDITIONS OF ANY KIND, either express or implied. No content created from\nScanCode should be considered or used as legal advice. Consult an Attorney\nfor any legal advice.\nScanCode is a free software code scanning tool from nexB Inc. and others.\nVisit https://github.com/nexB/scancode-toolkit/ for support and download.","start_timestamp":"2019-10-19T210920.143831","end_timestamp":"2019-10-19T211052.048182","message":null,"errors":[],"extra_data":{"files_count":36}}]}
{"files":[{"path":"samples" ... "scan_errors":[]}]}
{"files":[{"path":"samples/README", ... "scan_errors":[]}]}
{"files":[{"path":"samples/screenshot.png", ... "scan_errors":[]}]}
{"files":[{"path":"samples/arch", ... "scan_errors":[]}]}
{"files":[{"path":"samples/arch/zlib.tar.gz", ... "scan_errors":[]}]}
{"files":[{"path":"samples/arch/zlib.tar.gz-extract", ... "scan_errors":[]}]}
{"files":[{"path":"samples/arch/zlib.tar.gz-extract/zlib-1.2.8", ... "scan_errors":[]}]}
{"files":[{"path":"samples/arch/zlib.tar.gz-extract/zlib-1.2.8/adler32.c", ... "scan_errors":[]}]}
{"files":[{"path":"samples/arch/zlib.tar.gz-extract/zlib-1.2.8/zlib.h", ... "scan_errors":[]}]}
{"files":[{"path":"samples/arch/zlib.tar.gz-extract/zlib-1.2.8/zutil.h", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/EULA", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/LICENSE", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/licenses", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/licenses/apache-1.1.txt", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/licenses/apache-2.0.txt", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/licenses/bouncycastle.txt", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/licenses/cpl-1.0.txt", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/licenses/lgpl.txt", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src/FixedMembershipToken.java", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src/GuardedBy.java", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src/ImmutableReference.java", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src/RATE_LIMITER.java", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src/RouterStub.java", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src/RouterStubManager.java", ... "scan_errors":[]}]}
{"files":[{"path":"samples/JGroups/src/S3_PING.java", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/adler32.c", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/deflate.c", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/deflate.h", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/zlib.h", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/zutil.c", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/zutil.h", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/ada", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/ada/zlib.ads", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/dotzlib", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/dotzlib/AssemblyInfo.cs", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/dotzlib/ChecksumImpl.cs", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/dotzlib/LICENSE_1_0.txt", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/dotzlib/readme.txt", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/gcc_gvmat64" ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/gcc_gvmat64/gvmat64.S" ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/infback9", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/infback9/infback9.c", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/infback9/infback9.h", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/iostream2", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/iostream2/zstream.h", ... "scan_errors":[]}]}
{"files":[{"path":"samples/zlib/iostream2/zstream_test.cpp", ... "scan_errors":[]}]}

Note

This jsonlines format also omits other file information like type, name, date, extension, sha1 and md5 hashes, programming language etc.


Comparing Different json Output Formats

Default --json Output:

_images/output_json.png

--json-pp Output:

_images/output_jsonpp.png

--json-lines Output:

_images/output_jsonlines.png

--spdx-rdf FILE

SPDX stands for “Software Package and Data Exchange” and is an open standard for communicating software bill of material information (including components, licenses, copyrights, and security references).

The following code performs a scan on the samples directory, and publishes the results in spdx-rdf format:

scancode -clpieu --spdx-rdf output.spdx samples

Learn more about SPDX specifications here and in this GitHub repository.

Here the file is structured as a dictionary of named properties and classes using W3C’s RDF Technology.

… figure:: data/output_spdx_rdf1.png


--spdx-tv FILE

This format is another SPDX variant, with the output file being structured in the following manner:

The following code performs a scan on the samples directory, and publishes the results in spdx-tv format:

scancode -clpieu --spdx-tv output.spdx samples

A SPDX-TV file starts with:

# Document Information

SPDXVersion: SPDX-2.1
DataLicense: CC0-1.0
DocumentComment: <text>Generated with ScanCode and provided on an "AS IS" BASIS, WITHOUT WARRANTIES
OR CONDITIONS OF ANY KIND, either express or implied. No content created from
ScanCode should be considered or used as legal advice. Consult an Attorney
for any legal advice.
ScanCode is a free software code scanning tool from nexB Inc. and others.
Visit https://github.com/nexB/scancode-toolkit/ for support and download.</text>


# Creation Info

Creator: Tool: ScanCode 2.2.1
Created: 2019-09-22T21:55:04Z

After a section titled #Packages, a list follows.

_images/output_spdx_tv_package.png

Each File information is listed under a #File title, for each of the files.

  • FileName

  • FileChecksum

  • LicenseConcluded

  • LicenseInfoInFile

  • FileCopyrightText

An example goes as follows:

_images/output_spdx_tv_file.png

After the files section, there’s a section for licenses under a #Licences title, with the following information for each license:

  • LicenseID

  • LicenseComment

  • ExtractedText

Here’s an example:

_images/output_spdx_tv_licenses.png

--html FILE

ScanCode supports formatting the Output result is a simple html format, to open with your favorite browser. This helps quick visualization of the detected license/copyright and other main information in the form of tables.

The following code performs a scan on the samples directory, and publishes the results in HTML format:

scancode -clpieu --html output.html samples

The HTML page generated has these following Tables:

  • Copyright and Licenses Information

  • File Information

  • Package Information

  • Licenses (Links to Dejacode/License Homepage)

_images/output_html1.png
_images/output_html2.png
_images/output_html3.png

--html-app FILE

ScanCode also supports formatting the output in a HTML visualization tool, which is more helpful than the standard HTML format.

Warning

The html-app feature has been deprecated and you should use Scancode Workbench instead to visualize scan results. The official Repository link. Also refer How to Visualize Scan results.

The following code performs a scan on the samples directory, and publishes the results in html-app format:

scancode -clpieu --csv output.html samples

The Files scanned are shown in the left sidebar, and the section on the right contains separate tabs for the following:

  • License Summary

  • Copyright Summary

  • Clues

  • File Details

  • Packages

Note

The HTML app also contains a Search option to easily find what you are looking for.

_images/output_html_app1.png
_images/output_html_app2.png
_images/output_html_app3.png

--csv FILE

ScanCode can publish results in the useful .csv format.

The following code performs a scan on the samples directory, and publishes the results in csv format:

scancode -lpceiu --csv sample.csv samples

The first line of the csv file contains the headings, and they are:

  • Resource,

  • type,

  • name,

  • base_name,

  • extension,

  • date,

  • size,

  • sha1,

  • md5,

  • files_count,

  • mime_type,

  • file_type,

  • programming_language,

  • is_binary,

  • is_text,

  • is_archive,

  • is_media,

  • is_source,

  • is_script,

  • scan_errors,

  • license__key,

  • license__score,

  • license__short_name,

  • license__category,

  • license__owner,

  • license__homepage_url,

  • license__text_url,

  • license__reference_url,

  • license__spdx_license_key,

  • license__spdx_url,

  • matched_rule__identifier,

  • matched_rule__license_choice,

  • matched_rule__licenses,

  • copyright,

  • copyright_holder,

  • author,

  • email,

  • start_line,

  • end_line,

  • url,

  • package__type,

  • package__name,

  • package__version,

  • package__primary_language,

  • package__summary,

  • package__description,

  • package__size,

  • package__release_date,

  • package__homepage_url,

  • package__notes,

  • package__bug_tracking_url,

  • package__vcs_repository,

  • package__copyright_top_level

Each subsequent line represents one element, i.e. can be any of the following:

  • license

  • copyright

  • package

  • email

  • url

So if there’s multiple elements in a file, they are each given an entry with the details mentioned earlier.

_images/output_csv.png

Custom Output Format

While the three built-in output formats are convenient for a verity of use-cases, one may wish to create their own output template, using the following arguments:

``--custom-output FILE --custom-template TEMP_FILE``

ScanCode makes this very easy, as it uses the popular Jinja2 template engine. Simply pass the path to the custom template to the --custom-template argument, or drop it in a folder to src/scancode/templates directory.

For example, if I wanted a simple CLI output I would create a template2.html with the particular data I wish to see. In this case, I am only interested in the license and copyright data for this particular scan.

## template.html:
[
    {% if files.license_copyright %}
        {% for location, data in files.license_copyright.items() %}
            {% for row in data %}
  location:"{{ location }}",
  {% if row.what == 'copyright' %}copyright:"{{ row.value|escape }}",{% endif %}
             {% endfor %}
         {% endfor %}
    {% endif %}
]

.. note::

    File name and extension does not matter for the template file.

Now I can run ScanCode using my newly created template:

$ scancode -clpeui --custom-output output.json --custom-template template.html samples
Scanning files...
  [####################################]  46
Scanning done.

Now are results are saved in output.json and we can easily view them with head output.json:

[
  location:"samples/JGroups/LICENSE",
  copyright:"Copyright (c) 1991, 1999 Free Software Foundation, Inc.",

  location:"samples/JGroups/LICENSE",
  copyright:"copyrighted by the Free Software Foundation",
]

For a more elaborate template, refer this default template given with Scancode, to generate HTML output with the --html output format option.

Documentation on Jinja templates.

Controlling Scancode Output and Filters
All “Output Control” Scan Options
--strip-root

Strip the root directory segment of all paths.

--full-root

Report full, absolute paths.

Note

The options --strip-root and --full-root can’t be used together, i.e. Any one option may be used in a single scan.

Note

The default is to always include the last directory segment of the scanned path such that all paths have a common root directory.

--ignore-author <pattern>

Ignore a file (and all its findings) if an author contains a match to the <pattern> regular expression.

--ignore-copyright-holder <pattern>

Ignore a file (and all its findings) if a copyright holder contains a match to the <pattern> regular expression.

Note

Note that this both the options --ignore-author and --ignore-copyright-holder will ignore a file even if it has other scanned data such as a license or errors.

--only-findings

Only return files or directories with findings for the requested scans. Files and directories without findings are omitted (file information is not treated as findings).


Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.


--strip-root Vs. --full-root

For a default scan of the “samples” folder, this a comparison between the default, strip-root and full-root options.

An example Scan

scancode -cplieu --json-pp output.json samples --full-root

These two changes only the “path” attribute of the file information. For this comparison we compare the “path” attributes of the file LICENSE inside JGroups directory.

The default path:

"path": "samples/JGroups/LICENSE",

For the --full-root option, the path relative to the Root of your local filesystem.

"path": "/home/ayansm/Desktop/GSoD/scancode-toolkit-versions/scancode-toolkit-2.2.1/samples/JGroups/LICENSE"

For the --strip-root option, the root directory (here samples) is removed from path :

"path": "JGroups/LICENSE"

Note

The options --strip-root and --full-root can’t be used together, i.e. Any one option may be used in a single scan.

Note

The default is to always include the last directory segment of the scanned path such that all paths have a common root directory.


--ignore-author <pattern> Option

In a normal scan, all files inside the directory specified as an input argument is scanned and subsequently included in the scan report. But if you want to run the scan on only some selective files, with some specific common author then --ignore-author option can be used to do the same.

This scan ignores all files with authors matching the string “Apache Software Foundation”:

scancode -cplieu --json-pp output.json samples --ignore-author "Apache Software Foundation"

More information on Glob Pattern Matching.

Note

Note that this both the options --ignore-author and --ignore-copyright-holder will ignore a file even if it has other scanned data such as a license or errors.



--only-findings Plugin

This option removes from the scan results, the files where nothing significant has been detected, like files which doesn’t contain any licenses, copyrights, emails or urls (if requested in the scan options), and isn’t a package.

An example Scan:

scancode -cplieu --json-pp output.json samples --only-findings

Note

This also changes in the result displayed, the number of files scanned.

For example, scanning the sample files (distributed by default with scancode-toolkit) without this option, displays in it’s report information of 43 files. But after enabling this option, the result shows information for only 31 files.

Pre-Scan Options
All “Pre-Scan” Options
--ignore <pattern>

Ignore files matching <pattern>.

--include <pattern>

Include files matching <pattern>.

--classify

Classify files with flags telling if the file is a legal, or readme or test file, etc.

Sub-Options:

  • --license-clarity-score

  • --summary-key-files

--facet <facet_pattern>

Here <facet_pattern> represents <facet>=<pattern>. Add the <facet> to files with a path matching <pattern>.

Sub-Options:

  • --summary-by-facet


Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.


--ignore Option

In a scan, all files inside the directory specified as an input argument is scanned. But if there are some files which you don’t want to scan, the --ignore option can be used to do the same.

A sample usage:

scancode --ignore "*.java" samples samples.json

Here, Scancode ignores files ending with .java, and continues with other files as usual.

More information on Glob Pattern Matching.


--include Option

In a normal scan, all files inside the directory specified as an input argument is scanned. But if you want to run the scan on only some selective files, then --include option can be used to do the same.

A sample usage:

scancode --include "*.java" samples samples.json

Here, Scancode selectively scans files that has names ending with .java, and ignores all other files. This is basically complementary in behavior to the --ignore option.

More information on Glob Pattern Matching.


--classify

Sub-Option

The options --license-clarity-score and --summary-key-files are sub-options of --classify. --license-clarity-score and --summary-key-files are Post-Scan Options.

The --classify option can be used like:

scancode -clpieu --json-pp sample_facet.json samples --classify

This option makes ScanCode further classify scanned files/directories, to determine whether they fall in these following categories

  • legal

  • readme

  • top-level

  • manifest

    A manifest file in computing is a file containing metadata for a group of accompanying files that are part of a set or coherent unit.

  • key-file

    A KEY file is a generic file extension used by various programs when registering legal copies of the software. It may be saved in a plain text format, but generally contains some form of encrypted key string that authenticates the purchase and registers the software.

As in, to the JSON object of each file scanned, these extra attributes are added:

"is_legal": false,
"is_manifest": false,
"is_readme": true,
"is_top_level": true,
"is_key_file": true,

--facet Option

Sub-Option

The option --summary-by-facet is a sub-option of --facet. --summary-by-facet is a Post-Scan Option.

Valid <facet> values are:

  • core,

  • dev,

  • tests,

  • docs,

  • data,

  • examples.

You can use the --facet option in the following manner:

scancode -clpieu --json-pp sample_facet.json samples --facet dev="*.java" --facet dev="*.c"

This adds to the header object, the following attribute:

"--facet": [
  "dev=*.java",
  "dev=*.c"
],

Here in this example, .java and .c files are marked as it belongs to facet dev.

As a result, .java file has the following attribute added:

"facets": [
  "dev"
],

Note

All other files which are not dev are marked to be included in the facet core.

For each facet, the --facet option precedes the <facet>=<pattern> argument. For specifying multiple facets, this whole part is repeated, including the --facet option.

For users who want to know What is a Facet?.


Glob Pattern Matching

All the Pre-Scan options use pattern matching, so the basics of Glob Pattern Matching is discussed briefly below.

Glob pattern matching is useful for matching a group of files, by using patterns in their names. Then using these patterns, files are grouped and treated differently as required.

Here are some rules from the Linux Manual on glob patterns. Refer the same for more detailed information.

A string is a wildcard pattern if it contains one of the characters ‘?’, ‘*’ or ‘[‘. Globbing is the operation that expands a wildcard pattern into the list of pathnames matching the pattern. Matching is defined by:

  • A ‘?’ (not between brackets) matches any single character.

  • A ‘*’ (not between brackets) matches any string, including the empty string.

  • An expression “[…]” where the first character after the leading ‘[‘ is not an ‘!’ matches a single character, namely any of the characters enclosed by the brackets.

  • There is one special convention: two characters separated by ‘-‘ denote a range.

  • An expression “[!…]” matches a single character, namely any character that is not matched by the expression obtained by removing the first ‘!’ from it.

  • A ‘/’ in a pathname cannot be matched by a ‘?’ or ‘*’ wildcard, or by a range like “[.-0]”.

Note that wildcard patterns are not regular expressions, although they are a bit similar.

For more information on Glob pattern matching refer these resources:

You can also import these Python Libraries to practice UNIX style pattern matching:

  • fnmatch for File Name matching

  • glob for File Path matching


What is a Facet?

A facet is defined as follows (by ClearlyDefined):

A facet of a component is a subset of the files related to the component. It’s really just a grouping that helps us understand the shape of the project. Each facet is described by a set of glob expressions, essentially wildcard patterns that are matched against file names.

Each facet definition can have zero or more glob expressions. A file can be captured by more than one facet. Any file found but not captured by a defined facet is automatically assigned to the core facet.

  • core - The files that go into making the release of the component. Note that the core facet is not explicitly defined. Rather, it is made up of whatever is not in any other facet. So, by default, all files are in the core facet unless otherwise specified.

  • data - The files included in any data distribution of the component.

  • dev - Files primarily used at development time (e.g., build utilities) and not distributed with the component

  • docs - Documentation files. Docs may be included with the executable component or separately or not at all.

  • examples – Like docs, examples may be included in the main component release or separately.

  • tests – Test files may include code, data and other artifacts.

Important Links:

Post-Scan Options

Post-Scan options activate their respective post-scan plugins which execute the task.

All “Post-Scan” Options
--mark-source

Set the “is_source” flag to true for directories that contain over 90% of source files as direct children and descendants. Count the number of source files in a directory as a new “source_file_counts” attribute

Sub-Option of - --url

--consolidate

Group resources by Packages or license and copyright holder and return those groupings as a list of consolidated packages and a list of consolidated components.

Sub-Option of - --copyright, --license and --packages.

--filter-clues

Filter redundant duplicated clues already contained in detected licenses, copyright texts and notices.

--is-license-text

Set the “is_license_text” flag to true for files that contain mostly license texts and notices (e.g. over 90% of the content).

Sub-Option of - --info and --license-text.

Warning

--is-license-text is an experimental Option.

--license-clarity-score

Compute a summary license clarity score at the codebase level.

Sub-Option of - --classify.

--license-policy FILE

Load a License Policy file and apply it to the scan at the Resource level.

--summary

Summarize license, copyright and other scans at the codebase level.

Sub-Options:

  • --summary-by-facet

  • --summary-key-files

  • --summary-with-details

--summary-by-facet

Summarize license, copyright and other scans and group the results by facet.

Sub-Option of - --summary and --facet.

--summary-key-files

Summarize license, copyright and other scans for key, top-level files. Key files are top- level codebase files such as COPYING, README and package manifests as reported by the --classify option “is_legal”, “is_readme”, “is_manifest” and “is_top_level” flags.

Sub-Option of - --classify and --summary.

--summary-with-details

Summarize license, copyright and other scans at the codebase level, keeping intermediate details at the file and directory level.


Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.

To see all plugins available via command line help, use --plugins.

Note

Plugins that are shown by using --plugins inlcude the following:

  1. Post-Scan Plugins (and, the following)

  2. Pre-Scan Plugins

  3. Output Options

  4. Output Control

  5. Basic Scan Options


--mark-source Option

Dependency

The option --mark-source is a sub-option of and requires the option --info.

The mark-source option marks the “is_source” attribute of a directory to be “True”, if more than 90% of the files under that directory is source files, i.e. Their “is_source” attribute is “True”.

When the following command is executed to scan the samples directory with this option enabled:

scancode -clpieu --json-pp output.json samples --mark-source

Then, the following directories are marked as “Source”, i.e. Their “is_source” attribute is changed from “false” to “True”.

  • samples/JGroups/src

  • samples/zlib/iostream2

  • samples/zlib/gcc_gvmat64

  • samples/zlib/ada

  • samples/zlib/infback9


--consolidate Option

Dependency

The option --consolidate is a sub-option of and requires the options --license , --copyright and --package.

The JSON file containing scan results after using the --consolidate Plugin is structured as follows: (note: “…” in the image contains more data)

An example Scan:

scancode -clpieu --json-pp output.json samples --consolidate

The JSON output file is structured as follows:

{
  "headers": [
    {...}
  ],
  "consolidated_components": [
    {...
    },
    {
      "type": "license-holders",
      "identifier": "dmitriy_anisimkov_1",
      "consolidated_license_expression": "gpl-2.0-plus WITH ada-linking-exception",
      "consolidated_holders": [
        "Dmitriy Anisimkov"
      ],
      "consolidated_copyright": "Copyright (c) Dmitriy Anisimkov",
      "core_license_expression": "gpl-2.0-plus WITH ada-linking-exception",
      "core_holders": [
        "Dmitriy Anisimkov"
      ],
      "other_license_expression": null,
      "other_holders": [],
      "files_count": 1
    },
    {...
    }
  ],
  "consolidated_packages": [],
  "files": [
  ]
}

Each consolidated component has the following information:

"consolidated_components": [
{
  "type": "license-holders",
  "identifier": "dmitriy_anisimkov_1",
  "consolidated_license_expression": "gpl-2.0-plus WITH ada-linking-exception",
  "consolidated_holders": [
    "Dmitriy Anisimkov"
  ],
  "consolidated_copyright": "Copyright (c) Dmitriy Anisimkov",
  "core_license_expression": "gpl-2.0-plus WITH ada-linking-exception",
  "core_holders": [
    "Dmitriy Anisimkov"
  ],
  "other_license_expression": null,
  "other_holders": [],
  "files_count": 1
},

In addition to this, in every file/directory where the consolidated part (i.e. License information) was present, a “consolidated_to” attribute is added pointing to the “identifier” of “consolidated_components”:

"consolidated_to": [
         "dmitriy_anisimkov_1"
         ],

Note that multiple files may have the same “consolidated_to” attribute.


--filter-clues Option

The --filter-clues Plugin filters redundant duplicated clues already contained in detected licenses, copyright texts and notices.

Warning

Running the following scan generates an error:

./scancode -clp --json-pp sample_filter_clues.json samples --filter-clues

--is-license-text Option

Dependency

The option --is-license-text is a sub-option of and requires the options --info and --license-text. Also, the option --license-text is a sub-option of and requires the options --license.

If the --is-license-text is used, then the “is_license_text” flag is set to true for files that contain mostly license texts and notices. Here mostly means over 90% of the content of the file.

An example Scan:

scancode -clpieu --json-pp output.json samples --license-text --is-license-text

If the samples directory is scanned with this plugin, the files containing mostly license texts will have the following attribute set to ‘true’:

"is_license_text": true,

The files in samples that will have the “is_license_text” to be true are:

samples/JGroups/EULA
samples/JGroups/LICENSE
samples/JGroups/licenses/apache-1.1.txt
samples/JGroups/licenses/apache-2.0.txt
samples/JGroups/licenses/bouncycastle.txt
samples/JGroups/licenses/cpl-1.0.txt
samples/JGroups/licenses/lgpl.txt
samples/zlib/dotzlib/LICENSE_1_0.txt

Note that the license objects for each detected license in the files already has “is_license_text” attributes by default, but not the file objects. They only have this attribute if the plugin is used.

Warning

--is-license-text is an experimental Option.


--license-clarity-score Option

Dependency

The option --license-clarity-score is a sub-option of and requires the option --classify.

The --license-clarity-score plugin when used in a scan, computes a summary license clarity score at the codebase level.

An example Scan:

scancode -clpieu --json-pp output.json samples --classify --license-clarity-score

The “license_clarity_score” will have the following attributes:

  • “score”

  • “declared”

  • “discovered”

  • “consistency”

  • “spdx”

  • “license_texts”

It whole JSON file is structured as follows, when it has “license_clarity_score”:

{
  "headers": [
    { ...
    }
  ],
  "license_clarity_score": {
    "score": 17,
    "declared": false,
    "discovered": 0.69,
    "consistency": false,
    "spdx": false,
    "license_texts": false
  },
  "files": [
  ...
  ]
}

--license-policy FILE Option

The Policy file is a YAML (.yml) document with the following structure:

license_policies:
-   license_key: mit
    label: Approved License
    color_code: '#00800'
    icon: icon-ok-circle
-   license_key: agpl-3.0
    label: Approved License
    color_code: '#008000'
    icon: icon-ok-circle

Note

In the policy file only the “license_key” is a required field.

Applying License Policies during a ScanCode scan, using the --license-policy Plugin:

scancode -clipeu --json-pp output.json samples --license-policy policy-file.yml

Note

--license-policy FILE is a not a sub-option of --license. It works normally without -l.

This adds to every file/directory an object “license_policy”, having as further attributes under it the fields as specified in the .YAML file. Here according to our example .YAML file, the attributes will be:

  • “license_key”

  • “label”

  • “color_code”

  • “icon”

Here the samples directory is scanned, and the Scan Results for a sample file is as follows:

{
  "path": "samples/JGroups/licenses/apache-2.0.txt",
  ...
  ...
  ...
  "licenses": [
  ...
  ...
  ...
  ],
  "license_expressions": [
    "apache-2.0"
  ],
  "copyrights": [],
  "holders": [],
  "authors": [],
  "packages": [],
  "emails": [],
  "license_policy": {
    "license_key": "apache-2.0",
    "label": "Approved License",
    "color_code": "#008000",
    "icon": "icon-ok-circle"
  },
  "urls": [],
  "files_count": 0,
  "dirs_count": 0,
  "size_count": 0,
  "scan_errors": []
},

More information on the License Policy Plugin and usage.


--summary Option

Sub-Option

The option --summary-by-facet, --summary-key-files and --summary-with-details``are sub-options of ``--summary. These Sub-Options are all Post-Scan Options.

An example Scan:

scancode -clpieu --json-pp output.json samples --summary

The whole JSON file is structured as follows, when the --summary plugin is applied:

{
  "headers": [
    {
    ...
    }
  ],
  "summary": {
    "license_expressions": [ ...
    ],
    "copyrights": [ ...
    ],
    "holders": [ ...
    ],
    "authors": [ ...
    ],
    "programming_language": [ ...
    ],
    "packages": []
  },
  "files": [ ...
  ]
}

The Summary object has the following attributes.

  • “license_expressions”

  • “copyrights”

  • “holders”

  • “authors”

  • “programming_language”

  • “packages”

Each attribute has multiple entries each containing “value” and “count”, with their values having the summary information inside them.

A sample summary object generated:

"summary": {
"license_expressions": [
  {
    "value": "zlib",
    "count": 13
  },
]
],
"copyrights": [
  {
    "value": "Copyright (c) Mark Adler",
    "count": 4
  },
  {
    "value": "Copyright (c) Free Software Foundation, Inc.",
    "count": 2
  },
  {
    "value": "Copyright (c) The Apache Software Foundation",
    "count": 1
  },
  {
    "value": "Copyright Red Hat, Inc. and individual contributors",
    "count": 1
  }
],
"holders": [
  {
    "value": null,
    "count": 10
  },
  {
    "value": "Mark Adler",
    "count": 4
  },
  {
    "value": "Red Hat, Inc. and individual contributors",
    "count": 1
  },
  {
    "value": "The Apache Software Foundation",
    "count": 1
  },
],
"authors": [
  {
    "value": "Bela Ban",
    "count": 4
  },
  {
    "value": "Brian Stansberry",
    "count": 1
  },
  {
    "value": "the Apache Software Foundation (http://www.apache.org/)",
    "count": 1
  }
],
"programming_language": [
  {
    "value": "C++",
    "count": 13
  },
  {
    "value": "Java",
    "count": 7
  },
],
"packages": []

--summary-by-facet Option

Dependency

The option --summary-by-facet is a sub-option of and requires the options --facet and --summary.

Running the scan with --summary --summary-by-facet Plugins creates individual summaries for all the facets with the same license, copyright and other scan information, at a codebase level (in addition to the codebase level general summary generated by --summary Plugin)

An example scan using the --summary-by-facet Plugin:

scancode -clieu --json-pp output.json samples --summary --facet dev="*.java" --facet dev="*.c" --summary-by-facet

Note

All other files which are not dev are marked to be included in the facet core.

Warning

Running the same scan with ./scancode -clpieu i.e. with -p generates an error. Avoid this.

The JSON file containing scan results is structured as follows:

{
  "headers": [ ...
  ],
  "summary": { ...
  },
  "summary_by_facet": [
    {
      "facet": "core",
      "summary": { ...
      }
    },
    {
      "facet": "dev",
      "summary": { ...
      }
    },
    {
      "facet": "tests",
      "summary": { ...
      }
    },
    {
      "facet": "docs",
      "summary": { ...
      }
    },
    {
      "facet": "data",
      "summary": { ...
      }
    },
    {
      "facet": "examples",
      "summary": { ...
      }
    }
  ],
  "files": [
}

A sample “summary_by_facet” object generated by the previous scan (shortened):

"summary_by_facet": [
  {
    "facet": "core",
    "summary": {
      "license_expressions": [
        {
          "value": "mit",
          "count": 1
        },
      ],
      "copyrights": [
        {
          "value": "Copyright (c) Free Software Foundation, Inc.",
          "count": 2
        },
      ],
      "holders": [
        {
          "value": "The Apache Software Foundation",
          "count": 1
        },
      "authors": [
        {
          "value": "Gilles Vollant",
          "count": 1
        },
      ],
      "programming_language": [
        {
          "value": "C++",
          "count": 8
        },
      ]
    }
  },
  {
    "facet": "dev",
    "summary": {
      "license_expressions": [
        {
          "value": "zlib",
          "count": 5
        },
      "copyrights": [
        {
          "value": "Copyright Red Hat Middleware LLC, and individual contributors",
          "count": 1
        },
      ],
      "holders": [
        {
          "value": "Mark Adler",
          "count": 3
        },
      ],
      "authors": [
          "value": "Brian Stansberry",
          "count": 1
        },
      ],
      "programming_language": [
        {
          "value": "Java",
          "count": 7
        },
        {
          "value": "C++",
          "count": 5
        }
      ]
    }
  },
],

Note

Summaries for all the facets are generated by default, regardless of facets not having any files under them.

For users who want to know What is a Facet?.


--summary-key-files Option

Dependency

The option --summary-key-files is a sub-option of and requires the options --classify and --summary.

An example Scan:

scancode -clpieu --json-pp output.json samples --classify --summary --summary-key-files

Running the scan with --summary --summary-key-files Plugins creates summaries for key files with the same license, copyright and other scan information, at a codebase level (in addition to the codebase level general summary generated by --summary Plugin)

The resulting JSON file containing the scan results is structured as follows:

{
  "headers": [ ...
  ],
  "summary": {
    "license_expressions": [ ...
    ],
    "copyrights": [ ...
    ],
    "holders": [ ...
    ],
    "authors": [ ...
    ],
    "programming_language": [ ...
    ],
    "packages": []
  },
  "summary_of_key_files": {
    "license_expressions": [
      {
        "value": null,
        "count": 1
      }
    ],
    "copyrights": [
      {
        "value": null,
        "count": 1
      }
    ],
    "holders": [
      {
        "value": null,
        "count": 1
      }
    ],
    "authors": [
      {
        "value": null,
        "count": 1
      }
    ],
    "programming_language": [
      {
        "value": null,
        "count": 1
      }
    ]
  },
  "files": [

These following flags for each file/directory is also present (generated by --classify)

  • “is_legal”

  • “is_manifest”

  • “is_readme”

  • “is_top_level”

  • “is_key_file”


--summary-with-details Option

The --summary plugin summarizes license, copyright and other scan information at the codebase level. Now running the scan with the --summary-with-details plugin instead creates summaries at individual file/directories with the same license, copyright and other scan information, but at a file/directory level (in addition to the the codebase level summary).

An example Scan:

scancode -clpieu --json-pp output.json samples --summary-with-details

Note

--summary is redundant in a scan when --summary-with-details is already selected.

A sample file object in the scan results (a directory level summary of samples/arch) is structured as follows:

{
  "path": "samples/arch",
  "type": "directory",
  "name": "arch",
  "base_name": "arch",
  "extension": "",
  "size": 0,
  "date": null,
  "sha1": null,
  "md5": null,
  "mime_type": null,
  "file_type": null,
  "programming_language": null,
  "is_binary": false,
  "is_text": false,
  "is_archive": false,
  "is_media": false,
  "is_source": false,
  "is_script": false,
  "licenses": [],
  "license_expressions": [],
  "copyrights": [],
  "holders": [],
  "authors": [],
  "packages": [],
  "emails": [],
  "urls": [],
  "is_legal": false,
  "is_manifest": false,
  "is_readme": false,
  "is_top_level": true,
  "is_key_file": false,
  "summary": {
    "license_expressions": [
      {
        "value": "zlib",
        "count": 3
      },
      {
        "value": null,
        "count": 1
      }
    ],
    "copyrights": [
      {
        "value": null,
        "count": 1
      },
      {
        "value": "Copyright (c) Jean-loup Gailly",
        "count": 1
      },
      {
        "value": "Copyright (c) Jean-loup Gailly and Mark Adler",
        "count": 1
      },
      {
        "value": "Copyright (c) Mark Adler",
        "count": 1
      }
    ],
    "holders": [
      {
        "value": null,
        "count": 1
      },
      {
        "value": "Jean-loup Gailly",
        "count": 1
      },
      {
        "value": "Jean-loup Gailly and Mark Adler",
        "count": 1
      },
      {
        "value": "Mark Adler",
        "count": 1
      }
    ],
    "authors": [
      {
        "value": null,
        "count": 4
      }
    ],
    "programming_language": [
      {
        "value": "C++",
        "count": 3
      },
      {
        "value": null,
        "count": 1
      }
    ]
  },
  "files_count": 4,
  "dirs_count": 2,
  "size_count": 127720,
  "scan_errors": []
},

These following flags for each file/directory is also present (generated by --classify)

  • “is_legal”

  • “is_manifest”

  • “is_readme”

  • “is_top_level”

  • “is_key_file”

Plugins

Plugin Architecture

Notes: this is the initial design for ScanCode plugins. The actual architecture evolved and is different.

Abstract:

This project’s purpose is to create a decoupled plugin architecture for scancode such that it can handle plugins at different stages of a scan and can be coupled at runtime. These stages would be

  • Pre - scan: Before starting the scan

E.g Plugins to handle extraction of different archive types or instructions on how to handle certain types of files.

  • Scan proper: During the scan

E.g Plugins to add more options for the scan, maybe to ignore certain files or add some command line arguments, create new scans (alternative or as a dependency for further scanning) etc.

  • Post - scan: After the scan

E.g Plugins for output deduction, formatting or converting output to other formats (such as json, spdx, csv, xml, etc.)

Upside of building a pluggable system would be to allow easier additions and rare modifications to code, without having to really fiddle around with core codebase. This will also provide a level of abstraction between the plugins and scancode so that any erroneous plugin would not affect the functioning of scancode as a whole.

Description:

This project aims at making scancode a “pluggable” system, where new functionalities can be added to scancode at runtime as “plugins”. These plugins can be hooked into scancode using some predefined hooks. I would consider pluggy as the way to go for a plugin management system.

Why pluggy?

Pluggy is well documented and maintained regularly, and has proved its worth in projects such as py.test. Pluggy relies on hook specifications and hook implementations (callbacks) instead of the conventional subclassing approach which may encourage tight-coupling in the overlying framework. Basically a hook specification contains method signatures (no code), these are defined by the application. A hook implementation contains definitions for methods declared in the corresponding hook specification implemented by a plugin.

As mentioned in the abstract, the plugin architecture will have 3 hook specifications (can be increased if required)

1. Pre - scan hook
  • Structure -

prescan_hookspec = HookspecMarker('prescan')

@prescan_hookspec
def extract_archive(args):

Here the path of the archive to be extracted will be passed as an argument to the extract_archive function which will be called before scan, at the time of extraction. This will process the archive type and extract the contents accordingly. This functionality can be further extended by calling this function if any archive is found inside the scanning tree.

2. Scan proper hook
  • Structure

scanproper_hookspec = HookspecMarker('scanproper')

@scanproper_hookspec
def add_cmdline_option(args):

This function will be called before starting the scan, without any arguments, it will return a dict containing the click extension details and possibly some help text. If this option is called by the user then the call will be rerouted to the callback defined by the click extension. For instance say a plugin implements functionality to add regex as a valid ignore pattern, then this function will return a dict as:

{
    'name': '--ignore-regex',
    'options' : {
        'default': None,
        'multiple': True,
        'metavar': <pattern>
    },
    'help': 'Ignore files matching regex <pattern>'
    'call_after': 'is_ignored'
}

According to the above dict, if the option –ignore-regex is supplied, this function will be called after the is_ignored function and the data returned by the is_ignored function will be supplied to this function as its argument(s). So if the program flow was:

scancode() ⇔ scan() ⇔ resource_paths() ⇔ is_ignored()

It will now be edited to

scancode() ⇔ scan() ⇔ resource_paths() ⇔ is_ignored() ⇔ add_cmdline_option()

Options such as call_after, call_before, call_first, call_last can be defined to determine when the function is to be executed.

@scanproper_hookspec
def dependency_scan(args):

This function will be called before starting the scan without any arguments, it will return a list of file types or attributes which if encountered in the scanned tree, will call this function with the path to the file as an argument. This function can do some extra processing on those files and return the data to be processed as a dependency for the normal scanning process. E.g. It can return a list such as:

[ 'debian/copyright' ]

Whenever a file matches this pattern, this function will be called and the data returned will be supplied to the main scancode function.

3. Post - scan hook
  • Structure -

postscan_hookspec = HookspecMarker('postscan')

@postscan_hookspec
def format_output(args):

This function will be called after a scan is finished. It will be supplied with path to the ABC data generated from the scan, path to the root of the scanned code and a path where the output is expected to be stored. The function will store the processed data in the output path supplied. This can be used to convert output to other formats such as CSV, SPDX, JSON, etc.

@postscan_hookspec
def summarize_output(args):

This function will be called after a scan is finished. It will be supplied the data to be reported to the user as well as a path to the root of the scanned node. The data returned can then be reported to the user. This can be used to summarize output, maybe encapsulate the data to be reported or omit similar file metadata or even classify files such as tests, code proper, licenses, readme, configs, build scripts etc.

  • Identifying or configuring plugins

For python plugins, pluggy supports loading modules from setuptools entrypoints, E.g.

entry_points = {
    'scancode_plugins': [
        'name_of_plugin = ignore_regex',
    ]
}

This plugin can be loaded using the PluginManager class’s load_setuptools_entrypoints(‘scancode_plugins’) method which will return a list of loaded plugins.

For non python plugins, all such plugins will be stored in a common directory and each of these plugins will have a manifest configuration in YAML format. This directory will be scanned at startup for plugins. After parsing the config file of a plugin, the data will be supplied to the plugin manager as if it were supplied using setuptools entrypoints.

In case of non python plugins, the plugin executables will be spawned in their own processes and according to their config data, they will be passed arguments and would return data as necessary. In addition to this, the desired hook function can be called from a non python plugin using certain arguments, which again can be mapped in the config file.

Sample config file for a ignore_regex plugin calling scanproper hook would be:

name: ignore_regex
hook: scanproper
hookfunctions:
  add_cmdline_option: '-aco'
  dependency_scan: '-dc'
data:
  add_cmdline_option':
    - name: '--ignore-regex'
    - options:
        - default: None
        - multiple: True
        - metavar: <pattern>
    - help: 'Ignore files matching regex <pattern>'
    - call_after: 'is_ignored'
Existing solutions:

An alternate solution to a “pluggable” system would be the more conventional approach of adding functionalities directly to the core codebase, which removes the abstraction layer provided by a plugin management and hook calling system.

License Policy Plugin

This plugin allows the user to apply policy details to a scancode scan, depending on which licenses are detected in a particular file. If a license specified in the Policy file is detected by scancode, this plugin will apply that policy information to the Resource as a new attribute: license_policy.

Policy File Specification

The Policy file is a YAML (.yml) document with the following structure:

license_policies:
-   license_key: mit
    label: Approved License
    color_code: '#00800'
    icon: icon-ok-circle
-   license_key: agpl-3.0
    label: Approved License
    color_code: '#008000'
    icon: icon-ok-circle
-   license_key: broadcom-commercial
    label: Restricted License
    color_code: '#FFcc33'
    icon: icon-warning-sign

The only required key is license_key, which represents the ScanCode license key to match against the detected licenses in the scan results.

In the above example, a descriptive label is added along with a color code and CSS id name for potential visual display.

Using the Plugin

To apply License Policies during a ScanCode scan, specify the --license-policy option.

For example, use the following command to run a File Info and License scan on /path/to/codebase/, using a License Policy file found at ~/path/to/policy-file.yml:

$ scancode -clipeu /path/to/codebase/ --license-policy ~/path/to/policy-file.yml --json-pp
  ~/path/to/scan-output.json
Example Output

Here is an example of the ScanCode output after running --license-policy:

{
 "path": "samples/zlib/deflate.c",
 "type": "file",
 "licenses": [
   {
     "key": "zlib",
     ...
     ...
     ...
   }
 ],
 "license_policy": {
   "license_key": "zlib",
   "label": "Approved License",
   "color_code": "#00800",
   "icon": "icon-ok-circle"
 },
 "scan_errors": []
 }
Plugin Tutorials

Basic Tutorials

How to Run a Scan

In this simple tutorial example, we perform a basic scan on the samples directory distributed by default with Scancode.

Prerequisites

Refer Prerequisites to make sure the correct Python Interpreters and other prerequisites are satisfied.

Setting up a Virtual Environment

ScanCode Toolkit supports Python 3 in 3.2.x and later versions, so if you are using 3.2.x or later versions, you should create a virtual environment using the Virtualenv tool with a python 3.6 interpreter.

The following commands set up and activate the Virtual Environment venv-scancode-py3:

virtualenv -p /usr/bin/python3.6 venv-scancode-py3
source venv-scancode-py3/bin/activate

If you are using Scancode Toolkit 3.1.0 and earlier versions, they are not compatible with Python 3.x so you should create the virtual environment with a python 2.7 interpreter:

virtualenv -p /usr/bin/python2.7 venv-scancode-py2
source venv-scancode-py2/bin/activate
Setting up Scancode Toolkit

Get ScanCode Toolkit from pip:

pip install scancode-toolkit

Note

You can install a specific version of Scancode Toolkit like scancode-toolkit==3.1.1.

Looking into Files

As mentioned previously, we are going to perform the scan on the samples directory distributed by default with Scancode Toolkit. Here’s the directory structure and respective files:

_images/files_sample.png

We notice here that the sample files contain a package zlib.tar.gz. So we have to extract the archive before running the scan, to also scan the files inside this package.

Performing Extraction

To extract the packages inside samples directory:

extractcode samples

This extracts the zlib.tar.gz package:

_images/extractcode.png

Note

--shallow option can be used to recursively extract packages.

Deciding Scan Options

These are some common scan options you should consider using before you start the actual scan, according to your requirements.

  1. The Basic Scan options, i.e. -c, -l, -p, -e, -u, and -i are to be decided, according to your requirements. If you do not need one specific type of information (say, licenses), consider removing it, because the more things you scan for, longer it will take for the scan to complete.

Note

You have to select these options explicitly, as they are not default anymore from versions 3.x, unlike earlier versions having -clp as default.

  1. --license-score INTEGER is to be set if license matching accuracy is desired (Default is 0, and increasing this means a more accurate match). Also, using --license-text includes the matched text to the result.

  2. -n INTEGER option can be used to speed up the scan using multiple parallel processes.

  3. --timeout FLOAT option can be used to skip a file taking a lot of time to scan.

  4. --ignore <pattern> can be used to skip certain group of files.

  5. <OUTPUT FORMAT OPTION(s)> is also a very important decision when you want to use the output for specific tasks/have requirements. Here we are using json as ScanCode Workbench imports json files only.

For the complete list of options, refer All Available Options.

Running The Scan

Now, run the scan with the options decided:

scancode -clpeui -n 2 --ignore "*.java" --json-pp sample.json samples

A Progress report is shown:

Setup plugins...
Collect file inventory...
Scan files for: info, licenses, copyrights, packages, emails, urls with 2 process(es)...
[####################] 29
Scanning done.
Summary:        info, licenses, copyrights, packages, emails, urls with 2 process(es)
Errors count:   0
Scan Speed:     1.09 files/sec. 40.67 KB/sec.
Initial counts: 49 resource(s): 36 file(s) and 13 directorie(s)
Final counts:   42 resource(s): 29 file(s) and 13 directorie(s) for 1.06 MB
Timings:
  scan_start: 2019-09-24T203514.573671
  scan_end:   2019-09-24T203545.649805
  setup_scan:licenses: 4.30s
  setup: 4.30s
  scan: 26.62s
  total: 31.14s
Removing temporary files...done.
How to Visualize Scan results

In this simple tutorial example, we import results from a basic scan performed on the samples directory distributed by default with Scancode, and visualize the outputs through Scancode Workbench.

Warning

This tutorial uses the 3.1.1 version of Scancode Toolkit, and Scancode Workbench 3.1.0 (This beta version of ScanCode Workbench is compatible with scans from any ScanCode Toolkit develop version/branch at or after v3.0.2). If you are using an older version of Scancode Toolkit, check respective versions of this documentation. Also refer the Scancode Workbench release highlights.

Warning

This tutorial is for Linux based systems presently. Additional Help for Windows/MacOS will be added.

Setting up Scancode Workbench

According to the Install Building Requirements, we have to install Node.js 6.x or later. Refer to Node.js install instructions here.

You can also run the following commands:

sudo apt-get install -y nodejs
sudo npm install npm@5.2.0 -g

After Node.js and npm is installed and get the Scancode Workbench 3.1.0 tarball from the Workbench Release Page. Extract the package and then launch Scancode Workbench:

./ScanCode-Workbench

This opens the Workbench.

Note

You can also build Scancode Toolkit and Scancode Workbench from source. Clone the repository, don’t forget to checkout to the specific release using git checkout <release>, and follow the build instructions. You’ll also have to create a Python 2.7 Virtual Environment, or use the same venv-3.1.1 created here at How to Run a Scan.

Importing Data into Scancode Workbench
  1. Click on the File -> Import JSON File or Press Ctrl + I.

  2. Select the file from the pop-up window.

  3. Select a Name and Location (where you want it later) for the .sqlite output file.

Note

You can also import a .sqlite file you’ve saved in the past to load scan results. As it is much faster, once you’ve imported the JSON file and a corresponding SQLite file has been created, you shouldn’t repeat this. Instead, import the SQLite file next time you want to visualize the same scan result.

Visualization
Views

Refer Scancode Workbench Views for more information on Visualization.

The dashboard has a general overview.

_images/workbench_dashboard.png

There are 3 principal views (They appear in the same order in the GIFs):

  • Chart Summary View,

  • Table View,

  • Components Summary View.

_images/views_sample.gif
Filters

You can also click any file/directory on the file list located on the right, to filter the results such that it only contains results from that File/Directory.

_images/filter_sample.gif
Components

Refer Creating Conclusions for more information on Components.

In the table view,

  1. Apply filters by selecting Files/Directories

  2. Right Click on the Left Panel

  3. Select Edit Component

  4. A pop-up opens with fields, make necessary edits and Save.

  5. Go to the Component Summary View to see the Component.

_images/components_sample.gif
How To Extract Archives

ScanCode Toolkit provides archive extraction. This command can be used before running a scan over a codebase in order to ensure all archives are extracted. Archives found inside an extracted archive are extracted recursively. Extraction is done in-place in a directory and named after the archive with '-extract' appended.

_images/scancode-toolkit-extract.png
Usage:
extractcode [OPTIONS] <input>
All Extractcode Options

This is intended to be used as an input preparation step, before running the scan. Archives found in an extracted archive are extracted recursively by default. Extraction is done in-place in a directory named ‘-extract’ side-by-side with an archive.

To extract the packages in the samples directory

extractcode samples

This extracts the zlib.tar.gz package:

_images/extractcode.png
--shallow

Do not extract recursively nested archives (e.g. Not archives in archives).

--verbose

Print verbose file-by-file progress messages.

--quiet

Do not print any summary or progress message.

-h, --help

Show the extractcode help message and exit.

--about

Show information about ScanCode and licensing and exit.

--version

Show the version and exit.

How to specify Scancode Output Format

A basic overview of formatting Scancode Output is presented here.

More information on Scancode Output Formats.

Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.

JSON

If you want JSON output of ScanCode results, you can pass the --json argument to ScanCode. The following commands will output scan results in a formatted json file:

  • scancode --json /path/to/output.json /path/to/target/dir

  • scancode --json-pp /path/to/output.json /path/to/target/dir

  • scancode --json-lines /path/to/output.json /path/to/target/dir

To compare the JSON output in different formats refer Comparing Different json Output Formats.

HTML

If you want HTML output of ScanCode results, you can pass the --html argument to ScanCode. The following commands will output scan results in a formatted HTML page or simple web application:

  • scancode --html /path/to/output.html /path/to/target/dir

  • scancode --html-app /path/to/output.html /path/to/target/dir

For more details on the HTML output format refer --html FILE.

Warning

The --html-app option has been deprecated, use Scancode Workbench instead.

Custom Output Format

While the three built-in output formats are convenient for a verity of use-cases, one may wish to create their own output template, using the following arguments:

``--custom-output FILE --custom-template TEMP_FILE``

ScanCode makes this very easy, as it uses the popular Jinja2 template engine. Simply pass the path to the custom template to the --custom-template argument, or drop it in a folder to src/scancode/templates directory.

For example, if I wanted a simple CLI output I would create a template2.html with the particular data I wish to see. In this case, I am only interested in the license and copyright data for this particular scan.

## template.html:
[
    {% if files.license_copyright %}
        {% for location, data in files.license_copyright.items() %}
            {% for row in data %}
  location:"{{ location }}",
  {% if row.what == 'copyright' %}copyright:"{{ row.value|escape }}",{% endif %}
             {% endfor %}
         {% endfor %}
    {% endif %}
]

.. note::

    File name and extension does not matter for the template file.

Now I can run ScanCode using my newly created template:

$ scancode -clpeui --custom-output output.json --custom-template template.html samples
Scanning files...
  [####################################]  46
Scanning done.

Now are results are saved in output.json and we can easily view them with head output.json:

[
  location:"samples/JGroups/LICENSE",
  copyright:"Copyright (c) 1991, 1999 Free Software Foundation, Inc.",

  location:"samples/JGroups/LICENSE",
  copyright:"copyrighted by the Free Software Foundation",
]

For a more elaborate template, refer this default template given with Scancode, to generate HTML output with the --html output format option.

Documentation on Jinja templates.

How to set what will be detected in Scan

ScanCode allows you to scan a codebase for license, copyright and other interesting information that can be discovered in files. The following options are available for detection when using ScanCode Toolkit:

All “Basic” Scan Options

Option lists are two-column lists of command-line options and descriptions, documenting a program’s options. For example:

-c, --copyright

Scan <input> for copyrights.

Sub-Options:

  • --consolidate

-l, --license

Scan <input> for licenses.

Sub-Options:

  • --consolidate

  • --license-score INT

  • --license-text

  • --license-url-template TEXT

  • --license-text-diagnostics

  • --is-license-text

-p, --package

Scan <input> for packages.

Sub-Options:

  • --consolidate

-e, --email

Scan <input> for emails.

Sub-Options:

  • --max-email INT

-u, --url

Scan <input> for urls.

Sub-Options:

  • --max-url INT

-i, --info

Include information such as:

  • Size,

  • Type,

  • Date,

  • Programming language,

  • sha1 and md5 hashes,

  • binary/text/archive/media/source/script flags

  • Additional options through more CLI options

Sub-Options:

  • --mark-source

Note

Unlike previous 2.x versions, -c, -l, and -p are not default. If any of combination of these options are used, ScanCode only performs that specific task, and not the others. scancode -e only scans for emails, and doesn’t scan for copyright/license/packages/general information.

Note

These options, i.e. -c, -l, -p, -e, -u, and -i can be used together. As in, instead of scancode -c -i -p, you can write scancode -cip and it will be the same.

--generated

Classify automatically generated code files with a flag.

--max-email INT

Report only up to INT emails found in a file. Use 0 for no limit. [Default: 50]

Sub-Option of - --email

--max-url INT

Report only up to INT urls found in a file. Use 0 for no limit. [Default: 50]

Sub-Option of - --url

--license-score INTEGER

Do not return license matches with scores lower than this score. A number between 0 and 100. [Default: 0] Here, a bigger number means a better match, i.e. Setting a higher license score translates to a higher threshold (with equal or less number of matches).

Sub-Option of - --license

--license-text

Include the matched text for the detected licenses in the output report.

Sub-Option of - --license

Sub-Options:

  • --license-text-diagnostics

  • --is-license-text

--license-url-template TEXT

Set the template URL used for the license reference URLs.

In a template URL, curly braces ({}) are replaced by the license key. [Default: https://enterprise.dejacode.com/urn/urn:dje:license:{}]

Sub-Option of - --license

--license-text-diagnostics

In the matched license text, include diagnostic highlights surrounding with square brackets [] words that are not matched.

Sub-Option of - --license and --license-text

Different Scans

The following examples will use the samples directory that is provided with the ScanCode Toolkit code. All examples will be saved in the JSON format, which can be loaded into Scancode Workbench for visualization. See How to Visualize Scan results for more information. Another output format option is a static html file. See Scancode Output Formats for more information.

Note

For more information on the Scan Command for Various Installation Methods/Operating Systems, refer Installation.

Scan for all clues:

To scan for licenses, copyrights, urls, emails, package information, and file information

scancode -clipeu --json output.json samples
Scan for emails and URLs:
scancode -eu --json-pp output.json samples
Scan for package information:
scancode -p --json-pp output.json samples
Scan for file information:
scancode -i --json-pp output.json samples
To see more example scans:
scancode --examples

For more information, refer All Available Options.

Add A Post-Scan Plugin
Built-In vs. Optional Installation
Built-In

Some post-scan plugins are installed when ScanCode itself is installed, e.g., the License Policy Plugin, whose code is located here:

https://github.com/nexB/scancode-toolkit/blob/develop/src/licensedcode/plugin_license_policy.py

These plugins do not require any additional installation steps and can be used as soon as ScanCode is up and running.

Optional

ScanCode is also designed to use post-scan plugins that must be installed separately from the installation of ScanCode. The code for this sort of plugin is located here:

https://github.com/nexB/scancode-toolkit/tree/develop/plugins/

This wiki page will focus on optional post-scan plugins.

Example Post-Scan Plugin: Hello ScanCode

To illustrate the creation of a simple post-scan plugin, we’ll create a hypothetical plugin named Hello ScanCode, which will print Hello ScanCode! in your terminal after you’ve run a scan. Your command will look like something like this:

scancode -i -n 2 <path to target codebase> --hello --json <path to JSON output file>

We’ll start by creating three folders:

  1. Top-level folder – /scancode-hello/

  2. 2nd-level folder – /src/

  3. 3rd-level folder – /hello_scancode/

1. Top-level folder – /scancode-hello/
  • In the /scancode-toolkit/plugins/ directory, add a folder with a relevant name, e.g., scancode-hello. This folder will hold all of your plugin code.

  • Inside the /scancode-hello/ folder you’ll need to add a folder named src and 7 files.

  1. /src/ – This folder will contain your primary Python code and is discussed in more detail in the following section.

The 7 Files are:

  1. .gitignore – See, e.g., /plugins/scancode-ignore-binaries/.gitignore

/build/
/dist/
  1. apache-2.0.LICENSE – See, e.g., /plugins/scancode-ignore-binaries/apache-2.0.LICENSE

  2. MANIFEST.in

graft src

include setup.py
include setup.cfg
include .gitignore
include README.md
include MANIFEST.in
include NOTICE
include apache-2.0.LICENSE

global-exclude *.py[co] __pycache__ *.*~
  1. NOTICE – See, e.g., /plugins/scancode-ignore-binaries/NOTICE

  2. README.md

  3. setup.cfg

[metadata]
license_file = NOTICE

[bdist_wheel]
universal = 1

[aliases]
release = clean --all  bdist_wheel
  1. setup.py – This is an example of what our setup.py file would look like:

#!/usr/bin/env python
# -*- encoding: utf-8 -*-

from __future__ import absolute_import
from __future__ import print_function

from glob import glob
from os.path import basename
from os.path import join
from os.path import splitext

from setuptools import find_packages
from setuptools import setup


desc = '''A ScanCode post-scan plugin to to illustrate the creation of a simple post-scan plugin.'''

setup(
    name='scancode-hello',
    version='1.0.0',
    license='Apache-2.0 with ScanCode acknowledgment',
    description=desc,
    long_description=desc,
    author='nexB',
    author_email='info@aboutcode.org',
    url='https://github.com/nexB/scancode-toolkit/plugins/scancode-categories',
    packages=find_packages('src'),
    package_dir={'': 'src'},
    py_modules=[splitext(basename(path))[0] for path in glob('src/*.py')],
    include_package_data=True,
    zip_safe=False,
    classifiers=[
        # complete classifier list: http://pypi.python.org/pypi?%3Aaction=list_classifiers
        'Development Status :: 4 - Beta',
        'Intended Audience :: Developers',
        'License :: OSI Approved :: Apache Software License',
        'Programming Language :: Python',
        'Programming Language :: Python :: 2.7',
        'Topic :: Utilities',
    ],
    keywords=[
        'scancode', 'plugin', 'post-scan'
    ],
    install_requires=[
        'scancode-toolkit',
    ],
    entry_points={
        'scancode_post_scan': [
            'hello = hello_scancode.hello_scancode:SayHello',
        ],
    }
)
2. 2nd-level folder – /src/
  1. Add an __init__.py file inside the src folder. This file can be empty, and is used to indicate that the folder should be treated as a Python package directory.

  2. Add a folder that will contain our primary code – we’ll name the folder hello_scancode. If you look at the example of the setup.py file above, you’ll see this line in the entry_points section:

'hello = hello_scancode.hello_scancode:SayHello',
  • hello refers to the name of the command flag.

  • The first hello_scancode is the name of the folder we just created.

  • The second hello_scancode is the name of the .py file containing our code (discussed in the next section).

  • SayHello is the name of the PostScanPlugin class we create in that file (see sample code below).

3. 3rd-level folder – /hello_scancode/
  1. Add an __init__.py file inside the hello_scancode folder. As noted above, this file can be empty.

  2. Add a hello_scancode.py file.

Notice at the top of the file
#
# Copyright (c) 2019 nexB Inc. and others. All rights reserved.
# http://nexb.com and https://github.com/nexB/scancode-toolkit/
# The ScanCode software is licensed under the Apache License version 2.0.
# Data generated with ScanCode require an acknowledgment.
# ScanCode is a trademark of nexB Inc.
#
# You may not use this software except in compliance with the License.
# You may obtain a copy of the License at: http://apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed
# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
# CONDITIONS OF ANY KIND, either express or implied. See the License for the
# specific language governing permissions and limitations under the License.
#
# When you publish or redistribute any data created with ScanCode or any ScanCode
# derivative work, you must accompany this data with the following acknowledgment:
#
#  Generated with ScanCode and provided on an "AS IS" BASIS, WITHOUT WARRANTIES
#  OR CONDITIONS OF ANY KIND, either express or implied. No content created from
#  ScanCode should be considered or used as legal advice. Consult an Attorney
#  for any legal advice.
#  ScanCode is a free software code scanning tool from nexB Inc. and others.
#  Visit https://github.com/nexB/scancode-toolkit/ for support and download.
Imports
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

from plugincode.post_scan import PostScanPlugin
from plugincode.post_scan import post_scan_impl
from scancode import CommandLineOption
from scancode import POST_SCAN_GROUP
Create a PostScanPlugin class

The PostScanPlugin class (see L40-L45 code) inherits from the CodebasePlugin class (see L139-L150 code ), which inherits from the BasePlugin class (see L38-L136 code ).

@post_scan_impl
class SayHello(PostScanPlugin):
    """
    Illustrate a simple "Hello World" post-scan plugin.
    """

    options = [
        CommandLineOption(('--hello',),
                                        is_flag=True, default=False,
                                        help='Generate a simple "Hello ScanCode" greeting in the terminal.',
                                        help_group=POST_SCAN_GROUP)
    ]

    def is_enabled(self, hello, **kwargs):
        return hello

    def process_codebase(self, codebase, hello, **kwargs):
        """
        Say hello.
        """
        if not self.is_enabled(hello):
            return

        print('\nHello ScanCode!!\n')
Load the plugin
  • To load and use the plugin in the normal course, navigate to the plugin’s root folder (in this example: /plugins/scancode-hello/) and run pip install . (don’t forget the final .).

  • If you’re developing and want to test your work, save your edits and run pip install -e . from the same folder.

More-complex examples

This Hello ScanCode example is quite simple. For examples of more-complex structures and functionalities you can take a look at the other post-scan plugins for guidance and ideas.

One good example is the License Policy post-scan plugin. This plugin is installed when ScanCode is installed and consequently is not located in the /plugins/ directory used for manually-installed post-scan plugins. The code for the License Policy plugin can be found at /scancode-toolkit/src/licensedcode/plugin_license_policy.py and illustrates how a plugin can be used to analyze the results of a ScanCode scan using external data files and add the results of that analysis as a new field in the ScanCode JSON output file.

How-To Guides

How To Add a New License for Detection
How to add a new license for detection?

To add new license, you first need to select a new and unique license key (mit and gpl-2.0 are some of the existing license keys). All licenses are stored as plain text files in the src/licensedcode/data/licenses directory using their key as part of the file names.

You need to create a pair of files:

  • a file with the text of the license saved in a plain text file named key.LICENSE

  • a small text data file (in YAML format) named key.yml that contains license information such as:

    key: my-license
    name: My License
    

The key name can contain only these symbols:

  • lowercase letters from a to z,

  • numbers from 0 to 9,and

  • dash - and . period signs. No spaces.

Save these two files in the src/licensedcode/data/licenses/ directory.

Done!

See the src/licensedcode/data/licenses/ directory for examples.

How to Add New License Rules for Enhanced Detection

ScanCode relies on license rules to detect licenses. A rule is a simple text file containing a license text or notice or mention. And a small YAML text file that tells ScanCode which licenses to report when the text is detected.

See the FAQ for a high level description of How to Add New License Rules for Enhanced Detection.

How to add a new license detection rule?

A license detection rule is a pair of files:

  • a plain text rule file that is typically a variant of a license text, notice or license mention.

  • a small text data file (in YAML format) documenting which license(s) should be detected for the rule text.

To add a new rule, you need to pick a unique base file name. As a convention, we like to include the license key(s) that should be detected in that name to make it more descriptive. For example: mit_and_gpl-2.0 is a good base name. Add a suffix to make it unique if there is already a rule with this base name. Do not use spaces or special characters in that name.

Then create the rule file in the src/licensedcode/data/rules/ directory using this name, replacing selected_base_name with the base name you selected:

selected_base_name.RULE

Save your rule text in this file.

Then create the YAML data file in the src/licensedcode/data/rules/ directory using this name:

selected_base_name.yml

For a simple mit and gpl-2.0 detection license keys detection, the content of this file can be this YAML snippet:

licenses:
    - mit
    - gpl-2.0

Save these two files in the src/licensedcode/data/licenses/ directory and you are done!

See the src/licensedcode/data/rules/ directory for examples.

More (advanced) rules options:

  • you can use a notes: text field to document this rule.

  • if no license should be detected for your .RULE text, do not add a list of license keys, just add a note.

  • .RULE text can contain special text regions that can be ignored when scanning for licenses. You can mark a template region in your rule text using {{double curly braces}} and up to five words can vary and still match this rule. You must add this field in your .yml data file to mark this rule as a template

template: yes
  • By using a number after the opening braces, more than five words can be skipped. With {{10 double curly braces }} ten words would be skipped.

  • To mark a rule as detecting a choice of licenses, add this field in your .yml file:

    license_choice: yes
    

See the #257 issue and the related #258 pull request for an example: this adds a new rule to detect a combination of MIT or GPL.

How it all Works

Overview
How does ScanCode work?

For license detection, ScanCode uses a (large) number of license texts and license detection ‘rules’ that are compiled in a search index. When scanning, the text of the target file is extracted and used to query the license search index and find license matches.

For copyright detection, ScanCode uses a grammar that defines the most common and less common forms of copyright statements. When scanning, the target file text is extracted and ‘parsed’ with this grammar to extract copyright statements.

ScanCode-Toolkit performs the scan on a codebase in the following steps :

  1. Collect an inventory of the code files and classify the code using file types,

  2. Extract files from any archive using a general purpose extractor

  3. Extract texts from binary files if needed

  4. Use an extensible rules engine to detect open source license text and notices

  5. Use a specialized parser to capture copyright statements

  6. Identify packaged code and collect metadata from packages

  7. Report the results in the formats of your choice (JSON, CSV, etc.) for integration with other tools

Scan results are provided in various formats:

  • a JSON file simple or pretty-printed,

  • SPDX tag value or XML, RDF formats,

  • CSV,

  • a simple unformatted HTML file that can be opened in browser or as a spreadsheet.

For each scanned file, the result contains:

  • its location in the codebase,

  • the detected licenses and copyright statements,

  • the start and end line numbers identifying where the license or copyright was found in the scanned file, and

  • reference information for the detected license.

For archive extraction, ScanCode uses a combination of Python modules, 7zip and libarchive/bsdtar to detect archive types and extract these recursively.

Several other utility modules are used such as libmagic for file and mime type detection.

Contribute

Contributing to Code Development

See CONTRIBUTING.rst for details.

Code layout and conventions

Source code is in src/ Tests are in tests/.

There is one Python package for each major feature under src/ and a corresponding directory with the same name under tests (but this is not a package by design).

Each test script is named test_XXXX and while we love to use py.test as a test runner, most tests have no dependencies on py.test, only on the unittest module (with the exception of some command line tests that depend on pytest monkeypatching capabilities.

When source or tests need data files, we store these in a data subdirectory.

We use PEP8 conventions with a relaxed line length that can be up to 90’ish characters long when needed to keep the code clear and readable.

We store pre-built bundled native binaries in bin/ sub-directories of each src/ packages. These binaries are organized by OS and architecture. This ensures that ScanCode works out of the box either using a checkout or a download, without needing a compiler and toolchain to be installed. The corresponding source code for the pre-built binaries are stored in a separate repository at https://github.com/nexB/scancode-thirdparty-src.

We store bundled thirdparty components and libraries in the thirdparty directory. Python libraries are stored as wheels, eventually pre-built if the corresponding wheel is not available in the Pypi repository. Some of these components may be advanced builds with bug fixes or advanced patches.

We write tests, a lot of tests, thousands of tests. Several tests are data-driven and use data files as test input and sometimes data files as test expectation (in this case using either JSON or YAML files). The tests should pass on Linux 64 bits, Windows 32 and 64 bits and on MacOSX 10.6.8 and up. We maintain two CI loops with Travis (Linux) at https://travis-ci.org/nexB/scancode-toolkit and Appveyor (Windows) at https://ci.appveyor.com/project/nexB/scancode-toolkit.

When finding bugs or adding new features, we add tests. See existing test code for examples.

More info:

  • Source code and license datasets are in the /src/ directory.

  • Test code and test data are in the /tests/ directory.

  • Datasets and test data are in /data/ sub-directories.

  • Third-party components are vendored in the /thirdparty/ directory. ScanCode is self contained and should not require network access for installation or configuration of third-party libraries.

  • Additional pre-compiled vendored binaries are stored in bin/ sub-directories of the /src/ directory with their sources in this repo: https://github.com/nexB/scancode-thirdparty-src/

  • Porting ScanCode to other OS (FreeBSD, etc.) is possible. Enter an issue for help.

  • Bugs and pull requests are welcomed.

  • See the wiki and CONTRIBUTING.rst for more info.

Running tests

ScanCode comes with over 13,000 unit tests to ensure detection accuracy and stability across Linux, Windows and macOS OSes: we kinda love tests, do we?

We use pytest to run the tests: call the py.test script to run the whole test suite. This is installed by pytest, which is bundled with a ScanCode checkout and installed when you run ./configure).

If you are running from a fresh git clone and you run ./configure and then source bin/activate the py.test command will be available in your path.

Alternatively, if you have already configured but are not in an activated “virtualenv” the py.test command is available under <root of your checkout>/bin/py.test

(Note: paths here are for POSIX, but mostly the same applies to Windows)

If you have a multiprocessor machine you might want to run the tests in parallel (and faster) For instance: py.test -n4 runs the tests on 4 CPUs. We typically run the tests in verbose mode with py.test -vvs -n4.

You can also run a subset of the test suite as shown in the CI configs https://github.com/nexB/scancode-toolkit/blob/develop/appveyor.yml#L6 e,g, py.test -n 2 -vvs tests/scancode runs only the test scripts present in the tests/scancode directory. (You can pass a path to a specific test script file there too).

See also https://docs.pytest.org for details or use the py.test -h command to show the many other options available.

One useful option is to run a select subset of the test functions matching a pattern with the -k option, for instance: py.test -vvs -k tcpdump would only run test functions that contain the string “tcpdump” in their name or their class name or module name .

Another useful option after a test run with some failures is to re-run only the failed tests with the --lf option, for instance: py.test -vvs --lf would only run only test functions that failed in the previous run.

pip requirements and the configure script

ScanCode use the configure and configure.bat (and etc/configure.py behind the scenes) scripts to install a virtualenv , install required packaged dependencies as pip requirements and more configure tasks such that ScanCode can be installed in a self-contained way with no network connectivity required.

Earlier unreleased versions of ScanCode where using buildout to install and configure eventually complex dependencies. We had some improvements that were merged in the upstream buildout to support bootstrapping and installing without a network connection and When we migrated to use pip and wheels as new, improved and faster way to install and configure dependencies we missed some of the features of buildout like the recipes, being able to invoke arbitrary Python or shell scripts after installing packages and have scripts or requirements that are operating system-specific.

ScanCode requirements and third-party Python libraries

In a somewhat unconventional way, all the required libraries are bundled aka. Copied in the repo itself in the thirdparty/ directory. If ScanCode were only a library it would not make sense. But it is first an application and having a well defined frozen set of dependent packages is important for an app. The benefit of this approach (combined with the configure script) means that a mere checkout of the repository contains everything needed to run ScanCode except for a Python interpreter.

Using ScanCode as a Python library

ScanCode can be used alright as a Python library and is available as as a Python wheel in Pypi and installed with pip install scancode-toolkit.

How to cut a new release:
  • run bumpversion with major, minor or patch to bump the version in:

    • src/scancode/__init__.py

    • setup.py

    • Update the CHANGELOG.rst

  • commit changes and push changes to develop:

    • git commit -m "commit message"

    • git push --set-upstream origin develop

  • merge develop branch in master and tag the release.

    • git checkout master

    • git merge develop

    • git tag -a v1.6.1 -m "Release v1.6.1"

    • git push --set-upstream origin master

    • git push --set-upstream origin v1.6.1

  • draft a new release in GitHub, using the previous release blurb as a base. Highlight new and noteworthy changes from the CHANGELOG.rst.

  • run etc/release/release.sh locally.

  • upload the release archives created in the dist/ directory to the GitHub release page.

  • save the release as a draft. Use the previous release notes to create notes in the same style. Ensure that the link to third-party source code is present.

  • test the downloads.

  • publish the release on GitHub

  • then build and publish the released wheel on Pypi. For this you need your own Pypi credentials (and get authorized to publish Pypi release: ask @pombredanne) and you need to have the twine package installed and configured.

    • Build a .whl with python setup.py bdist_wheel

    • Run twine with twine upload dist/<path to the built wheel>

    • Once uploaded check the published release at https://pypi.python.org/pypi/scancode-toolkit/

    • Then create a new fresh local virtualenv and test the wheel installation with: pip install scancode-toolkit

Contributing to the Documentation
Setup Local Build

To get started, create or identify a working directory on your local machine.

Open that directory and execute the following command in a terminal session:

git clone https://github.com/nexB/scancode-toolkit.git

That will create an /scancode-toolkit directory in your working directory. Now you can install the dependencies in a virtualenv:

cd scancode-toolkit
virtualenv -p /usr/bin/python3.6 docs-venv
source docs-venv/bin/activate

Now, the following prerequisites are installed

  • Sphinx

  • sphinx_rtd_theme (the format theme used by ReadTheDocs)

  • docs8 (style linter)

pip install Sphinx sphinx_rtd_theme doc8

Now you can build the HTML documents locally:

cd docs
make html

Assuming that your Sphinx installation was successful, Sphinx should build a local instance of the documentation .html files:

open build/html/index.html

Note

In case this command did not work, for example on Ubuntu 18.04 you may get a message like “Couldn’t get a file descriptor referring to the console”, try:

see build/html/index.html

You now have a local build of the AboutCode documents.

Share Document Improvements

Ensure that you have the latest files:

git pull
git status

Before commiting changes run Continious Integration Scripts locally to run tests. Refer Continuous Integration for instructions on the same.

Follow standard git procedures to upload your new and modified files. The following commands are examples:

git status
git add source/index.rst
git add source/how-to-scan.rst
git status
git commit -m "New how-to document that explains how to scan"
git status
git push
git status

The Scancode-Toolkit webhook with ReadTheDocs should rebuild the documentation after your Pull Request is Merged.

Refer the Pro Git Book available online for Git tutorials covering more complex topics on Branching, Merging, Rebasing etc.

Continuous Integration

The documentations are checked on every new commit through Travis-CI, so that common errors are avoided and documentation standards are enforced. Travis-CI presently checks for these 3 aspects of the documentation :

  1. Successful Builds (By using sphinx-build)

  2. No Broken Links (By Using link-check)

  3. Linting Errors (By Using Doc8)

So run these scripts at your local system before creating a Pull Request:

cd docs
./scripts/sphinx_build_link_check.sh
./scripts/doc8_style_check.sh
Style Checks Using Doc8
How To Run Style Tests

In the project root, run the following command:

$ doc8 --max-line-length 100 docs/source/ --ignore D000

A sample output is:

Scanning...
Validating...
docs/source/misc/licence_policy_plugin.rst:37: D002 Trailing whitespace
docs/source/misc/faq.rst:45: D003 Tabulation used for indentation
docs/source/misc/faq.rst:9: D001 Line too long
docs/source/misc/support.rst:6: D005 No newline at end of file
========
Total files scanned = 34
Total files ignored = 0
Total accumulated errors = 326
Detailed error counts:
    - CheckCarriageReturn = 0
    - CheckIndentationNoTab = 75
    - CheckMaxLineLength = 190
    - CheckNewlineEndOfFile = 13
    - CheckTrailingWhitespace = 47
    - CheckValidity = 1

Now fix the errors and run again till there isn’t any style error in the documentation.

What is Checked?

PyCQA is an Organization for code quality tools (and plugins) for the Python programming language. Doc8 is a sub-project of the same Organization. Refer this README for more details.

What is checked:

  • invalid rst format - D000

  • lines should not be longer than 100 characters - D001

    • RST exception: line with no whitespace except in the beginning

    • RST exception: lines with http or https URLs

    • RST exception: literal blocks

    • RST exception: rst target directives

  • no trailing whitespace - D002

  • no tabulation for indentation - D003

  • no carriage returns (use UNIX newlines) - D004

  • no newline at end of file - D005

Interspinx

ScanCode toolkit documentation uses Intersphinx to link to other Sphinx Documentations, to maintain links to other Aboutcode Projects.

To link sections in the same documentation, standart reST labels are used. Refer Cross-Referencing for more information.

For example:

.. _my-reference-label:

Section to cross-reference
--------------------------

This is the text of the section.

It refers to the section itself, see :ref:`my-reference-label`.

Now, using Intersphinx, you can create these labels in one Sphinx Documentation and then referance these labels from another Sphinx Documentation, hosted in different locations.

You just have to add the following in the conf.py file for your Sphinx Documentation, where you want to add the links:

extensions = [
'sphinx.ext.intersphinx'
]

intersphinx_mapping = {'aboutcode': ('https://aboutcode.readthedocs.io/en/latest/', None)}

To show all Intersphinx links and their targets of an Intersphinx mapping file, run:

python -msphinx.ext.intersphinx https://aboutcode.readthedocs.io/en/latest/objects.inv

Warning

python -msphinx.ext.intersphinx https://aboutcode.readthedocs.io/objects.inv will give error.

This enables you to create links to the aboutcode Documentation in your own Documentation, where you modified the configuration file. Links can be added like this:

For more details refer :ref:`aboutcode:doc_style_guide`.

You can also not use the aboutcode label assigned to all links from aboutcode.readthedocs.io, if you don’t have a label having the same name in your Sphinx Documentation. Example:

For more details refer :ref:`doc_style_guide`.

If you have a label in your documentation which is also present in the documentation linked by Intersphinx, and you link to that label, it will create a link to the local label.

For more information, refer this tutorial named Using Intersphinx.

Style Conventions for the Documentaion
  1. Headings

    (Refer) Normally, there are no heading levels assigned to certain characters as the structure is determined from the succession of headings. However, this convention is used in Python’s Style Guide for documenting which you may follow:

    # with overline, for parts

    • with overline, for chapters

    =, for sections

    -, for subsections

    ^, for sub-subsections

    “, for paragraphs

  2. Heading Underlines

    Do not use underlines that are longer/shorter than the title headline itself. As in:

    Correct :
    
    Extra Style Checks
    ------------------
    
    Incorrect :
    
    Extra Style Checks
    ------------------------
    

Note

Underlines shorter than the Title text generates Errors on sphinx-build.

  1. Internal Links

    Using :ref: is advised over standard reStructuredText links to sections (like `Section title`_) because it works across files, when section headings are changed, will raise warnings if incorrect, and works for all builders that support cross-references. However, external links are created by using the standard `Section title`_ method.

  2. Eliminate Redundancy

    If a section/file has to be repeated somewhere else, do not write the exact same section/file twice. Use .. include: ../README.rst instead. Here, ../ refers to the documentation root, so file location can be used accordingly. This enables us to link documents from other upstream folders.

  3. Using :ref: only when necessary

    Use :ref: to create internal links only when needed, i.e. it is referenced somewhere. Do not create references for all the sections and then only reference some of them, because this created unnecessary references. This also generates ERROR in restructuredtext-lint.

  4. Spelling

    You should check for spelling errors before you push changes. Aspell is a GNU project Command Line tool you can use for this purpose. Download and install Aspell, then execute aspell check <file-name> for all the files changed. Be careful about not changing commands or other stuff as Aspell gives prompts for a lot of them. Also delete the temporary .bak files generated. Refer the manual for more information on how to use.

  5. Notes and Warning Snippets

    Every Note and Warning sections are to be kept in rst_snippets/note_snippets/ and rst_snippets/warning_snippets/ and then included to eliminate redundancy, as these are frequently used in multiple files.

Converting from Markdown

If you want to convert a .md file to a .rst file, this tool does it pretty well. You’d still have to clean up and check for errors as this contains a lot of bugs. But this is definitely better than converting everything by yourself.

This will be helpful in converting GitHub wiki’s (Markdown Files) to reStructuredtext files for Sphinx/ReadTheDocs hosting.

Roadmap

This is a high level list of what we are working on and what is completed.

Legend

white_check_mark completed clock1030 In progress white_large_square Planned, not started

Work in Progress

(see Completed features below)

Packages manifests and dependencies parsers
License Detection
  • white_check_mark support and detect license expressions (code in https://github.com/nexB/license-expression)

  • clock1030 support and detect composite licenses

  • white_large_square support custom licenses

  • white_large_square move licenses data set to external separate repository

  • white_check_mark Improved unknown license detection

  • white_check_mark sync with external sources (DejaCode, SPDX, etc.)

Copyrights
  • white_check_mark speed up copyright detection

  • white_check_mark improved detected lines range

  • white_check_mark streamline grammar of copyright parser

  • white_check_mark normalize holders and authors for summarizing

  • white_check_mark normalize and streamline results data format

Core features
  • white_check_mark pre scan filtering (ignore binaries, etc)

  • white_check_mark pre/post/ouput plugins! (worked as part of the GSoC by @yadsharaf )

  • white_check_mark scan plugins (e.g. plugins that run a scan to collect data)

  • white_check_mark support Python 3 #295

  • clock1030 transparent archive extraction (as opposed to on-demand with extractcode)

  • clock1030 scancode.yml configuration file for exclusions, defaults, scan failure conditions, etc.

  • white_large_square support scan pipelines and rules to organize more complex scans

  • white_check_mark scan baselining, delta scan and failure conditions (such as license change, etc) ( spawned as its the DeltaCode project)

  • white_large_square dedupe and similarities to avoid re-scanning. For now only identical files are scanned only once.

  • clock1030 Improved logging, tracing and error diagnostics

  • white_check_mark native support for ABC Data (See AboutCode Data : ABCD )

Classification, summarization and deduction
  • clock1030 File classification #426

  • white_check_mark summarize and aggregate data #377 at the top level

Source code support (some will be spawned as their own tool)
Compiled code support (will be spawned as their own tool)
Data exchange
  • white_check_mark SPDX data conversion #338

Packaging
  • white_large_square simpler installation, automated installer

  • white_check_mark distro-friendly packaging

  • clock1030 unbundle and package as multiple libaries (commoncode, extractcode, etc)

Documentation
  • white_large_square integration in a build/CI loop

  • white_large_square end to end guide to analyze a codebase

  • white_large_square hacking guides

  • white_large_square API doc when using ScanCode as a library

CI integration
  • white_large_square Plugins for CI (Jenkins, etc)

  • white_large_square Integration for CI (Travis, Appveyor, Drone, etc)

Other work in progress
Package mining and matching

(Note that this will be spawned in its project) Some code is in https://github.com/nexB/scancode-toolkit-contrib/

  • clock1030 exact matching

  • clock1030 attribute-based matching

  • clock1030 fuzzy matching

  • white_large_square peer-reviewed meta packages repo

  • white_large_square basic mining of package repositories

Other
  • white_large_square Crypto code detection

Completed features
Core scans
  • white_check_mark exact license detection

  • white_check_mark approximate license detection

  • white_check_mark copyright detection

  • white_check_mark file information (size, type, etc.)

  • white_check_mark URLs, emails, authors

Outputs and UI
  • white_check_mark JSON compact and pretty

  • white_check_mark plain HTML tables, also usable in a spreadsheet

  • white_check_mark fancy HTML ‘app’ with a file tree navigation, and scan results filtering, search and sorting

  • white_check_mark improved scans GUI now its own project: https://github.com/nexB/aboutcode-manager

  • white_check_mark simple scan summary

  • white_check_mark SPDX output

Package and dependencies
  • white_check_mark common model for packages data

  • white_check_mark basic support for common packages format

  • white_check_mark RPM packages base

  • white_check_mark NuGet packages base

  • white_check_mark Python packages base

  • white_check_mark PHP Composer packages support with dependencies

  • white_check_mark Java Maven POM packages support with dependencies

  • white_check_mark npm packages support with dependencies

Speed!
  • white_check_mark accelerate license detection indexing and scanning; include caching

  • white_check_mark scan using multiple processes to speed up overall scan

  • white_check_mark cache per-file scan to disk and stream final results

Other
  • white_check_mark archive extraction with extractcode

  • white_check_mark conversion of scan results to CSV

  • white_check_mark improved error handling, verbose and diagnostic output

Google Summer of Code 2017 - Final report
Project: Plugin architecture for ScanCode

Yash D. Saraf yashdsaraf@gmail.com


This project’s purpose was to create a decoupled plugin architecture for ScanCode such that it can handle plugins at different stages of a scan and can be coupled at runtime. These stages were,

1. Format :

In this stage, the plugins are supposed to run after the scanning is done and post-scan plugins are called. These plugins could be used for:

  • converting the scanned output to the given format (say csv, json, etc.)

HOWTO

Here, a plugin needs to add an entry in the scancode_output_writers entry point in the following format : '<format> = <module>:<function>'.

  • <format> is the format name which will be used as the command line option name (e.g csv or json ).

  • <module> is a python module which implements the output hook specification.

  • <function> is the function to which the scan output will be passed if this plugin is called.

The <format> name will be automatically added to the --format command line option and (if called) the scanned data will be passed to the plugin.

2. Post-scan :

In this stage, the plugins are supposed to run after the scanning is done. Some uses for these plugins were:

  • summarization of scan outputs

    e.g A post-scan plugin for marking is_source to true for directories with ~90% of source files.

  • simplification of scan outputs

    e.g The --only-findings option to return files or directories with findings for the requested scans. Files and directories without findings are omitted (not considering basic file information as findings)).

This option already existed, I just ported it to a post-scan plugin.

HOWTO

Here, a plugin needs to add an entry in the scancode_post_scan entry point in the following format '<name> = <module>:<function>'

  • <name> is the command line option name (e.g only-findings).

  • <module> is a python module which implements the post_scan hook specification.

  • <function> is the function to which the scanned files will be passed if this plugin is called

The command line option for this plugin will be automatically created using the <function> ‘s doctring as its help text and (if called) the scanned files will be passed to the plugin.

3. Pre-scan :

In this stage, the plugins are supposed to run before the scan starts. So the potential uses for these types of plugins were to:

  • ignore files based on a given pattern (glob)

  • ignore files based on their info i.e size, type etc.

  • extract archives before scanning

HOWTO

Here, a plugin needs to add an entry in the scancode_pre_scan entry point in the following format : '<name> = <module>:<class>'

  • <name> is the command line option name (e.g ignore ).

  • <module> is a python module which implements the pre_scan hook specification.

  • <class> is the class which is instantiated and its appropriate method is invoked if this plugin is called. This needs to extend the plugincode.pre_scan.PreScanPlugin class.

The command line option for this plugin will be automatically created using the <class> ‘s doctring as its help text. Since there isn’t a single spot where pre-scan plugins can be plugged in, more methods to PreScanPlugin class can be added which can represent different hooks, say to add or delete a scan there might be a method called process_scan.

If a plugin’s option is passed by the user, then the <class> is instantiated with the user input and its appropriate aforementioned methods are called.

4. Scan (proper):

In this stage, the plugins are supposed to run before the scan starts and after the pre-scan plugins are called. These plugins would have been used for

  • adding or deleting scans

  • adding dependency scans (whose data could be used in other scans)

No development has been done for this stage, but it will be quite similar to pre-scan.

5. Other work:

Group cli options in cli help

Here, the goal was to add command line options to pre-defined groups such that they are displayed in their respective groups when scancode -h or scancode --help is called. This helped to better visually represent the command line options and determine more easily what context they belong to.

Add a Resource class to hold all scanned info * Ongoing *

Here, the goal was to create a Resource class, such that it holds all the scanned data for a resource (i.e a file or a directory). This class would go on to eventually encapsulate the caching logic entirely. For now, it just holds the info and path of a resource.

6. What’s left?
  • Pre-scan plugin for archive extractions

  • Scan (proper) plugins

  • More complex post-scan plugins

  • Support plugins written in languages other than python

Additionally, all my commits can be found here.

Google Summer of Code 2019 - Final report
Project: scancode-toolkit to Python 3

Owner: Abhishek Kumar

Mentor: Philippe Ombredanne

Overview

Problem: Since Python 2.7 will retire in few months and will not be maintained any longer.

Solution: Scancode needs to be ported to python 3 and all test suites must pass on both version of Python. The main difference that makes Python 3 better than Python 2.x is that the support for unicode is greatly improved in Python 3. This will also be useful for scancode as scancode has users in more than 100 languages and it’s easy to translate strings from unicode to other languages.

Objective: To make scancode-toolkit installable on on Python 3.6 and higher, as presently it installs with Python 2.7 only.

Implementation
  • It was started in development mode(editable mode) and then it was moved to work in virtual environments.

  • I have worked module by module according to the order of hierarchy of modules. For example :All module is dependent on commoncode, so it must be ported first. In this way we have created the Porting order:

    1. commoncode

    2. plugincode

    3. typecode

    4. extractcode

    5. textcode

    6. scancode basics (some tests are integration tests and will have to wait to be ported)

    7. formattedcode, starting with JSON (some tests are integration tests and will have to wait to be ported)

    8. cluecode

    9. licensedcode

    10. packagedcode (depends on licensecode)

    11. summarycode

    12. fixup the remaining bits and tests

After porting each module, I have marked these modules as ported scanpy3 with help of conffest plugin (created by @pombredanne). Conffest plugin is heart of this project. Without this, it was very difficult to do. Dependencies was fixed at the time of porting the module where it was used.

Challenging part of Project

It is very difficult to deal with paths on different operating systems.The issue is around macOS/Windows/Linux. The first two OS handle unicode paths comfortably on Python 2 and 3 but not completely on macOS Mojave because its filesystem encoding is APFS. Linux paths are bytes and os.listdir is broken on Python 2. As a result you can only sanely handle Linux paths as bytes on Python 2. But on Python 3 path seems to be corrected as unicode on Linux.

For more details visit here :

We came with various Solution:

  • To use pathlib which generally handle paths correctly across platforms. And for backports we use pathlib 2. But this solution also fails because pathlib 2 does not work as expected wrt unicode vs bytes. And os.listdir also doesn’t work properly.

  • To use path.py which handles the paths across all the platforms even on macOS Mojave .

  • Use bytes on linux and python 3 and unicode everywhere.

We choose the third solution because it is most fundamental and simple and easy to use.

Project was tracked in this ticket nexB/scancode-toolkit#295

Project link : Port Scancode to Python 3

My contribution : List of Commits

Note : Please give your feedback here

Outcome

Now we have liftoff on Python 3 . We are able to run basic scans without errors on develop branch. You check it by running scancode -clipeu samples/ --json-pp - -n4 .

At last I would like to thanks my Mentor @pombredanne aka Philippe Ombredanne . He has helped lot in completing this project. He is very supportive and responsive. I have learned a lot from him. By his encouragement and motivation, I am very improving day by day, building and developing my skills. I have completed all the tasks that were in the scope of this GSoC project.

Long Running Issues - Help Needed
Roadmaps

This section provides a overview of ScanCode developement roadmap, in the sense what maintainers are considering, what the long-term goals are.

Good First Issue

A good first issue means it’s recommended for people who haven’t contributed to our codebase before.

A Solving Good First Issue is basically an issue based guide for new contributors to solve a Good First Issue.

Manitainers of ScanCode Toolkit label small bugs as good first issues for new contributors.

What you should understand before Solving a Good First Issue
  • ScanCode Toolkit tracks different kinds of issues using GitHub.

  • Some of these issues are labeled Good First Issue by the Maintainers, as in they recommend them.

  • A list of Good First Issue is also maintained here.

  • The list of Good First Issue contains a list of Issues, people assigned to them (or waiting to be assigned) and their status (active/completed).

  • Issues here are marked Solved using a Task List.

  • Contributors come at this issue (and not at individual issues) and ask the maintainers to be assigned.

  • After being assigned, contributors open another Issue labeled Solving Good First Issue so maintainers can Track their Progress on that Issue.

  • The task list in the new issue opened (labeled Solving Good First Issue) has to be updated by the Contributor.

Step by Step Workflow : Contributor’s Tasks
  1. Look at the Issues in Good First Issues List These are basically all the issues labeled Good First Issue with information on people assigned to the issues, and their status.

  2. Select a Good First Issue which isn’t assigned and comment in the Good First Issues List asking the maintainers to assign you.

  3. After you are assigned to that Issue by a maintainer, make sure you are assigned to the one you requested. It’ll look like [ ] #1724 @AyanSinhaMahapatra where #1724 is the Issue number and AyanSinhaMahapatra is your GitHub user ID.

  4. Open an Issue labeled Solving Good First Issue here .

  5. In this issue you opened, reference the following: (include #[number] in comments, like #1724)

    • The Original issue labeled Good First Issue that you are solving.

    • The Pull Request you open later.

    • The Good First Issues List

  6. Follow the Instruction on that Issue (It’s a Template you’ll just have to mark the Task List as you complete tasks)

    • Claim this issue

    • Reproduce

    • Create a Unit test

    • Come up with a Solution

    • Code your Solution

    • Run the tests locally

    • Commit and Push

    • Start a Pull Request

    • Make Sure all the Tests Pass

    • Done Ask in comments for a review :)

  7. Remind maintainers to close both Issues, after your Pull Request is Merged.

    • The Original issue labeled Good First Issue

    • The issue opened by you labeled Solving Good First Issue

First Timers Only

A first timers only. issue means we’ve worked to make it more legible to folks who either haven’t contributed to our codebase before, or even folks who haven’t contributed to open source before.

Small documenation inconsistencies are first timers only issues for new contributors.

Important Links
What you should understand before Solving a First Timers Only Issue
  • ScanCode Toolkit tracks different kinds of issues using GitHub.

  • Some of these issues are documentation inconsistencies listed here.

  • A list of First Timers Only Issues is also maintained here.

  • The list of First Timers Only contains a list of Issues, people assigned to them (or waiting to be assigned) and their status (active/completed).

  • Issues here are marked Solved using a Task List.

  • Contributors come at this issue and ask the maintainers to be assigned.

  • After being assigned, contributors open another Issue labeled First Timers Only so maintainers can Track their Progress.

  • The task list has to be updated by the Contributor.

Step by Step Workflow : Contributor’s Tasks
  1. Look at the Issues in First Timers Only List These are basically all the issues labeled First Timers Only issues, with information on people assigned to the issues, and their status.

  2. Select a First Timers Only issue which isn’t assigned to anyone yet, and comment on the List asking the maintainers to assign you.

  3. After you are assigned to that Issue by a maintainer, make sure you are assigned to the one you requested. It’ll look like [ ] #1724 @AyanSinhaMahapatra where #1724 is the Issue number and AyanSinhaMahapatra is your GitHub user ID.

  4. Open an Issue labeled First Timers Only here .

  5. In this issue you opened, reference the following: (include #[number] in comments, like #1724)

    • The Original issue labeled Good First Issue that you are solving.

    • The Pull Request you open later.

    • The Good First Issues List

  6. Follow the Instruction on that Issue (It’s a Template you’ll just have to mark the Task List as you complete tasks)

    • Issue Claimed

    • Review Guidelines

    • Refer Documentation

    • Build Docs Locally

    • Update

    • Commit and Push

    • Start a Pull Request

    • Make Sure all the Tests Pass

    • Done Ask in comments for a review :)

Miscellaneous

FAQ
Why ScanCode?

We could not find an existing tool (open source or commercial) meeting our needs:

  • usable from the command line or as library

  • running on Linux, Mac and Windows

  • written in a higher level language such as Python

  • easy to extend and evolve

Can licenses be synchronized with the DejaCode license library?

The license keys are the same that are used in DejaCode. They are kept in sync by hand in the short term. There is also a ticket to automate that sync with DejaCode and possibly other sources. See https://github.com/nexB/scancode-toolkit/issues/41

How is ScanCode different from licensecheck?

At a high level, ScanCode detects more licenses and copyrights than licensecheck does, reporting more details about the matches. It is likely slower.

In more details: ScanCode is a Python app using a data-driven approach (as opposed to carefully crafted regex):

  • for license scan, the detection is based on a (large) number of license full texts (~900) and license notices/rules (~1800) and is data driven as opposed to regex-driven. It detects exactly where in a file a license text is found. Just throw in more license texts to improve the detection.

  • for copyright scan, the approach is natural language parsing (using NLTK) with POS tagging and a grammar; it has a few thousand tests.

  • licenses and copyrights are detected in texts and binaries

Licensecheck (available here for reference: /https://metacpan.org/release/App-Licensecheck ) is a Perl script using hand-crafted regex patterns to find typical copyright statements and about 50 common licenses. There are about 50 license detection tests.

A quick test (in July 2015, before a major refactoring, but for this notice still valid) shows several things that are not detected by licensecheck that are detected by ScanCode.

How can I integrate ScanCode in my application?

More specifically, does this tool provide an API which can be used by us for the integration with my system to trigger the license check and to use the result?

In terms of API, there are two stable entry points:

#. The JSON output when you use it as a command line tool from any language or when you call the scancode.cli.scancode function from a Python script. #. Otherwise the scancode.cli.api module provides a simple function if you are only interested in calling a certain service on a given file (such as license detection or copyright detection)

Can I install ScanCode in a Unicode path?

Not for now. See https://github.com/nexB/scancode-toolkit/issues/867 There is a bug in virtualenv on Python2 https://github.com/pypa/virtualenv/issues/457 At this stage and until we completed the migration to Python 3 there is no way out but to use a path that contains only ASCII characters.

Support
Documentation

The ScanCode toolkit documentation lives at aboutcode.readthedocs.io/en/latest/scancode-toolkit/.

Issue Tracker

Post questions and bugs as GitHub tickets at: https://github.com/nexB/scancode-toolkit/issues

StackOverflow

Ask question on StackOverflow using the [scancode] tag.

Talk to the Developers

Join our Gitter Channel to talk with the developers of ScanCode Toolkit.

Documentation

For more information on Documentation or to leave feedback mail at aboutCode@groups.io, or leave a message at our Docs Channel.

Runtime Performance Reports

These are reports of runtimes for real life scans:

2015-09-03 by @rrjohnston

  • On Ubuntu 12.04 x86_64 Python 2.7.3 and ScanCode Version 1.3.1

  • Specs: 40 threads (2 processors, 10 cores each, with hyperthreading) 3.1 GHz 128GB RAM 8TB controller RAID5

  • scanned 195676 files in about 16.7 hours or about 3.25 file per second (using defaults licenses and copyrights)

  • notes: this version of ScanCode runs on a single thread so it does not make good use of extra processing power.

Scancode-Workbench Documentation

ScanCode Workbench allows you take the scan results from the ScanCode Toolkit and create a software inventory annotated with your summaries or conclusions (we call these Conclusions) at any levels of the codebase you choose.

The attributes you add (e.g., Name, Version, Owner, License Expression, Copyright) to your Conclusion about a single package or file – or a higher-level group of packages and/or files – can then be exported to a JSON or SQLite file. In addition, Conclusions created in ScanCode Workbench can be exported to DejaCode.

Basics

Scancode Workbench Views
Directory Tree

An interactive directory tree is always present on the left side of the application. The tree is expandable and collapsible. This allows the user to navigate the codebase structure. If a directory is selected, only that directory and its sub-files and folders will be shown in the view. Similarly, if a single file is selected, only information for that selected file will be shown.

_images/navigate-code-tree.gif
Table View

In the table view, the available clues detected by ScanCode are shown in a tabular format. A user can see provenance clues such as license and copyright information detected by ScanCode. A user can also see the file information (e.g. file type, file size, etc) and package information (package type, primary language of package) that was detected. The columns can be sorted as well as shown or hidden based on what the user’s preferences. Searching for specific clues (license names, copyrights, etc.) is also available in this view.

_images/table-view.gif
Chart Summary View

With the chart summary view, a user can select a node in the directory tree (i.e., a directory, folder or file) and display a horizontal bar chart listing the values identified in the scanned codebase – that is, the clues detected by ScanCode Toolkit – for a number of different attributes. The attributes are a subset of the columns displayed in the table view, and can be selected by clicking the dropdown at the top of the view. The chart displays the full range of values for the selected directory tree node and attribute and the number of times each value occurs in the scanned codebase.

_images/scancode-workbench-chart-summary.gif
Building Requirements
Linux
  • Python 2.7

  • Node.js version 6.x or later

  • npm 3.10.x or later but <= 5.2.0 (run npm install npm@5.2.0 -g)

MacOS
  • Python 2.7

  • Node.js >=6.x or later but <=8.9.4

  • npm 3.10.x or later but <= 5.2.0 (run npm install npm@5.2.0 -g)

  • Command Line Tools for Xcode (run xcode-select --install to install)

Windows
  • Node.js 6.x or later

  • npm 3.10.x or later but <= 5.2.0 (run npm install npm@5.2.0 -g)

  • Python v2.7.x

    • Make sure your Python path is set. To verify, open a command prompt and type python --version. Then, the version of python will be displayed.

  • Visual C++ Build Environment:

    • Either:

    • Option 1: Install Visual C++ Build Tools 2015 (or modify an existing installation) and select Common Tools for Visual C++ during setup. This also works with the free Community and Express for Desktop editions.

    • Option 2: Visual Studio 2015 (Community Edition or better)

ScanCode Workbench Platform Support

Our approach for platform support is to focus on one primary release for each of Linux, MacOS and Windows. The Priority definitions are:

  1. Primary - These are the primary platforms for build/test/release on an ongoing basis.

  2. Secondary - These are platforms where the primary ScanCode Workbench release for the corresponding OS Group should be forward-compatible, e.g., Windows 7 build should work on Windows 10. Issues reported and traced to a Secondary platform may not be fixed.

  3. Tertiary - These are any other platforms not listed as Primary or Secondary. In these cases, we will help users help themselves, but we are likely not to fix Issues that only surface on a Tertiary platform.

OS Group

Desktop OS Version

Arch

Priority

Notes

Windows

Windows 7 SP1

x64

1

Windows

Windows 10 SP?

x64

2

MacOS

10.9 Mavericks

x64

1

MacOS

10.10 Yosemite

x64

2

MacOS

10.11 El Capitan

x64

2

MacOS

10.12 Sierra

x64

2

Linux Deb

Ubuntu 12.04

x64

1

From Electron Docs: The prebuilt ia32 (i686) and x64 (amd64) binaries of Electron are built on Ubuntu 12.04.

Linux Deb

Ubuntu 14.xx

x64

2

Verified to be able to run the prebuilt binaries of Electron.

Linux Deb

Ubuntu 16.xx

x64

2

Verified to be able to run the prebuilt binaries of Electron.

Linux

Fedora 21

x64

2

Verified to be able to run the prebuilt binaries of Electron.

Linux

Debian 8

x64

2

Verified to be able to run the prebuilt binaries of Electron.

Linux RH

CentOS 7.xx

x64

?

Linux RH

RHEL 7.xx

x64

?

Electron Supported Platforms

https://electronjs.org/docs/tutorial/support#supported-platforms

The following platforms are supported by Electron:

MacOS

Only 64-bit binaries are provided for MacOS, and the minimum MacOS version supported is MacOS 10.9.

Windows

Windows 7 and later are supported, while older operating systems are not supported (and do not work). Both ia32 (x86) and x64 (amd64) binaries are provided for Windows. Please note: the ARM version of Windows is not supported for now.

Linux

The prebuilt ia32 (i686) and x64 (amd64) binaries of Electron are built on Ubuntu 12.04, and the ARM binary is built against ARM v7 with hard-float ABI and NEON for Debian Wheezy.

Whether the prebuilt binary can run on a distribution depends on whether the distribution includes the libraries that Electron is linked to on the building platform, so only Ubuntu 12.04 is guaranteed to work, but the following platforms are also verified to be able to run the prebuilt binaries of Electron:

  • Ubuntu 12.04 and later

  • Fedora 21

  • Debian 8

Check for Errors in the Developer Tools

When an unexpected error occurs in ScanCode Workbench, you will normally see a dialog message which provides details about the error and allows you to create an issue.

_images/dialog-error.png

If you can reproduce the error, use this approach to get the stack trace and report the issue. Open the Developer Tools with Ctrl+Shift+I or Alt+Cmd+I. From there, click the Console tab. Include the error that is logged in the issue in a code block or a file attachment.

_images/developer-tools-error.png

Tutorials

Creating Conclusions

A Conclusion in ScanCode Workbench refers to the documentation of your analysis and conclusions about the name, version, owner, copyright, license expression and other attributes for a single software package or file or – if you conclude these attributes are shared by a group of packages and/or files – for that group of packages/files.

You can record your Conclusions throughout the codebase you’re analyzing, at any level of the codebase (i.e., nodes in the directory tree representing the codebase) you think will best reflect the results of your analysis.

To create a Conclusion, begin by navigating to the ScanDataTable view.

_images/scandatatable-01.png

In the directory tree on the left, choose the directory, package or file you want to annotate, right-click that node, and select Edit Conclusion in the menu that appears. This will display a form with the path to that node displayed at the top of the form, and a series of attribute names (e.g., Status, Name, Version, License Expression, Owner, Copyright) and associated textboxes, dropdowns or radio buttons to record your input.

_images/conclusion-form-01.png
Conclusion Definitions

The following fields are available when creating a Conclusion:

Conclusion Field

Description

Status

Used to document status of Conclusion creation. The dropdown choices: Analyzed - A Conclusion has been created, Needs Attention - A Conclusion is flagged for further review, Original Code - A Conclusion references code from your organization, Not Reporting - A Conclusion that will not be reported and can be ignored.

Name

The primary name for your Conclusion (usually a file, directory or library name). A Conclusion can represent any software-related object. Any Conclusion can contain one or more sub-Conclusions. The combined Conclusion Name and Version must be unique.

Version

The Conclusion version number.

License Expression

This is the overall license (an individual license or combination of several licenses) for the Conclusion. The Conclusion form will populate a dropdown with any License Expression data detected by ScanCode when the imported scan was run, using the ScanCode License Expression syntax (e.g., gpl-2.0 represents the GPL 2.0 license). The user can also manually add one or more License Expressions by typing in the textbox and then hitting the Enter key. The License Expression is intended to capture the facts of a license (primarily the text, as provided by its owner), as well as an organization’s interpretation and policy regarding that license.

Owner

An Owner identifies the original creator (copyright holder) of the code covered by the Conclusion. If this Conclusion code is in its original, unmodified state, the Conclusion owner is associated with the original author/publisher. If this Conclusion code has been copied and modified, the Conclusion owner should be the owner that has copied and modified it.

Copyright

The Copyright notice that applies to the Conclusion code under the License Expression.

Modified

A Yes/No choice indicating whether the Conclusion code has been modified.

Deployed

A Yes/No choice indicating whether the Conclusion code has been deployed.

Code Type

The default choices are Source, Binary, Mixed and Document.

Notes

Any notes or comments the user wants to record.

Feature

The name of a product feature or codebase module that applies to the code covered by the Conclusion.

Purpose

The type of code covered by the Conclusion, e.g., Core, Test, Build, Documentation.

Programming Language

The primary language of the Conclusion code.

Homepage URL

The homepage URL for the Conclusion code.

Download URL

The download URL for the original Conclusion code.

License URL

The URL for the primary license represented by the License Expression.

Notice URL

The URL for the license notice that applies to the code covered by the Conclusion.

Importing and Exporting a JSON File
Import a ScanCode JSON File
_images/import-json-file.gif
  • We have provided a set of sample scans that you can quickly review in ScanCode Workbench in order to get a sense of its functionality and the types of information captured by a scan. The samples are located at https://github.com/nexB/scancode-workbench/tree/develop/samples.

  • To import a ScanCode JSON file:

    • Open the File menu and select Import JSON File (keyboard shortcut: Ctrl+I or ⌘+I ).

    • In the dialog window that opens, navigate to the JSON file you want to import, select the file and click Open.

    • You will then be prompted to choose a filename and location to save the JSON file as a SQLite database file. Add a filename, select the folder in which you want to save the SQLite database file, and click Save.

    • ScanCode Workbench will then create a SQLite database file from your JSON file, indicated by the status message “Creating Database …”

    • Once the process has finished, the status message will be replaced by an expandable code tree and, to the right of the tree, a table displaying provenance information generated by ScanCode.

Export a JSON file
  • To export a JSON file:

    • Select the File menu and then select Export JSON File (keyboard shortcut: Ctrl+E or ⌘+E ).

    • In the dialog window that opens, add a name for the file, navigate to the directory in which you want to save the file and click Save.

License Policy support in ScanCode Workbench

ScanCode Workbench now has basic support for tracking and viewing license policies that have been applied to a scancode-toolkit scan. In order for things to work, your initial scancode scan must be run with the --license-policy option. You can read more about that here: License Policy Plugin.

The basics

While the License Policy Plugin can be customized with any number of custom fields and values, ScanCode Workbench currently only supports a pre-defined set of policy labels.

license_key

label

scancode_license_key

Approved License

scancode_license_key

Prohibited License

scancode_license_key

Recommended License

scancode_license_key

Restricted License

This means in order to take advantage of ScanCode Workbench’s policy features, your license-policy.yml needs to have license_key and label fields at the very least.

Additionally, in order to take advantage of policy visualizations, label values must be one of the 4 above values: Approved License, Prohibited License, Recommended License or Restricted License. Later versions of ScanCode Workbench will eventually evolve to support more dynamic policy values.

Here is a simple example of a valid license-policy.yml file:

license_policies:
-   license_key: apache-2.0
    label: Approved License
-   license_key: apache-1.1
    label: Prohibited License
-   license_key: lgpl-2.1-plus
    label: Recommended License
-   license_key: cpl-1.0
    label: Restricted License

After running a scan with that particular license-policy.yml file, viewing the scan in ScanCode Workbench will look like the following:

_images/policy-view.png

As you can see, files which have detected licenses that fall under a particular policy will be shown in the JSTree view with specific icons. This way, you are able to quickly see what files fall under a specific policy.

Additionally, policy details can be found in the scan data view in their own column: License Policy. This column has been added to both the “Origin” column set and “License info” column set.

Opening and Saving a SQlite File
Open a SQLite File
  • To open a SQLite File:

    • Select the File menu and then select Open SQLite File (keyboard shortcut: Ctrl+O or ⌘+O ).

    • In the dialog window that opens, navigate to the SQLite file you want to open, select the file and click Open.

Save as a New SQLite File
  • To save as a new SQLite file:

    • Select the File menu and then select Save As New SQLite File (keyboard shortcut: Ctrl+S or ⌘+S ).

    • In the dialog window that opens, add a name for the file, navigate to the directory in which you want to save the file and click Save.

Deltacode Documentation

Welcome to Deltacode Documentation.

Comprehensive Installation

DeltaCode requires Python 2.7.x and is tested on Linux, Mac, and Windows. Make sure Python 2.7 is installed first.

System Requirements
  • Hardware : DeltaCode will run best with a modern X86 processor and at least 1GB of RAM and 250MB of disk.

  • Supported operating systems : DeltaCode should run on these OSes:

    1. Linux: on most recent 64-bit Linux distributions (32-bit distros are only partially supported),

    2. Mac: on recent Mac OSX (10.6.8 and up),

    3. Windows: on Windows 7 and up (32- or 64-bit) using a 32-bit Python.

Prerequisites

DeltaCode needs a Python 2.7 interpreter.

Installation on Linux and Mac

Download and extract the latest ScanCode release from: https://github.com/nexB/deltacode/releases/latest

Open a terminal in the extracted directory and run:

./deltacode --help

This will configure DeltaCode and display the command line help.

Installation on Windows

Download the latest ScanCode release zip file from: https://github.com/nexB/deltacode/releases/latest

  • In Windows Explorer, select the downloaded DeltaCode zip and right-click.

  • In the pop-up menu select ‘Extract All…’

  • In the pop-up window ‘Extract zip folders’ use the default options to extract.

  • Once the extraction is complete, a new Windows Explorer window will pop-up.

  • In this Explorer window, select the new folder that was created and right-click.

  • In the pop-up menu select ‘Properties’

  • In the pop-up window ‘Properties’, select the Location value. Copy this in clipboard.

  • Press the start menu button.

  • In the search box type

cmd
  • Select ‘cmd.exe’ listed in the search results.

  • A new ‘cmd.exe’ window pops-up.

  • In this window (aka. a command prompt), type this (this is ‘cd’ followed by a space)

cd
  • then right-click in this window and select Paste. This will paste the path where you extracted DeltaCode.

  • Press Enter.

  • This will change the current location of your command prompt to the root directory where DeltaCode is installed.

  • Then type

deltacode --help
  • Press enter. This will configure your DeltaCode installation.

  • Several messages are displayed followed by the deltacode command help.

  • The installation is complete.

Un-installation
  • Delete the directory in which you extracted DeltaCode.

  • Delete any temporary files created in your system temp directory under a deltacode directory.

Deltacode Output: Format, Fields and Structure

Usage: deltacode [OPTIONS]

  Identify the changes that need to be made to the 'old' scan file (-o or --old)
  in order to generate the 'new' scan file (-n or --new).  Write the results to
  a .json file (-j or --json-file) at a user-designated location.  If no file
  option is selected, print the JSON results to the console.

Options:
  -h, --help                Show this message and exit.
  --version                 Show the version and exit.
  -n, --new PATH            Identify the path to the "new" scan file [required]
  -o, --old PATH            Identify the path to the "old" scan file [required]
  -j, --json-file FILENAME  Identify the path to the .json output file
  -a, --all-delta-types     Include unmodified files as well as all changed
                            files in the .json output.  If not selected, only
                            changed files are included.
Output Formats

DeltaCode provides two output formats for the results of a DeltaCode codebase comparison: JSON and CSV.

The default output format is JSON. If the command-line input does not include an output flag (-j or --json-file) and the path to the output file, the results of the DeltaCode comparison will be displayed in the console in JSON format. Alternatively, the results will be saved to a .json file if the user includes the -j or --json-file flag and the output file’s path, e.g.:

deltacode -n [path to the 'new' codebase] -o [path to the 'old' codebase] -j [path to the JSON output file]

Once a user has generated a DeltaCode JSON output file, he or she can convert that JSON output to CSV format by running a command with this structure::

python etc/scripts/json2csv.py [path to the JSON input file] [path to the CSV output file]

See also JSON to CSV Conversion.

Overall Structure
JSON

Top-Level JSON

DeltaCode’s JSON output comprises the following six fields/keys and values at the top level:

  1. deltacode_notice – A string of the terms under which the DeltaCode output is provided.

  2. deltacode_options – A JSON object containing three key/value pairs:

    • --new – A string identifying the path to the JSON file containing the ScanCode output of the codebase the user wants DeltaCode to treat as the ‘new’ codebase.

    • --old – A string identifying the path to the JSON file containing the ScanCode output of the codebase the user wants DeltaCode to treat as the ‘old’ codebase.

    • --all-delta-types – A true or false value.
      • This value will be true if the command-line input includes the -a or --all-delta-types flag, in which case the deltas field described below will include details for unmodified files as well as all changed files.

      • If the user does not include the -a or --all-delta-types flag, the value will be false and unmodified files will be omitted from the DeltaCode output.

  3. deltacode_version – A string representing the version of DeltaCode on which the codebase comparison was run.

  4. deltacode_errors – A list of one or more strings identifying errors (if any) that occurred during the codebase-comparison process.

  5. deltas_count – An integer representing the number of ‘Delta’ objects – the file-level comparisons of the two codebases (discussed in the next section) – contained in the DeltaCode output’s deltas key/value pair.

    • If the user’s command-line input does not include the -a or --all-delta-types flag (see the discussion above of the --all-delta-types field/key), the DeltaCode output will omit details for unmodified files and consequently the deltas_count field will not include unmodified files.

  6. deltas – A list of ‘Delta’ objects, each of which represents a file-level comparison (i.e., the “delta”) of the ‘new’ and ‘old’ codebases. The Delta object is discussed in further detail in the next section.

This is the top-level JSON structure of the key/value pairs described above:

{
  "deltacode_notice": "",
  "deltacode_options": {
    "--new": "",
    "--old": "",
    "--all-delta-types": false
  },
  "deltacode_version": "",
  "deltacode_errors": [],
  "deltas_count": 0,
  "deltas": [one or more Delta objects]
}

The Delta Object

Each Delta object consists of four key/value pairs:

  • factors: A list of one or more strings representing the factors that characterize the file-level comparison and are used to calculate the resulting score, e.g.

    "factors": [
          "added",
          "license info added",
          "copyright info added"
        ],
    

The possible values for the factors field are discussed in some detail in DeltaCode Scoring Deltacode Scoring.

  • score: An integer representing the magnitude/importance of the file-level change – the higher the score, the greater the change. For further details about the DeltaCode scoring system, see DeltaCode Scoring Deltacode Scoring.

  • new: A ‘File’ object containing key/value pairs of certain ScanCode-based file attributes (path, licenses, copyrights etc.) for the file in the codebase designated by the user as new. If the Delta object represents the removal of a file (the factors value would be removed), the value of new will be null.

  • old: A ‘File’ object containing key/value pairs of certain ScanCode-based file attributes for the file in the codebase designated by the user as old. If the Delta object represents the addition of a file (the factors value would be added), the value of old will be null.

The JSON structure of a Delta object looks like this::

{
  "factors": [],
  "score": 0,
  "new": {
    "path": "",
    "type": "",
    "name": "",
    "size": 0,
    "sha1": "",
    "original_path": "",
    "licenses": [],
    "copyrights": []
  },
  "old": {
    "path": "",
    "type": "",
    "name": "",
    "size": 0,
    "sha1": "",
    "original_path": "",
    "licenses": [],
    "copyrights": []
  }
}

The File Object

As you saw in the preceding section, the File object has the following JSON structure::

{
  "path": "",
  "type": "",
  "name": "",
  "size": 0,
  "sha1": "",
  "original_path": "",
  "licenses": [],
  "copyrights": []
}

A File object consists of eight key/value pairs:

  • path: – A string identifying the path to the file in question. In processing the ‘new’ and ‘old’ codebases to be compared, DeltaCode may modify the codebases’ respective file paths in order to properly align them for comparison purposes. As a result, a File object’s path value may differ to some extent from its original_path value (see below).

  • type: – A string indicating whether the object is a file or a directory.

  • name: – A string reflecting the name of the file.

  • size: – An integer reflecting the size of the file in KB.

  • sha1: – A string reflecting the file’s sha1 value.

  • original_path: – A string identifying the file’s path as it exists in the codebase, prior to any processing by DeltaCode to modify the path for purposes of comparing the two codebases.

  • licenses: – A list of License objects reflecting all licenses identified by ScanCode as associated with the file. This list can be empty.

  • copyrights: – A list of Copyright objects reflecting all copyrights identified by ScanCode as associated with the file. This list can be empty.

Example of Detailed JSON output

Here is an example of the detailed DeltaCode output in JSON format displaying one Delta object in the deltas key/value pair – in this case, an excerpt from the JSON output of a DeltaCode comparison of zlib-1.2.11 and zlib-1.2.9::

{
  "deltacode_notice": "Generated with DeltaCode and provided on an \"AS IS\" BASIS, WITHOUT WARRANTIES\nOR CONDITIONS OF ANY KIND, either express or implied. No content created from\nDeltaCode should be considered or used as legal advice. Consult an Attorney\nfor any legal advice.\nDeltaCode is a free software codebase-comparison tool from nexB Inc. and others.\nVisit https://github.com/nexB/deltacode/ for support and download.",
  "deltacode_options": {
    "--new": "C:/scans/zlib-1.2.11.json",
    "--old": "C:/scans/zlib-1.2.9.json",
    "--all-delta-types": false
  },
  "deltacode_version": "1.0.0.post49.e3ff7be",
  "deltacode_errors": [],
  "deltas_count": 40,
  "deltas": [
    {
      "factors": [
        "modified"
      ],
      "score": 20,
      "new": {
        "path": "trees.c",
        "type": "file",
        "name": "trees.c",
        "size": 43761,
        "sha1": "ab030a33e399e7284b9ddf9bba64d0dd2730b417",
        "original_path": "zlib-1.2.11/trees.c",
        "licenses": [
          {
            "key": "zlib",
            "score": 60.0,
            "short_name": "ZLIB License",
            "category": "Permissive",
            "owner": "zlib"
          }
        ],
        "copyrights": [
          {
            "statements": [
              "Copyright (c) 1995-2017 Jean-loup Gailly"
            ],
            "holders": [
              "Jean-loup Gailly"
            ]
          }
        ]
      },
      "old": {
        "path": "trees.c",
        "type": "file",
        "name": "trees.c",
        "size": 43774,
        "sha1": "1a554d4edfaecfd377c71b345adb647d15ff7221",
        "original_path": "zlib-1.2.9/trees.c",
        "licenses": [
          {
            "key": "zlib",
            "score": 60.0,
            "short_name": "ZLIB License",
            "category": "Permissive",
            "owner": "zlib"
          }
        ],
        "copyrights": [
          {
            "statements": [
              "Copyright (c) 1995-2016 Jean-loup Gailly"
            ],
            "holders": [
              "Jean-loup Gailly"
            ]
          }
        ]
      }
    },
    [additional Delta objects if any]
  ]
}
CSV

Compared with DeltaCode’s JSON output, the CSV output is relatively simple, comprising the following seven fields as column headers, with each row representing one Delta object:

  • Score – An integer representing the magnitude/importance of the file-level change.

  • Factors – One or more strings – with no comma or other separators – representing the factors that characterize the file-level comparison and are used to calculate the resulting score.

  • Path – A string identifying the file’s path in the ‘new’ codebase unless the Delta object reflects a removed file, in which case the string identifies the file’s path in the ‘old’ codebase. As noted above, this path may vary to some extent from the file’s actual path in its codebase as a result of DeltaCode processing for codebase comparison purposes.

  • Name – A string reflecting the file’s name in the ‘new’ codebase unless the Delta object reflects a removed file, in which case the string reflects the file’s name in the ‘old’ codebase.

  • Type – A string reflecting the file’s type (‘file’ or ‘directory’) in the ‘new’ codebase unless the Delta object reflects a removed file, in which case the string reflects the file’s type in the ‘old’ codebase.

  • Size – An integer reflecting the file’s size in KB in the ‘new’ codebase unless the Delta object reflects a removed file, in which case the string reflects the file’s size in the ‘old’ codebase.

  • Old Path – A string reflecting the file’s path in the ‘old’ codebase if the Delta object reflects a moved file. If the Delta object does not involve a moved file, this field is empty. As with the Path field/column header above, this path may differ to some extent from the file’s actual path in its codebase due to DeltaCode processing for codebase comparison purposes.

Deltacode Scoring

Delta Objects
A File-Level Comparison of Two Codebases

A Delta object represents the file-level comparison (i.e., the “delta”) of two codebases, typically two versions of the same codebase, using ScanCode-generated JSON output files as input for the comparison process.

Based on how the user constructs the command-line input, DeltaCode’s naming convention treats one codebase as the “new” codebase and the other as the “old” codebase::

deltacode -n [path to the 'new' codebase] -o [path to the 'old' codebase] [...]
Basic Scoring

A DeltaCode codebase comparison produces a collection of file-level Delta objects. Depending on the nature of the file-level change between the two codebases, each Delta object is characterized as belonging to one of the categories listed below. Each category has an associated score intended to convey its potential importance – from a license/copyright compliance perspective – to a user’s analysis of the changes between the new and old codebases.

In descending order of importance, the categories are:

  1. added: A file has been added to the new codebase.

  2. modified: The file is contained in both the new and old codebase and has been modified (as reflected, among other things, by a change in the file’s sha1 attribute).

  3. moved: The file is contained in both the new and old codebase and has been moved but not modified.

  4. removed: A file has been removed from the old codebase.

  5. unmodified: The file is contained in both the new and old codebase and has not been modified or moved.

Note

Files are determined to be Moved by looping thru the added and removed Delta objects and checking their sha1 values.

The score of a Delta object characterized as added or modified may be increased based on the detection of license- and/or copyright-related changes. See License Additions and Changes and Copyright Holder Additions and Changes below.

Delta Object Fields and Values

Each Delta object includes the following fields and values:

  • factors: One or more strings representing the factors that characterize the file-level comparison and resulting score, e.g., in JSON format::

    "factors": [
      "added",
      "license info added",
      "copyright info added"
    ],
    
  • score: A number representing the magnitude/importance of the file-level change – the higher the score, the greater the change.

  • new: The ScanCode-based file attributes (path, licenses, copyrights etc.) for the file in the codebase designated by the user as new.

  • old: The ScanCode-based file attributes for the file in the codebase designated by the user as old.

Note that an added Delta object will have a new file but no old file, while a removed Delta object will have an old file but not a new file. In each case, the new and old keys will be present but the value for the missing file will be null.

License Additions and Changes

Certain file-level changes involving the license-related information in a Delta object will increase the object’s score.

  • An added Delta object’s score will be increased:

    • If the new file contains one or more licenses (factors will include license info added).

    • If the the new file contains any of the following Commercial/Copyleft license categories (factors will include, e.g., copyleft added):

      • ‘Commercial’

      • ‘Copyleft’

      • ‘Copyleft Limited’

      • ‘Free Restricted’

      • ‘Patent License’

      • ‘Proprietary Free’

  • A modified Delta object’s score will be increased:

    • If the old file has at least one license and the new file has no licenses (factors will include license info removed).

    • If the old file has no licenses and the new file has at least one license (factors will include license info added).

    • If both the old file and new file have at least one license and the license keys are not identical (e.g., the old file includes an mit license and an apache-2.0 license and the new file includes only an mit license) (factors will include license change).

    • If any of the Commercial/Copyleft license categories listed above are found in the new file but not in the old file (factors will include, e.g., proprietary free added).

Moved, Removed and Unmodified

As noted above in Basic Scoring Basic Scoring, from a license/copyright compliance perspective, the three least significant Delta categories are moved, removed and unmodified.

In the current version of DeltaCode, each of these three categories is assigned a score of 0, with no options to increase that score depending on the content of the Delta object.

However, it is possible that both moved and removed will be assigned some non-zero score in a future version. In particular, removed could be significant from a compliance viewpoint where, for example, the removal of a file results in the removal of a Commercial/Copyleft license obligation.

Development

See CONTRIBUTING.rst for details: https://github.com/nexB/deltacode/blob/develop/CONTRIBUTING.rst

Code layout and conventions

Source code is in src/. Tests are in tests/.

Each test script is named test_XXXX and while we love to use py.test as a test runner, most tests have no dependencies on py.test, only on the unittest module (with the exception of some command line tests that depend on pytest monkeypatching capabilities.

When source or tests need data files, we store these in a data subdirectory.

We use PEP8 conventions with a relaxed line length that can be up to 90’ish characters long when needed to keep the code clear and readable.

We store pre-built bundled native binaries in bin/ sub-directories of each src/ packages. These binaries are organized by OS and architecture. This ensure that DeltaCode works out of the box either using a checkout or a download, without needing a compiler and toolchain to be installed.

We store bundled thirdparty components and libraries in the thirdparty directory. Python libraries are stored as wheels, eventually pre-built if the corresponding wheel is not available in the Pypi repository.

Some of these components may be advanced builds with bug fixes or advanced patches.

We write tests, a lot of tests, thousands of tests. Several tests are data-driven and use data files as test input and sometimes data files as test expectation (in this case using either JSON or YAML files). The tests should pass on Linux 64 bits, Windows 32 and 64 bits and on MacOSX 10.6.8 and up. We maintain two CI loops with Travis (Linux) at https://travis-ci.org/nexB/deltacode and Appveyor (Windows) at https://ci.appveyor.com/project/nexB/deltacode

When finding bugs or adding new features, we add tests. See existing test code for examples.

Running tests

DeltaCode comes with over 130 unit tests to ensure detection accuracy and stability across Linux, Windows and macOS OSes: we kinda love tests, do we?

We use pytest to run the tests: call the py.test script to run the whole test suite. This is installed by pytest which is bundled with a DeltaCode checkout and installed when you run ./configure).

If you are running from a fresh git clone and you run ./configure and then source bin/activate the py.test command will be available in your path.

Alternatively if you have already configured but are not in an activated “virtualenv” the py.test command is available under <root of your checkout>/bin/py.test

(Note: paths here are for POSIX, but mostly the same applies to Windows)

If you have a multiprocessor machine you might want to run the tests in parallel (and faster) For instance: py.test -n4 runs the tests on 4 CPUs. We typically run the tests in verbose mode with py.test -vvs -n4

See also https://docs.pytest.org for details or use the py.test -h command to show the many other options available.

One useful option is to run a select subset of the test functions matching a pattern with the -k option for instance: py.test -vvs -k tcpdump would only run test functions that contain the string “tcpdump” in their name or their class name or module name .

Another useful option after a test run with some failures is to re-run only the failed tests with the --lf option for instance: py.test -vvs --lf would only run only test functions that failed in the previous run.

pip requirements and the configure script

DeltaCode use the configure and configure.bat (and etc/configure.py behind the scenes) scripts to install a virtualenv, install required packaged dependencies as pip requirements and more configure tasks such that DeltaCode can be installed in a self-contained way with no network connectivity required.

DeltaCode requirements and third-party Python libraries

In a somewhat unconventional way, all the required libraries are bundled aka. copied in the repo itself in the thirdparty/ directory. If DeltaCode were only a library it would not make sense. But its is first an application and having a well defined frozen set of dependent packages is important for an app.

The benefit of this approach (combined with the configure script) means that a mere checkout of the repository contains everything needed to run DeltaCode except for a Python interpreter.

Using DeltaCode as a Python library

(Coming Soon) DeltaCode can be used alright as a Python library and is available as as a Python wheel in Pypi and installed with pip install deltacode.

JSON to CSV Conversion

The default output format for a DeltaCode codebase comparison is JSON. If the -j or --json-file option is included in the deltacode command, the output will be written to a .json file at the user-designated location. For example:

deltacode -n [path to the 'new' codebase] -o [path to the 'old' codebase] -j [path to the JSON output file]

We have also created an easy-to-use script for users who want to convert their JSON output to CSV format. Located at etc/scripts/json2csv.py, the conversion can be run with this command template:

python etc/scripts/json2csv.py [path to the JSON input file] [path to the CSV output file]

Release Process

Steps to cut a new release:

run bumpversion with major, minor or patch to bump the version in:

src/deltacode/__init__.py
setup.py
deltacode.ABOUT

Update the CHANGELOG.rst commit changes and push changes to develop:

git commit -m "commit message"
git push --set-upstream origin develop

merge develop branch in master and tag the release.

git checkout master
git merge develop
git tag -a v1.6.1 -m "Release v1.6.1"
git push --set-upstream origin master
git push --set-upstream origin v1.6.1

Draft a new release in GitHub, using the previous release blurb as a base. Highlight new and noteworthy changes from the CHANGELOG.rst.

Run etc/release/release.sh locally.

Upload the release archives created in the dist/ directory to the GitHub release page.

Save the release as a draft. Use the previous release notes to create notes in the same style. Ensure that the link to thirdparty source code is present.

Test the downloads.

Publish the release on GitHub

Then build and publish the released wheel on Pypi. For this you need your own Pypi credentials (and get authorized to publish Pypi release: ask @pombredanne) and you need to have the twine package installed and configured.

Build a .whl with python setup.py bdist_wheel Run twine with twine upload dist/<path to the built wheel> Once uploaded check the published release at https://pypi.python.org/pypi/deltacode/ Then create a new fresh local virtualenv and test the wheel installation with: pip install deltacode

Google Summer of Code 2019 - Final report

Project: Approximately similar file detection in DeltaCode

Arnav Mandal <arnav.mandal1234@gmail.com>

Project Overview

DeltaCode is a tool to compare and report scan differences. It takes JSON files as an input which is the output of ScanCode-toolkit as well. When comparing files, it only uses the exact comparison. By exact comparison, I mean it compares the hash value of the files. The output of DeltaCode is a JSON/CSV file which includes the details of the scan such as delta score, delta count, etc. The goal of this project is to improve the usefulness of the delta by also finding files that are mostly the same (e.g. quasi or near duplicates) vs. files that are completely different. After this project, DeltaCode would be able to detect similar files in a directory approximately.

Requirements of the project
  • Provided two files using ScanCode-toolkit, the new near-duplicate detection should return the distance between the two files.

  • The code should be seamlessly integrated with ScanCode-toolkit. It should be highly configurable by the maintainers.

  • The strictness of near-duplicates should be noted and adjusted by a threshold variable.

The Project
  • Addition of new fingerprint plugin in the ScanCode Toolkit.

  • Implementation and integration of the fingerprint generation algorithm in the ScanCode Toolkit codebase.

  • Implementation of distance finding algorithm between the files and process them further in the DeltaCode codebase.

  • Integration of fingerprint field in the JSON file to compare the deltas and provide them with appropriate scores.

  • Make changes to old unit tests and addition of new unit tests in ScanCode Toolkit as well as DeltaCode.

I have completed all the tasks that were in the scope of this GSoC project.

AboutCode Docs

Welcome to the AboutCode wiki!

If you are interested in the Google Summer of Code 2019, check out this page. Google Summer of Code 2019

If you are interested in the Google Season of Documents 2019, go through this page. Google Season of Docs 2019

Contributor Project Ideas

Welcome to AboutCode!

AboutCode is a project to uncover data … about software code:

  • where does the code come from? which software package?

  • what’s is its license? copyright?

  • is the code secure, maintained, well coded?

All these are questions that are important to find answers to: there are million of free and open source software components available on the web.

Knowing where a software package comes from, if it is vulnerable and what’s its licensing should be a problem of the past such that everyone can safely consume more free and open source software.

Join us to make it so!

Our tools are used to help detect and report the origin and license of source code, packages and binaries as well as discover software and package dependencies, and track security vulnerabilities, bugs and other important software package attributes. This is a suite of command line tools, web-based and API servers and desktop applications.

AboutCode projects are…
  • ScanCode Toolkit a popular command line tool to scan code for licenses, copyrights and packages, used by many organizations and FOSS projects, small and large.

  • AboutCode Manager a JavaScript, Electron-based desktop application to review scan results and document your conclusions

  • AboutCode Toolkit a set of command line tools to document and inventory known packages and licenses and generate attribution docs

  • TraceCode Toolkit: a set of command line tools to find which source code is used to create a compiled binary

  • DeltaCode Toolkit: a new command line tool to compare codebases based on scan and determine if and where there are material differences that affect licensing

  • VulnerableCode Server: a new server-side application to track package vulnerabilities

  • AboutCode Server: a new server-side application to run and organize scans and ABC data (formerly ScanCode server)

  • ConAn: a command line tool to analyze the code in Docker and container images

  • license-expression: a library to parse and render boolean license expression (such as SPDX)

  • Other new tools for source and binary code matching/search and package inventories.

We also work closely with other orgs and projects:

  • purl aka. Package URLs https://github.com/package-url which is an emerging standard to reference software packages of all types.

  • SPDX.org aka. Software Package Data Exchange, a spec to document the origin and licensing of packages

Contact

Join the chat online or by IRC at https://gitter.im/aboutcode-org/discuss introduce yourself and start the discussion!

For personal issues, you can contact the primary org admin directly: @pombredanne and pombredanne@gmail.com

Please ask questions the smart way: http://www.catb.org/~esr/faqs/smart-questions.html

Technology

Discovering the origin of code is a vast topic. We primarily use Python for this and some C/C++ (and eventually Rust) for performance sensitive code and Electron/JavaScript for GUI. We are open to using any other language within reason.

Our domain includes text analysis and processing (for instance for copyrights and licenses), parsing (for package manifest formats), binary analysis (to detect the origin and license of binaries, which source code they come from, etc) as well as web based tools and APIs (to expose the tools and libraries as web services) and low-level data structures for efficient matching (such as Aho- Corasick and other automata)

About your project application

We expect your application to be in the range of 1000 words. Anything less than that will probably not contain enough information for us to determine whether you are the right person for the job. Your proposal should contain at least the following information, plus anything you think is relevant:

  • Your name

  • Title of your proposal

  • Abstract of your proposal

  • Detailed description of your idea including explanation on why is it innovative and what it will contribute

  • hint: explain your data structures and the main processing flows in details.

  • Description of previous work, existing solutions (links to prototypes, bibliography are more than welcome)

  • Mention the details of your academic studies, any previous work, internships

  • Relevant skills that will help you to achieve the goal (programming languages, frameworks)?

  • Any previous open-source projects (or even previous GSoC) you have contributed to and links.

  • Do you plan to have any other commitments during GSoC that may affect your work? Any vacations/holidays? Will you be available full time to work on your project? (Hint: do not bother applying if this is not a serious full time commitment)

Join the chat online or by IRC at https://gitter.im/aboutcode-org/discuss introduce yourself and start the discussion!

You need to understand something about open source licensing or package managers or code and binaries static analysis or low level data structures. The best way to demonstrate your capability would be to submit a small patch ahead of the project selection for an existing issue or a new issue.

We will always consider and prefer a project submissions where you have submitted a patch over any otherr submission without a patch.

Our Project ideas

Here is a list of candidate project ideas for your consideration. Your own ideas are welcomed too! Please chat about them to increase your chances of success!

Note that there is NO specific order in this list!

AboutCode data server

This project is to futher and evolve the ScanCode server (was started last year as a 2017 GSoC project) and rename it as the AboutCode server.

The features of this updated server would be:

VulnerableCode Package security vulnerability data feed (and scanner)

This project is to futher and evolve the VulnerableCode server and and software package vulnerabilities data aggregator.

VulnerableCode was started last year as a 2017 GSoC project. Its goal is to collect and aggregate vulnerabilities data and provide semi-automatic correlation. In the end it should provide the basis to report vulnerabilities alerts found in packages identified by ScanCode.

This is not trivial as there are several gaps in the CVE data and how they relate to packages as they are detected by ScanCode or else.

The features and TODO for this updated server would be:

  • Aggregate more and new packages vulnerabilities feeds,

  • Automating correlation: add smart relationship detection to infer new relatiosnhips between available packages and vulnerabilities from mining the graph of existing relations.

  • Create a ScanCode plugin to report vulnerabilities with detected packages using this data.

  • Integrate API lookup on the server withe the AboutCode Manager UI

  • Create a UI and model for community curation of vulnerability to package mappings, correlations and enhancements.

Integrate the license expression library in ScanCode (Python) and AboutCode Manager (JScript)

In GSoC 2017, this Python library was ported to JavaScript using Transcrypt.

The goal of this project is to add support for license expressions in multiple projects and evolve the license expression library as needed:

High volume matching automatons and data structures

MatchCode will provide ways to efficiently match actual code against a large stored indexes of open source code.

To enable this, we need to research and create efficient and compact data structures that are specialized for the type of data we lookup. Given the volume to consider (typically multi billion values indexed) there are special considerations to have compact and memory efficient dedicated structures (rather than using a general purpose DB or Key/value pair store) that includes looking at automata, and memory mapping. This types of data structures should be implemented in Rust as a preference (though C/C++ is OK) and include Python bindings.

There are several areas to research and implement:

  • A data structure to match efficiently a batch of fix-width checksums (e.g. SHA1) against a large index of such checksums, where each checksum points to one or more files or packages. A possible direction is to use finite state transducers or specialized B-tree indexes. Since when a codebase is being matched there can be millions of lokkups to do, the batch matching is preferred.

  • A data structure to match efficiently a batch of fix-width byte strings (e.g. LSH) against a large index of such LSH within a fixed hamming distance, where each points to one or more files or packages. A possible direction is to use finite state transducers (possibly weighted), specialized B-tree indexes or multiple hash-like on-disk tables.

  • A memory-mapped Aho-Corasick automaton to build large batch tree matchers. Available Aho-Corasick automaton may not have a Python binding or may not allow memory-mapping (like pyahocorasick we use in ScanCode). The volume of files we want to handle requires to reuse, extend or create aspecialized tree/paths matching automatons that can handle eventually billions of nodes and are larger than the available RAM. A possible direction is to use finite state transducers (possibly weighted).

  • Feature hashing research: we deal with manyt “features” and hashing to limit the number and size of the each features seems to be a valuable thing. The goal is to research feature hashing with short hashes (15, 16 and 32 bits) and evaluate if this leads to acceptable fasle-positive and loss of accuracy in the context of the data structures mentioned above.

Then using these data structures, the project should create a system for matching code as a Python-based server exposing a simple API. This is a green field project.

ScanCode scan deduction

The goal of this project is to take existing scan and match results and infer summaries and deduction at a higher level, such as the licensing or origin of a whole directory tree. This should be implemented as a set of ScanCode plugins

Transparent archive extraction in ScanCode

ScanCode archive extraction is currently done with a separate command line invocation. The goal of this project is to integrate archive extraction transparently into the ScanCode scan loop. This would be using the new plugins architecture.

Port ScanCode to Python 3

ScanCode runs only on Python 2.7 today. The goal of this project is to port ScanCode to support both Python 2 and Python 3.

Automated Docker, containers and VM images static package analysis

The goal of this project is to further the Conan container static analysis tool to effectively support proper inventory of installed packages without running the containers.

This includes determining which packages are installed in Docker layers for RPMs, Debian or Alpine Linux. And this woudl eventually require the integration of ScanCode.

Static analysis of binaries for build tracing in TraceCode

TraceCode does system call tracing only today.

  • The primary goal of this project is to do the same using symbol, debug symbol or string matching to accomplish something similar using static analysis.

  • This project also would cover updating TraceCode to use the Click comamnd line toolkit (like for ScanCode).

  • Finally thsi project should improve the tracing of the lifecycle of file descriptors in TraceCode build. We need to improve how TraceCode does system call tracing by improving the way we track open/close file descriptors in the trace to reconstruct the lifecycle of a traced file.

  • Tech

    • Python, Linux

  • URLS

  • Mentor

Create Linux distro packages for ScanCode

The goal of this project is to ensure that we have proper packages for Linux distros for ScanCode.

The first step is to debundle pre-built binaries that exist in ScanCode such that they come either from system-packages or pre-built Python wheels. This covers libarchive, libmagic and a few other native libraries.

The next step is to ensure that all the dependencies from ScanCode are also available as distro packages.

The last step is to create proper distro packages for RPM, Debian, Nix and GUIX, Alpine, Arch and Gentoo and also an AppImage.org package as well as a proper Docker image and eventually submit these package to the distros.

As a bonus, the same could then be done for AboutCode toolkit and TraceCode.

This requires a good understanding of packaging and Python.

Package URL implementations in many programming languages

We have a purl implmentation in Python, Go and possibly Java today.

The goal of this project is to create multiple parsers and builders in several programming languages:

DependentCode: a mostly universal Package dependencies resolver

The goal of this project is to create a tool for mostly universal package dependencies resolution using a SAT solver that should leverage the detected packages from ScanCode and the Package URLs and could provide a good enough way to resolve package dependencies for many system and application package formats. This is a green field project.

Google Season of Docs 2019

AboutCode has been accepted as a participant in the Google Season of Documents in 2019 as a mentoring org, and is looking for people with technical writing skills. This page contains information for technical writers and anyone else interested in helping.

AboutCode is a family of FOSS projects to uncover data about software code:

  • Where does the code come from? which software package?

  • What is its license? copyright?

  • Is the code secure, maintained, well coded?

All these questions are important, and are relevant to millions of free and open source software components available on the web for reuse. The answers are critical to ensure that everyone can safely consume free and open source software.

Join us to make it so!

Our tools are used to help detect and report the origin and license of source code, packages and binaries as well as to discover software and package dependencies, and in the future track security vulnerabilities, bugs and other important software package attributes. This is a suite of command line tools, web-based and API servers and desktop applications.

List of AboutCode projects

Note that the AboutCode focus for GSOD 2019 is on ScanCode Toolkit and ScanCode Workbench, although proposals to improve the documents of other AboutCode projects are welcome.

  • ScanCode Toolkit is a popular command line tool to scan code for licenses, copyrights and packages, used by many organizations and FOSS projects, small and large.

  • Scancode Workbench (formerly AboutCode Manager) is a JavaScript, Electron-based desktop application to review scan results and document your origin and license conclusions.

  • Other AboutCode projects are described at https://www.aboutcode.org and https://github.com/nexB/aboutcode

    We also work closely with, contribute to and have co-started several other orgs and projects:

  • Package URL is an emerging standard to reference software packages of all types with simple, readable and concise URLs.

  • SPDX is the Software Package Data Exchange, a specification to document the origin and licensing of software packages.

  • ClearlyDefined is a project to review FOSS software and help FOSS projects to improve their licensing and documentation clarity.

Contact

Join the chat online or by IRC at https://gitter.im/aboutcode-org/discuss Introduce yourself and start the discussion!

For personal issues, you can contact the primary org admin directly: @pombredanne and pombredanne@gmail.com

or the GSOD coordinator directly at dmclark@nexb.com

Please ask questions the smart way: http://www.catb.org/~esr/faqs/smart-questions.html

Technology

We primarily use Python (and some C/C++) for code analysis. We use Electron/JavaScript for GUI.

Our domain includes text analysis and processing (for instance for copyright and license detection), parsing (for package manifest formats), binary analysis (to detect the origin and license of binaries, which source code they come from, etc.) as well as web based tools and APIs (to expose the tools and libraries as web services) and low-level data structures for efficient matching (such as Aho-Corasick and other automata).

Our documentation is provided in text files that support the help function of our command line tools. We also have begun to provide documentation in the Wiki section of some AboutCode projects.

Technical Writing Skills Needed

Incoming technical writers will need the following skills:

  • Ability to install and configure open source code from GitHub.

  • Ability to understand and run programs from the command line in a terminal window.

  • Familiarity with the four document functions described at https://www.divio.com/blog/documentation/

  • Ability to create and edit wiki pages with multiple markdown languages.

  • An interest in FOSS licensing and software code and origin analysis.

We are happy to help you get up to speed, and the more you are able to demonstrate ability and skills in advance, the more likely we are to choose your application!

About your project application

Your application should be in the range of 1000 words, and should contain the following information, plus anything else that you think is relevant:

  • Your name and contact details

  • Title of your proposal

  • Abstract of your proposal

  • Description of your idea including an explanation of what it will contribute to the project, such as the software development life cycle requirements that you expect to help with the documentation improvements.

  • Description of previous work, existing solutions, open-source projects, preferably with links.

  • Details of your academic studies and any previous internships.

  • Descriptions of your relevant skills.

  • Do you plan to have any other commitments during GSOD that may affect your work? Any vacations/holidays? Will you be available full time to work on your project? Please apply only if this is a serious full time commitment during the GSOD time frame.

Join the chat online or by IRC at https://gitter.im/aboutcode-org/discuss Introduce yourself and start the discussion!

An excellent, competitive way to demonstrate your capability would be to submit a documentation improvement to an AboutCode project, especially to ScanCode Toolkit or ScanCode Workbench.

You can pick any project idea from the list below. You can also submit Your Documentation Project ideas.

Our Documentation Project ideas

Here is a list of candidate project ideas for your consideration, organized by documentation function: Tutorial , How-To , Reference , Discussion.

Note that the AboutCode focus for GSOD 2019 is on ScanCode Toolkit and ScanCode Workbench, although proposals to improve the documents of other AboutCode projects are welcome.

Your Documentation Project ideas are welcome too! Please chat about them to increase your chances of success!

Tutorial ideas
Scan a Codebase and Analyze the Results

Provide specific instructions to guide a new user to:

How-To ideas
How To Get the License Clarity Score of a Package

Explain the recommended scancode-toolkit options to get a license clarity score.

How To Discover Licensing Issues in a Software Project
Reference ideas
ScanCode Output Formats

Explain the various ScanCode output formats and their business purposes.

Discussion ideas
Integrating ScanCode into a Software Development Lifecycle

Discuss options and techniques to integrate ScanCode into a software development lifecycle workflow:

Your Documentation Project ideas

Download and install ScanCode Toolkit and ScanCode Workbench and try them out. For example, you may try scanning an open source software package in a technology with which you are familiar. What are the documentation weak points?

  • Is it difficult to get started? A Tutorial document opportunity.

  • Is it difficult to accomplish a specific objective? A How-To document opportunity.

  • Are the capabilities of the tool too mysterious? Do you want to know more about what you can do with it? A Reference document opportunity.

  • Do you feel that you need to understand its concepts better in order to use it and trust it? Do you want to know more about how the code scanning actually works? A Discussion document opportunity.

Feel free to propose and describe your own documentation ideas.

Mentoring

We welcome new mentors to help with the program. We require some understanding of the project domain to join as a mentor. Contact the team on Gitter at https://gitter.im/aboutcode-org/discuss

Google Summer of Code 2017

AboutCode Logo

Welcome to AboutCode! This year AboutCode is a mentoring Organization for the Google Summer of Code 2017 edition.

AboutCode is a project to uncover data … about software code:

  • where does it come from?

  • what is its license? copyright?

  • is it secure, maintained, well coded?

All these are questions that are important to find answers to when there are million of free and open source software components available on the web.

Where software comes from and what is its license should be a problem of the past, such that everyone can safely consume more free and open source software. Come and join us to make it so!

Our tools are used to help detect and report the origin and license of source code, packages and binaries, as well as discover software and package dependencies, track vulnerabilities, bugs and other important software component attributes.

Contact

Subscribe to the mailing list at https://lists.sourceforge.net/lists/listinfo/aboutcode-discuss and introduce yourself and start the discussion! The mailing list is usually the better option to avoid timezone gaps.

The list archive have also plenty of interesting information. Someone may have asked your question before. Search and browse the archives at https://sourceforge.net/p/aboutcode/mailman/aboutcode-discuss/ !

For short chats, you can also join the #aboutcode IRC channel on Freenode or the Gitter channel at https://gitter.im/aboutcode-org/discuss

For personal issues, you can contact the org admin directly: @pombredanne and pombredanne@gmail.com

Please ask questions the smart way: http://www.catb.org/~esr/faqs/smart-questions.html

Technology

Discovering the origin of code is a vast topic. We primarily use Python for this and some C/C++ and JavaScript, but we are open to using any other language within reason.

Our domain includes text analysis and processing (for instance for copyrights and licenses), parsing (for package manifest formats), binary analysis (to detect the origin and license of binaries, which source code they come from, etc) as well as web based tools and APIs (to expose the tools and libraries as web services).

About your project application

We expect your application to be in the range of 1000 words. Anything less than that will probably not contain enough information for us to determine whether you are the right person for the job. Your proposal should contain at least the following information, plus anything you think is relevant:

  • Your name

  • Title of your proposal

  • Abstract of your proposal

  • Detailed description of your idea including explanation on why is it innovative and what it will contribute

    • hint: explain your data structures and the main processing flows in details.

  • Description of previous work, existing solutions (links to prototypes, bibliography are more than welcome)

  • Mention the details of your academic studies, any previous work, internships

  • Relevant skills that will help you to achieve the goal (programming languages, frameworks)?

  • Any previous open-source projects (or even previous GSoC) you have contributed to and links.

  • Do you plan to have any other commitments during GSoC that may affect your work? Any vacations/holidays? Will you be available full time to work on your project? (Hint: do not bother applying if this is not a serious full time commitment)

Subscribe to the mailing list at https://lists.sourceforge.net/lists/listinfo/aboutcode-discuss or join the #aboutcode IRC channel on Freenode and introduce yourself and start the discussion!

You need to understand something about open source licensing or package managers or code and binaries static analysis. The best way to demonstrate your capability would be to submit a small patch ahead of the project selection for an existing issue or a new issue.

Project ideas
ScanCode live scan server :

This project is to use ScanCode as a library in a web and REST API application that allows you to scan code on demand by entering a URL and then store the scan results. It could also be made available as a Travis or Github integration to scan on commit with webhooks. Bonus feature is to scan based on a received tweet of similar IRC or IM integration.

Package security vulnerability data feed (and scanner) :

The end goal for this project is to build on existing projects to match packages identified by ScanCode to existing vulnerability alerts. This is not trivial as there are several gaps in the CVE data and how they relate to packages as they are detected by ScanCode or else. This is a green field project.

The key points to tackle are:

  1. create the tools to build a free and open source structured and curate security feed

    • the aggregation of packages vulnerabilities feeds in a common and structured model (CVE, distro trackers, etc),

    • the aggregation of additional security data (CWE, CPE, and more) in that model,

    • the correlation of the different data items, creating accurate relationships and matching of actual package identifiers to vulnerabilities,

    • an architecture for community curation of vulnerabilities, correlation and enhancement of the data.

  2. as a side bonus, build the tools in ScanCode to match detected packages to this feed. Note there is no FOSS tool and DB that does all of this today (only proprietary solutions such as vfeed or vulndb).

Port the Python license expression library to JScript and prepare and publish an NPM package:

Use automated code translation (for JS) for the port. Add license expression support to AboutCodeMgr with this library. As a bonus, create a web server app and API service to parse and normalize ScanCode and SPDX license expressions either in Python or JavaScript.

MatchCode :

Create a system for matching code using checksums and fingerprints against a repository of checksums and fingerprints. Create a basic repository for storing these fingerprints and expose a basic API. Create a client that can collect fingerprints on code and get matches using API calls to this repository or package manager APIs (Maven, Pypi, etc), or search engines APIs such as searchcode.com, debsources, or Github or Bitbucket commit hash searches/API or the SoftwareHeritage.org API.

ScanCode scan deduction :

The goal of this project is to take existing scan and match results and infer summaries and deduction at a higher level, such as the licensing of a whole directory tree.

DeltaCode :

A new tool to help determine at a high level if the licensing for two codebases or versions of code has changed, and if so how. This is NOT a generic diff tool that identifies all codebase differences, rather it focuses on changes in licensing based on differences between ScanCode files.

Support full JSON and ABCD formats in AttributeCode
Transparent archive extraction in ScanCode :

ScanCode archive extraction is currently done with a separate command line invocation. The goal of this project is to integrate archive extraction transparently into the ScanCode scan loop.

Automated docker and VM images static package analysis :

to determine which packages are installed in Docker layers for RPMs, Debian or Alpine Linux. This is for the conan Docker image analysis tool.

Plugin architecture for ScanCode :

Create ScanCode plugins for outputs to multiple formats (CSV, JSON, SPDX, Debian Copyright)

Static analysis of binaries for build tracing in TraceCode :

TraceCode does system call tracing. The goal of this project is to do the same using symbol, debug symbol or string matching to accomplish something similar,

Better support tracing the lifecycle of file descriptors in TraceCode build :

TraceCode does system call tracing. The goal of this project is to improve the way we track open/close file descriptors in the trace to reconstruct the life of a file.

Create Debian and RPM packages for ScanCode, AttributeCode and TraceCode.

Consider also including an AppImage.org package. If you think this may not fill in a full three months project, consider also adding some extras such as submitting the packages to Debian and Fedora.

AboutCode Manager test suite and Ci :

Create an extensive test suite for the Electron app and setup the CI to run unit, integration and smoke tests on Ci for Windows, Linux and Mac.

DependentCode :

Create a tool for mostly universal package dependencies resolution.

FetchCode :

Create a tool for mostly universal package and code download from VCS, web, ftp, etc.

Google Summer of Code 2018

See Contributor Project Ideas.

Google Summer of Code 2019

AboutCode is participating in the Google Summer of Code in 2019 as a mentoring org. This page contain all the information for students and anyone else interested in helping.

AboutCode is a family of FOSS projects to uncover data … about software code:

  • where does the code come from? which software package?

  • what is its license? copyright?

  • is the code secure, maintained, well coded?

All these are questions that are important to answer: there are million of free and open source software components available on the web for reuse.

Knowing where a software package comes from, what is its license and if it is vulnerable and what’s its licensing should be a problem of the past such that everyone can safely consume more free and open source software.

Join us to make it so!

Our tools are used to help detect and report the origin and license of source code, packages and binaries as well as discover software and package dependencies, and in the future track security vulnerabilities, bugs and other important software package attributes. This is a suite of command line tools, web-based and API servers and desktop applications.

AboutCode projects are…
  • ScanCode Toolkit is a popular command line tool to scan code for licenses, copyrights and packages, used by many organizations and FOSS projects, small and large.

  • Scancode Workbench (formerly AboutCode Manager) is a JavaScript, Electron-based desktop application to review scan results and document your origin and license conclusions.

  • AboutCode Toolkit is a command line tool to document and inventory known packages and licenses and generate attribution docs, typically using the results of analyzed and reviewed scans.

  • TraceCode Toolkit is a command line tool to find which source code file is used to create a compiled binary and trace and graph builds.

  • DeltaCode is a command line tool to compare scans and determine if and where there are material differences that affect licensing.

  • ConAn : a command line tool to analyze the code in Docker and container images

  • VulnerableCode : an emerging server-side application to collect and track known package vulnerabilities.

  • license-expression : a library to parse, analyze, simplify and render boolean license expression (such as SPDX)

We also work closely, contribute and co-started several other orgs and projects:

  • Package URL which is an emerging standard to reference software packages of all types with simple, readable and concise URLs.

  • SPDX aka. Software Package Data Exchange, a spec to document the origin and licensing of packages.

  • ClearlyDefined to review and help FOSS projects improve their licensing and documentation clarity.

Contact

Join the chat online or by IRC at https://gitter.im/aboutcode-org/discuss Introduce yourself and start the discussion!

For personal issues, you can contact the primary org admin directly: @pombredanne and pombredanne@gmail.com

Please ask questions the smart way: http://www.catb.org/~esr/faqs/smart-questions.html

Technology

Discovering the origin of code is a vast topic. We primarily use Python for this and some C/C++ (and eventually some Rust and Go) for performance sensitive code and Electron/JavaScript for GUI.

Our domain includes text analysis and processing (for instance for copyrights and licenses detection), parsing (for package manifest formats), binary analysis (to detect the origin and license of binaries, which source code they come from, etc.) as well as web based tools and APIs (to expose the tools and libraries as web services) and low-level data structures for efficient matching (such as Aho- Corasick and other automata).

Skills

Incoming students will need the following skills:

  • Intermediate to strong Python programming. For some projects, strong C/C++ and/or Rust is needed too.

  • Familiarity with git as a version control system

  • Ability to set up your own development environment

  • An interest in FOSS licensing and software code and origin analysis

We are happy to help you get up to speed, but the more you are able to demonstrate ability and skills in advance, the more likely we are to choose your application!

About your project application

We expect your application to be in the range of 1000 words. Anything less than that will probably not contain enough information for us to determine whether you are the right person for the job. Your proposal should contain at least the following information, plus anything you think is relevant:

  • Your name

  • Title of your proposal

  • Abstract of your proposal

  • Detailed description of your idea including explanation on why is it innovative and what it will contribute to the project

    • hint: explain your data structures and you planned main processing flows in details.

  • Description of previous work, existing solutions (links to prototypes, bibliography are more than welcome)

  • Mention the details of your academic studies, any previous work, internships

  • Relevant skills that will help you to achieve the goal (programming languages, frameworks)?

  • Any previous open-source projects (or even previous GSoC) you have contributed to and links.

  • Do you plan to have any other commitments during GSoC that may affect your work? Any vacations/holidays? Will you be available full time to work on your project? (Hint: do not bother applying if this is not a serious full time commitment during the GSoC time frame)

Join the chat online or by IRC at https://gitter.im/aboutcode-org/discuss introduce yourself and start the discussion!

The best way to demonstrate your capability would be to submit a small patch ahead of the project selection for an existing issue or a new issue.

We will always consider and prefer a project submissions where you have submitted a patch over any other submission without a patch.

You can pick any project idea from the list below. If you have other ideas that are not in this list, contact the team first to make sure it makes sense.

Our Project ideas

Here is a list of candidate project ideas for your consideration. Your own ideas are welcomed too! Please chat about them to increase your chances of success!

ScanCode ideas
Port ScanCode to Python 3

ScanCode runs only on Python 2.7 today. The goal of this project is to port ScanCode to support both Python 2 and Python 3.

Improve Programming language detection and classification in ScanCode

ScanCode programming language detection is not as accurate as it could be and this is important to get this right to drive further automation. We also need to automatically classify each file in facets when possible.

The goal of this project is to improve the quality of programming language detection (which is using only Pygments today and could use another tool, e.g. some Bayesian classifier like Github linguist, enry ?). And to create and implement a flexible framework of rules to automate assigning files to facets which could use some machine learning and classifier.

Improve License detection accuracy and speed in ScanCode

ScanCode license detection is using a sophisticated set of techniques base on automatons, inverted indexes and sequence matching. There are some cases where license detection accuracy could be improved (such as when scanning long notices). Other improvements would be welcomed to ensure the proper detected license text is collected in an improved way. Dealing with large files sometimes trigger a timeout and handling these cases would be needed too (by breaking files in chunks). The detection speed could also be improved possibly by porting some critical code sections to C or Rust and that would need extensive profiling.

Improve ScanCode scan summarization and deduction

The goal of this project is to take existing scan results and infer summaries and perform some deduction of license and origin at a higher level, such as the licensing or origin of a whole directory tree. The ultimate goal is to automate the conclusion of a license and origin based on scans. This could include using statistics and machine learning techniques such as classifiers where relevant and efficient.

This should be implemented as a set of ScanCode plugins and further the summarycode module plugins.

Create Linux distros and FreeBSD packages for ScanCode.

The goal of this project is to ensure that we have proper packages for Linux distros and FreeBSD for ScanCode.

The first step is to debundle pre-built binaries that exist in ScanCode such that they come either from system-packages or pre-built Python wheels. This covers libarchive, libmagic and a few other native libraries and has been recently completed.

The next step is to ensure that all the dependencies from ScanCode are also available as distro packages.

The last step is to create proper distro packages for RPM, Debian, FreeBSD and as many other distros such as Nix and GUIX, Alpine, Arch and Gentoo (and possibly also AppImage.org packages and Docker images) and submit these package to the distros.

As a bonus, the same could then be done for AboutCode toolkit and TraceCode.

This requires a good understanding of packaging and Python.

DeltaCode projects
Approximately Similar file detection in DeltaCode

DeltaCode is a tool to compare and report scan differences. When comparing files, it only uses exact comparison. The goal of this project is to improve the usefulness of the delta by also finding files that are mostly the same (e.g. quasi or nrea duplicates) vs. files that are completely different. Then the DeltaCode comparison core should be updated accordingly to detect and report material changes to scans (such as new, update or removed licenses, origins and packages) when changes are also meterial in the code files (e.g. such that small changes may be ignored)

TraceCode projects
Static analysis of binaries for build tracing in TraceCode

TraceCode does system call tracing only today. The primary goal of this project is to create a tool that provides the same results as the strace-based tracing but would be using using ELF symbols, DWARF debug symbols, signatures or string matching to determine when and how a source code file is built in a binary using only a static analysis. The primary target should be Linux executables, though the code should be designed to be extensible to Windows PE and macOS Dylib and exes.

Improve dynamic build tracing in TraceCode

TraceCode does system call tracing and relies on kernel-space system calls and in particular tracing file descriptors. This project should improve the tracing of the lifecycle of file descriptors when tracing a build with strace. We need to improve how TraceCode does system call tracing by improving the way we track open/close file descriptors in the trace to reconstruct the lifecycle of a traced file. This requires to understand and dive if the essence of system calls and file lifecycle from a kernel point of view and build datastructure and code to reconstruct user-space file activity from the kernel traces along a timeline.

This project also would cover updating TraceCode to use the Click command line toolkit (like for ScanCode).

Conan and Other projects
Containers and VM images static package analysis

The goal of this project is to further the Conan container static analysis tool to effectively support proper inventory of installed packages without running the containers.

This includes determining which packages are installed in Docker layers for RPMs, Debian or Alpine Linux in a static way. And this may eventually require the integration with ScanCode.

DependentCode: a mostly universal Package dependencies resolver

The goal of this project is to create a tool for a universal package dependencies resolution using a SAT solver that should leverage the detected packages from ScanCode and the Package URLs and could provide a good enough way to resolve package dependencies for many system and application package formats. This is a green field project.

VulnerableCode Package security vulnerability correlated data feed

This project is to futher and evolve the VulnerableCode server and software package vulnerabilities data aggregator.

VulnerableCode was started as a GSoC project in 2017. Its goal is to collect, aggregate and correlate vulnerabilities data and provide semi-automatic correlation. In the end it should provide the basis to report vulnerabilities alerts found in packages identified by ScanCode.

This is not trivial as there are several gaps in the CVE data and how they relate to packages as they are detected by ScanCode or else.

The features and TODO for this updated server would be:

High volume matching automatons and data structures

Finding similar code is a way to detect the origin of code against an index of open source code.

To enable this, we need to research and create efficient and compact data structures that are specialized for the type of data we lookup. Given the volume to consider (typically multi billion values indexed) there are special considerations to have compact and memory efficient dedicated structures (rather than using a general purpose DB or Key/value pair store) that includes looking at automata, and memory mapping. This types of data structures should be implemented in Rust as a preference (though C/C++ is OK) and include Python bindings.

There are several areas to research and prototype such as:

  • A data structure to match efficiently a batch of fix-width checksums (e.g. SHA1) against a large index of such checksums, where each checksum points to one or more files or packages. A possible direction is to use finite state transducers, specialized B-tree indexes, blomm-like filters. Since when a codebase is being matched there can be millions of lookups to do, the batch matching is preferred.

  • A data structure to match efficiently a batch of fix-width byte strings (e.g. LSH) against a large index of such LSH within a fixed hamming distance, where each points to one or more files or packages. A possible direction is to use finite state transducers (possibly weighted), specialized B-tree indexes or multiple hash-like on-disk tables.

  • A memory-mapped Aho-Corasick automaton to build large batch tree matchers. Available Aho-Corasick automatons may not have a Python binding or may not allow memory-mapping (like pyahocorasick we use in ScanCode). The volume of files we want to handle requires to reuse, extend or create specialized tree/paths matching automatons that can handle eventually billions of nodes and are larger than the available memory. A possible direction is to use finite state transducers (possibly weighted).

  • Feature hashing research: we deal with many “features” and hashing to limit the number and size of the each features seems to be a valuable thing. The goal is to research the validaty of feature hashing with short hashes (15, 16 and 32 bits) and evaluate if this leads to acceptable false-positive and loss of accuracy in the context of the data structures mentioned above.

Then using these data structures, the project should create a system for matching code as a Python-based server exposing a simple API. This is a green field project.

Mentoring

We welcome new mentors to help with the program and require some good unerstanding of the project codebase and domain to join as a mentor. Contact the team on Gitter.

Writing good Commit Messages

What is good commit message? We want to avoid this: https://xkcd.com/1296/

Read these articles:

The main style points are these:

Subject:

  • Add a issue number at the end of the line when available as in “#234”

  • Limit the subject line to 50 characters

  • Capitalize the subject line

  • Do not end the subject line with a period

  • Use the imperative mood in the subject line: you are giving orders to the codebase

Body:

  • Separate subject from body with a blank line

  • Wrap the body at 72 characters. Use only spaces for formatting, not tabs.

  • Use the body to explain what and why vs. how

  • use bullets with a * if needed

  • Add a Reported-by: if needed

  • End your message with a Signed-off-by: prefixed by a blank line

Other comments:

We like to suffix the subject line with an issue number. If this was a trivial change it may not have one though. If it had one a you would use #156 as a suffix to the first line.

We like to tell why the commit is there and use an imperative style, like if you were giving an order to the codebase with your commit:

e.g rather than : Minor fix for unnecessary operations. may be Remove unnecessary operations #123 or:

Remove unnecessary operations #123

    * If the ts timestamp does not exist, do not compare with old one.

You need to add a signoff to your commit. So the final message would have looked like this:

Remove unnecessary operations #123

    * If the ts timestamp does not exist, do not compare with old one.

Signed-off-by: Philippe Ombredanne <pombredanne@nexb.com>

AboutCode-Toolkit Documentation

AboutCode Toolkit

Build and tests status

Branch

Linux/macOS

Windows

Master

Linux Master branch tests status

Windows Master branch tests status

Develop

Linux Develop branch tests status

Windows Develop branch tests status

The AboutCode Toolkit and ABOUT files provide a simple way to document the origin, license, usage and other important or interesting information about third-party software components that you use in your project.

You start by storing ABOUT files (a small YAML formatted text file with field/value pairs) side-by-side with each of the third-party software components you use. Each ABOUT file documents origin and license for one software. For more information on the ABOUT file format, visit http://www.dejacode.org There are many examples of ABOUT files (valid or invalid) in the testdata/ directory of the whole repository.

The current version of the AboutCode Toolkit can read these ABOUT files so that you can collect and validate the inventory of third-party components that you use.

In addition, this tool is able to generate attribution notices and identify redistributable source code used in your project to help you comply with open source licenses conditions.

This version of the AboutCode Toolkit follows the ABOUT specification version 3.0 at: https://github.com/nexB/aboutcode-toolkit/blob/develop/SPECIFICATION.rst

REQUIREMENTS

The AboutCode Toolkit is tested with Python 2.7 and 3.6 on Linux, Mac and Windows. You will need to install a Python interpreter if you do not have one already installed.

On Linux and Mac, Python is typically pre-installed. To verify which version may be pre-installed, open a terminal and type:

python –version

On Windows or Mac, you can download the latest Python here:

https://www.python.org/downloads/

Download the .msi installer for Windows or the .dmg archive for Mac. Open and run the installer using all the default options.

INSTALLATION
Checkout or download and extract the AboutCode Toolkit from:

https://github.com/nexB/aboutcode-toolkit/

To install all the needed dependencies in a virtualenv, run (on posix):

source configure

or on windows:

configure

REFERENCE

See https://github.com/nexB/aboutcode-toolkit/blob/master/REFERENCE.rst for reference on aboutcode-toolkit usage.

TESTS and DEVELOPMENT
To install all the needed development dependencies, run (on posix):

source configure etc/conf/dev

or on windows:

configure etc/conf/dev

To verify that everything works fine you can run the test suite with:

py.test

HELP and SUPPORT

If you have a question or find a bug, enter a ticket at:

For issues, you can use:

SOURCE CODE
The AboutCode Toolkit is available through GitHub. For the latest version visit:

https://github.com/nexB/aboutcode-toolkit

HACKING

We accept pull requests provided under the same license as this tool. You agree to the http://developercertificate.org/

LICENSE

The AboutCode Toolkit is released under the Apache 2.0 license. See (of course) the about.ABOUT file for details.

Reference

about

Syntax

about [OPTIONS] [COMMANDS]

Options:

--version    Show the version and exit.
--help       Show this message and exit.

Commands:

attrib     LOCATION: directory, OUTPUT: output file
check      LOCATION: directory
gen        LOCATION: input file, OUTPUT: directory
inventory  LOCATION: directory, OUTPUT: csv file
attrib

Syntax

about attrib [OPTIONS] LOCATION OUTPUT

LOCATION: Path to an ABOUT file or a directory containing ABOUT files.
OUTPUT: Path to output file to write the attribution to.

Options:

--inventory PATH            Path to an inventory file.
--mapping                   Use for mapping between the input keys and the ABOUT field.
                            names - mapping.config
--mapping-file              Use a custom mapping file with mapping between input
                            keys and ABOUT field names.
--template PATH             Path to a custom attribution template.
--vartext TEXT              Variable texts to the attribution template
--verbose                   Show all the errors and warning.
-q, --quiet                 Do not print any error/warning.
-h, --help                  Show this message and exit.
Purpose

Generate an attribution file which contains the all license information from the LOCATION along with the license text.

Assume the following:

'/home/about_files/'** contains all the ABOUT files [LOCATION]
'/home/attribution/attribution.html' is the user's output path [OUTPUT]
'/home/project/component_list.csv' is the inventory that user want to be generated
$ about attrib /home/about_files/ /home/attribution/attribution.html
Options
--inventory

    This option allows you to define which ABOUT files should be used for attribution generation.
    For instance,
    '/home/project/component_list.csv' is the inventory that user want to be generated

$ about attrib --inventory /home/project/component_list.csv LOCATION OUTPUT

--mapping

    See mapping.config for details

--mapping-file

    Same behavior as `--mapping` but with custom mapping file

$ about attrib --mapping-file CUSTOM_MAPPING_FILE_PATH LOCATION OUTPUT

--template

    This option allows you to use your own template for attribution generation.
    For instance, if you have a custom template located at:
    /home/custom_template/template.html

$ about attrib --template /home/custom_template/template.html LOCATION OUTPUT

--vartext

    This option allow you to pass variable texts to the attribution template

$ about attrib --vartext "title=Attribution Notice" --vartext "header=Product 101" LOCATION OUTPUT

    Users can use the following in the template to get the vartext:
    {{ vartext_dict['title'] }}
    {{ vartext_dict['header'] }}

--verbose

    This option tells the tool to show all errors found.
    The default behavior will only show 'CRITICAL', 'ERROR', and 'WARNING'
The following data are passed to jinja2 and, therefore, can be used for a custom template:
  • about object: the about objects

  • common_licenses: a common license keys list in licenses.py

  • license_key_and_context: a dictionary list with license_key as a key and license text as the value

  • license_file_name_and_key: a dictionary list with license file name as a key and license key as the value

  • license_key_to_license_name: a dictionary list with license key as a key and license file name as the value

check

Syntax

about check [OPTIONS] LOCATION

LOCATION: Path to an ABOUT file or a directory with ABOUT files.

Options:

--verbose                Show all the errors and warning
-h, --help               Show this message and exit.
Purpose

Validating ABOUT files at LOCATION.

Options
--verbose

    This option tells the tool to show all errors found.
    The default behavior will only show 'CRITICAL', 'ERROR', and 'WARNING'

$ about check --verbose /home/project/about_files/
gen

Syntax

about gen [OPTIONS] LOCATION OUTPUT

LOCATION: Path to a JSON or CSV inventory file.
OUTPUT: Path to a directory where ABOUT files are generated.

Options:

--fetch-license KEY                 Fetch licenses text from a DejaCode API. and
                                    create <license>.LICENSE side-by-side
                                    with the generated .ABOUT file using data
                                    fetched from a DejaCode License Library. The
                                    following additional options are required:

                                    api_url - URL to the DejaCode License Library
                                    API endpoint

                                    api_key - DejaCode API key
                                    Example syntax:

                                    about gen --fetch-license 'api_url' 'api_key'
--license-notice-text-location PATH Copy the 'license_file' from the directory to
                                    the generated location.
--mapping                           Use for mapping between the input keys and
                                    the ABOUT field names - mapping.config
--mapping-file                      Use a custom mapping file with mapping between input
                                    keys and ABOUT field names.
--verbose                           Show all the errors and warning.
-q, --quiet                         Do not print any error/warning.
-h, --help                          Show this message and exit.
Purpose

Given an inventory of ABOUT files at location, generate ABOUT files in base directory.

Options
--fetch-license

    Fetch licenses text from a DejaCode API. and create <license>.LICENSE side-by-side
    with the generated .ABOUT file using data fetched from a DejaCode License Library.

    This option requires 2 parameters:
        api_url - URL to the DJE License Library
        api_key - Hash key to authenticate yourself in the API.

    In addition, the input needs to have the 'license_expression' field.
    (Please contact nexB to get the api_* value to use for this feature)

$ about gen --fetch-license 'api_url' 'api_key' LOCATION OUTPUT

--license-notice-text-location

    Copy the license files and notice files to the generated location based on the
    'license_file' and 'notice_file' value in the input from the directory

    For instance,
    the directory, /home/licenses_notices/, contains all the licenses and notices that you want:
    /home/license/apache2.LICENSE
    /home/license/jquery.js.NOTICE

$ about gen --license-notice-text-location /home/licenses_notices/ LOCATION OUTPUT

--mapping

    See mapping.config for details

--mapping-file

    Same behavior as `--mapping` but with custom mapping file

$ about attrib --mapping-file CUSTOM_MAPPING_FILE_PATH LOCATION OUTPUT

--verbose

    This option tells the tool to show all errors found.
    The default behavior will only show 'CRITICAL', 'ERROR', and 'WARNING'
inventory

Syntax

about inventory [OPTIONS] LOCATION OUTPUT

LOCATION: Path to an ABOUT file or a directory with ABOUT files.
OUTPUT: Path to the JSON or CSV inventory file to create.

Options:

--filter TEXT               Filter for the output inventory.
-f, --format [json|csv]     Set OUTPUT file format.  [default: csv]
--mapping                   Use file mapping.config to collect the defined not supported fields in ABOUT files.
--mapping-file              Use a custom mapping file with mapping between input
                            keys and ABOUT field names.
--mapping-output FILE       Use a custom mapping file with mapping between
                            ABOUT field names and output keys
--verbose                   Show all the errors and warning.
-q, --quiet                 Do not print any error/warning.
-h, --help                  Show this message and exit.
Purpose

Collect a JSON or CSV inventory of components from ABOUT files.

Options
-filter TEXT

    Filter for the output inventory.

$ about inventory --filter "license_expression=gpl-2.0" LOCATION OUTPUT

The above command will only inventory the ABOUT files which have the "license_expression: gpl-2.0"

-f, --format [json|csv]

    Set OUTPUT file format.  [default: csv]

$ about inventory -f json LOCATION OUTPUT

--mapping

    See mapping.config for details

--mapping-file

    Same behavior as `--mapping` but with custom mapping file

$ about inventory --mapping-file CUSTOM_MAPPING_FILE_PATH LOCATION OUTPUT

--mapping-output

    Same behavior as `--mapping-file` but with custom mapping file
    In the custom mapping file, the left side is the custom key name where
    the right side is the ABOUT field name. For instance,
    Component: name

    The "Component" is a custom field name for the output
    The "name" is one of the defaul ABOUT field name that user want to convert

$ about inventory --mapping-output CUSTOM_MAPPING_FILE_PATH LOCATION OUTPUT

--verbose

    This option tells the tool to show all errors found.
    The default behavior will only show 'CRITICAL', 'ERROR', and 'WARNING'
Special Notes
Multiple licenses support format

The multiple licenses support format for CSV files are separated by line break

about_resource

name

license_key

license_file

test.tar.xz

test

apache-2.0
mit
apache-2.0.LICENSE
mit.LICENSE

The multiple licenses support format for ABOUT files are by “grouping” with the keyword “licenses”

about_resource: test.tar.xz
name: test
licenses:
    -   key: apache 2.0
        name: apache-2.0.LICENSE
    -   key: mit
        name: mit.LICENSE

ABOUT File Specification v3.1.2

Purpose

An ABOUT file provides a simple way to document the provenance (origin and license) and other important or interesting information about a software component. An ABOUT file is a small YAML formatted text file stored in the codebase side-by-side with the software component file or archive that it documents. No modification of the documented software is needed.

The ABOUT format is plain text with field name/value pairs separated by a colon. It is easy to read and create by hand and is designed first for humans, rather than machines. The format is well-defined and structured just enough to make it easy to process with software as well. It contains enough information to fulfill key license requirements such as creating credits or attribution notices, collecting redistributable source code, or providing information about new versions of a software component.

Getting Started

A simple and valid ABOUT file named httpd.ABOUT may look like this:

about_resource: httpd-2.4.3.tar.gz
name: Apache HTTP Server
version: 2.4.3
homepage_url: http://httpd.apache.org
download_url: http://archive.apache.org/dist/httpd/httpd-2.4.3.tar.gz
license_expression: apache-2.0
licenses:
    -   key: apache-2.0
    -   file: apache-2.0.LICENSE
notice_file: httpd.NOTICE
copyright: Copyright (c) 2012 The Apache Software Foundation.

The meaning of this ABOUT file is:

  • The file “httpd-2.4.3.tar.gz” is stored in the same directory and side-by-side with the ABOUT file “httpd.ABOUT” that documents it.

  • The name of this component is “Apache HTTP Server” with version “2.4.3”.

  • The home URL for this component is http://httpd.apache.org

  • The file “httpd-2.4.3.tar.gz” was originally downloaded from http://archive.apache.org/dist/httpd/httpd-2.4.3.tar.gz

  • In the same directory, “apache-2.0.LICENSE” and “httpd.NOTICE” are files that contain respectively the license text and the notice text for this component.

  • This component is licensed under “apache-2.0”

Specification

An ABOUT file is an ASCII YAML formatted text file. Note that while Unicode characters are not supported in an ABOUT file proper, external files can contain UTF-8 Unicode.

ABOUT file name

An ABOUT file name can use a limited set of characters and is suffixed with a “.ABOUT” extension using any combination of uppercase and lowercase characters.

A file name can contain only these US-ASCII characters:

  • digits from 0 to 9

  • uppercase and lowercase letters from A to Z

  • the following symbols: “_”, “-“, “+”, “.”, “(“, “)”, “~”, “[“, “]”, “{“, “}”

  • The case of a file name is not significant. On case-sensitive file systems (such as on Linux), a tool must report an error if two ABOUT files stored in the same directory have the same lowercase file name. This is to ensure that ABOUT files can be used across file systems. The convention is to use a lowercase file name and an uppercase ABOUT extension.

Lines of text

An ABOUT file contains lines of US-ASCII text. Lines contain field names/values pairs. The standard line ending is the LF character. The line ending characters can be any LF, CR or CR/LF and tools must normalize line endings to LF when processing an ABOUT file. Empty lines and lines containing only white spaces that are not part of a field value continuation are ignored. Empty lines are commonly used to improve the readability of an ABOUT file.

Field name

A field name can contain only these US-ASCII characters:

  • digits from 0 to 9

  • uppercase and lowercase letters from A to Z

  • the “_” underscore sign.

  • Field names are not case sensitive. For example, “HOMEPAGE_URL” and “HomePage_url” represent the same field name.

  • A field name must start at the beginning of a new line. It can be followed by one or more spaces that must be ignored. These spaces are commonly used to improve the readability of an ABOUT file.

Field value

The field value is separated from the field name by a “:” colon. The “:” colon can be followed by one or more spaces that must be ignored. This also applies to trailing white spaces: they must be ignored.

The field value is composed of one or more lines of plain US-ASCII printable text.

When a field value is a long string, additional continuation lines must start with at least one space. In this case, the first space of an additional continuation line is ignored and should be removed from the field value by tools.

For instance:

description: This is a long description for a
 software component that additional continuation line is used.


  When a field value contains more than one line of text,  a 'literal block'
  (using |) is need.

For instance:

description: |
    This is a long description for a software component that spans
    multiple lines with arbitrary line breaks.

    This text contains multiple lines.
Fields are mandatory or optional

As defined in this specification, a field can be mandatory or optional. Tools must report an error for missing mandatory fields.

Extension and ignored fields

An ignored field is a field with a name that is not defined in this specification. Custom extension fields are also supported and must be processed by tools as ignored fields unless a certain tool can process a certain extension field.

Fields validation

When processing an ABOUT file, tools must report a warning or error if a field is invalid. A field can be invalid for several reasons, such as invalid field name syntax or invalid content. Tools should report additional validation error details. The validation process should check that each field name is syntactically correct and that fields contain correct values according to its concise, common sense definition in this specification. For certain fields, additional and specific validations are relevant such as checksum verification, URL validation, path resolution and verification, and so forth. Tools should report a warning for ignored fields.

Fields order and multiple occurrences

The field order does not matter. Multiple occurrences of a field name is not supported.

The tool processing an ABOUT file or CSV/JSON input will issue an error when a field name occurs more than once in the input file (as for any other ignored field).

Field referencing a file

The actual value of some fields may be contained in another file. This is useful for long texts or to reference a common text in multiple ABOUT files such as a common license text. In this case the field name is suffixed with “_file” and the field value must be a path pointing to the file that contains the actual value of the field. This path must be a POSIX path relative to the path of the ABOUT file. The file content must be UTF-8-encoded text. This is in contrast with field values contained directly in an ABOUT file that must be US-ASCII- encoded text and allows to support non-ASCII text content.

For example, the full license text for a component is often stored in a separate file named COPYING:

licenses:
    -   file: linux.COPYING

In this example, the README file is stored in a doc directory, one directory above the ABOUT file directory, using a relative POSIX path:

licenses:
    -   file: ../docs/ruby.README
Field referencing a URL

The value of a field may reference URLs such as a homepage or a download. In this case the field name is suffixed with “_url” and the field value must be a valid absolute URL starting with ftp://, http:// or https://. URLs are informational and the content they may reference is ignored. For example, a download URL is referenced this way:

download_url: http://www.kernel.org/pub/linux/kernel/v3.0/linux-3.4.20.tar.bz2
Flag fields

Flag fields have a “true” or “false” value. True, T, Yes or Y , x must be interpreted as “true” in any case combination. False, F, No or N must be interpreted as “false” in any case combination.

Referencing the file or directory documented by an ABOUT file

An ABOUT file documents one file or directory. The mandatory “about_resource” field reference the documented file or directory. The value of the “about_resource” field is the name or path of the referenced file or directory.

A tool processing an ABOUT file must report an error if this field is missing.

By convention, an ABOUT file is often stored in the same directory side-by-side to the file or directory that it documents, but this is not mandatory.

For example, a file named django.ABOUT contains the following field to document the django-1.2.3.tar.gz archive stored in the same directory:

about_resource: django-1.2.3.tar.gz

In this example, the ABOUT file documents a whole sub-directory:

about_resource: linux-kernel-2.6.23

In this example, the ABOUT file documents the current directory, using a “.” period to reference it:

about_resource: .
Other Mandatory fields

When a tool processes an ABOUT file, it must issue an error if these mandatory field are missing.

  • about_resource: The resource this file referencing to.

  • name: Component name.

Optional Information fields
  • version: Component or package version. A component or package usually has a version, such as a revision number or hash from a version control system (for a snapshot checked out from VCS such as Subversion or Git). If not available, the version should be the date the component was provisioned, in an ISO date format such as ‘YYYY-MM-DD’.

  • spec_version: The version of the ABOUT file format specification used for this file. This is provided as a hint to readers and tools in order to support future versions of this specification.

  • description: Component description, as a short text.

  • download_url: A direct URL to download the original file or archive documented by this ABOUT file.

  • homepage_url: URL to the homepage for this component.

  • changelog_file: Changelog file for the component.

  • notes: Notes and comments about the component.

Optional Owner and Author fields
  • owner: The name of the primary organization or person(s) that owns or provides the component.

  • owner_url: URL to the homepage for the owner.

  • contact: Contact information (such as an email address or physical address) for the component owner.

  • author: Name of the organization(s) or person(s) that authored the component.

  • author_file: Author file for the component.

Optional Licensing fields
  • copyright: Copyright statement for the component.

  • notice_file: Legal notice or credits for the component.

  • notice_url: URL to a legal notice for the component.

  • license_file: License file that applies to the component. For example, the name of a license file such as LICENSE or COPYING file extracted from a downloaded archive.

  • license_url: URL to the license text for the component.

  • license_expression: The license expression that apply to the component. You can separate each identifier using ” or ” and ” and ” to document the relationship between multiple license identifiers, such as a choice among multiple licenses.

  • license_name: The license short name for the license.

  • license_key: The license key(s) for the component.

Optional Boolean flag fields
  • redistribute: Set this flag to yes if the component license requires source code redistribution. Defaults to no when absent.

  • attribute: Set this flag to yes if the component license requires publishing an attribution or credit notice. Defaults to no when absent.

  • track_changes: Set this flag to yes if the component license requires tracking changes made to a the component. Defaults to no when absent.

  • modified: Set this flag to yes if the component has been modified. Defaults to no when absent.

  • internal_use_only: Set this flag to yes if the component is used internal only. Defaults to no when absent.

Optional Extension fields

You can create extension fields by prefixing them with a short prefix to distinguish these from the standard fields. You should provide documentation for these extensions and create or extend existing tools to support these extensions. Other tools must ignore these extensions.

Optional Extension fields to reference files stored in a version control system (VCS)

These fields provide a simple way to reference files stored in a version control system. There are many VCS tools such as CVS, Subversion, Git, ClearCase and GNU Arch. Accurate addressing of a file or directory revision in each tool in a uniform way may not be possible. Some tools may require access control via user/password or certificate and this information should not be stored in an ABOUT file. This extension defines the ‘vcs’ field extension prefix and a few common fields to handle the diversity of ways that VCS tools reference files and directories under version control:

  • vcs_tool: VCS tool such as git, svn, cvs, etc.

  • vcs_repository: Typically a URL or some other identifier used by a VCS tool to point to a repository such as an SVN or Git repository URL.

  • vcs_path: Path used by a particular VCS tool to point to a file, directory or module inside a repository.

  • vcs_tag: tag name or path used by a particular VCS tool.

  • vcs_branch: branch name or path used by a particular VCS tool.

  • vcs_revision: revision identifier such as a revision hash or version number.

Some examples for using the vcs_* extension fields include:

vcs_tool: svn
vcs_repository: http://svn.code.sf.net/p/inkscape/code/inkscape_project/
vcs_path: trunk/inkscape_planet/
vcs_revision: 22886

or:

vcs_tool: git
vcs_repository: git://git.kernel.org/pub/scm/linux/kernel/git/stable/linux-stable.git
vcs_path: tools/lib/traceevent
vcs_revision: b59958d90b3e75a3b66cd311661535f94f5be4d1
Optional Extension fields for checksums

These fields support checksums (such as SHA1 and MD5)commonly provided with downloaded archives to verify their integrity. A tool can optionally use these to verify the integrity of a file documented by an ABOUT file.

  • checksum_md5: MD5 for the file documented by this ABOUT file in the “about_resource” field.

  • checksum_sha1: SHA1 for the file documented by this ABOUT file in the “about_resource” field.

Some examples:

checksum_md5: f30b9c173b1f19cf42ffa44f78e4b96c

AboutCode Data : ABCD

Summary

ABCD is an abbreviation for ABout Code Data. The AboutCode Data goal is to provide a simple, standardized and extensible way to document data about software code such that:

  • It is a common way to exchange data about code between any nexB tools by import and export.

  • It becomes the preferred way to exchange data between nexB tools and other tools.

  • It could become a valuable structure to exchange data between any tools concerned with data about software.

ABCD is technology and programming language neutral, preferring JSON or YAML document formats.

ABC Data is structured around a few basic objects: Products, Components, Packages, Files, Parties and Licenses. It is extensible to other specific or future object types.

Objects have “attributes” that are simple name/value pairs. A value can be either a plain value or another object or a list of objects and attributes.

ABC Data is minimally specified by design: only a few basic objects and attributes are documented with conventions to name and structure data and how to define relationships between objects. There is only a small reference dictionary for some well known attributes documented here.

The planned benefit for tools using ABC Data is simplified data exchange and integration between multiple best-of-breed tools.

Context

There is currently no easy way to describe information about code and software in a simple and standardized way. There have been many efforts to provide this data in a more structured way such as:

  • SPDX (focused on packages and licenses),

  • DOAP (focused on projects),

  • The original ABOUT metafile format, and

  • The many different software package metadata formats (Maven, NPM, RPM, Deb, etc).

These data structures are fragmented and generally too purpose- or technology-specific.

Recently there have been efforts to collect and expose more data such as:

  • libraries.io (a catalog of packages, AGPL-licensed) and dependencyci.com its companion commercial service,

  • versioneye.com (a catalog of package versions updates, now MIT-licensed),

  • softwarearchive.org (an effort to build an all-encompassing software source code archive),

  • sources.debian.net (a Debian-focused code and metadata search facility),

  • searchcode.com (an add-supported source code search engine exposing some metadata)

  • appstream (a cross-distro effort to normalize desktop package metadata access to Linux desktops https://www.freedesktop.org/software/appstream/docs/).

These efforts are all useful, but they do not address how you can consistently exchange data about code in a user-centric and technology-neutral, normalized way.

Why does this matter? Software and code are everywhere. FLOSS code is exploding with millions of components and packages. The data about this code is out there somewhere but getting it is often too difficult. This is a problem of data normalization, aggregation and exchange.

Whether you consume or produce software, accessing and creating normalized data about your code and the code you use should be made easier such that:

  • You can efficiently make code selection and re-use decisions,

  • You can discover what is in your code, and

  • You can continuously track updates, bugs, licenses, liveliness, quality and security attributes of the code you use or consider using.

With the notable exceptions of SPDX and the earlier versions of the ABOUT format, available data formats about software have been designed first for a specific technology (e.g. Linux distros) or programming language (e.g. maven, npm, etc.) and documentation of code provenance and related attributes has been secondary and minimal. In most cases, the primary focus has been to provide first comprehensive support for package installation, dependency resolution or package building and provenance and licensing information is often treated with lesser details.

ABCD: the AboutCode Data structure

ABCD is an abbreviation for ABout Code Data. The goal is to provide a simple, standardized and extensible way to document things about software code.

In contrast with other approaches, the AboutCode Data structure is focused on providing data that is useful to users first and is not limited to software package data only. AboutCode Data need not be as strictly specified as traditional package manager data formats because its purpose is not to drive a software build, package creation or software installation nor is it to compute the resolution of dependencies. It only provides information (metadata) about the code.

The vision for the ABC Data structure is to provide a common way to exchange data about code between all nexB tools, such that these tools can all import and export data about code seamlessly (TraceCode, ScanCode, AboutCode Manager, AttributeCode, upcoming MineCode, etc.). The ABCD structure should also be the preferred way to exchange data about code between nexB tools and other tools. We may create small adapters to convert other data formats in and out of the ABCD structure and encourage other tool authors to natively support ABC Data, though the main focus is on our tools.

The ABCD structure is technology and programming language neutral and designed so that the parties exchanging data about code can do so reliably with some minimal conventions; and that the data is easily processed by machines and not hard to read by humans.

ABC Data is structured around “objects”. Objects have “attributes” that are simple name/value pairs. A value can be either a plain value or another object or a list of nested objects and attributes.

ABC Data is organized around:

  • a few known object types,

  • simple conventions to create lists of objects and describe object relationships,

  • simple conventions to create attributes as name/value pairs, and

  • a small dictionary or vocabulary of well-known attribute names that have a common definition across all tools.

ABC Data is “under-specified” by design: only a few essential objects and attributes are documented here with the conventions on how to structure the ABC Data.

Basic objects describing data about code

At the top level we have these main object types:

  • Product(s): a software product, application or system such as a Cost Accounting application.

  • Component(s): a software component, such as the PostgreSQL 9 database system, usually a significant or major version

  • Package(s): a set of files that comprise a Component as used, such as a postgresql-9.4.5-linux-x86.zip archive. The version is exact and specific.

  • File(s): any file and directory identified by a path, such as a binary package or a source code directory or file.

And these secondary, important but less prominent object types:

  • Party(ies): a person or an organization. An organization can be a project, formally or informally organized, a company, a department within a company, etc. A Party typically has contact information (such as an email or physical address or home url). A Party may have defaults that apply to much of its software (for an org that creates software) such as a default Apache license for Apache Foundation projects. Parties often relate to other objects through a role relationship such as owner, author, maintainer, etc.

  • License(s): information about the license of code. A License typically has a name, text and additional categories. (tags or attributes).

Each of these objects has a few identifying attributes and eventually many tool- or application-specific data attributes. Each tool defines and documents the attributes they can handle and care for. When some agreement is reached on the definition of new attributes or objects, the ABCD dictionary may be updated accordingly with new objects types such as for software security, quality or other interesting aspects.

Objects are interrelated with other objects. Objects can relate to each other via a reference using identifiers pointing to other objects or via an embedded list of objects. The nature of the relationship between two objects can also be specified with additional attributes as needed.

Here are typical relationships between objects:

image1

Here is an example of relationships for a simple Widget product:

image2

Tools can define any custom objects and some used more commonly may be promoted to be documented here over time.

Attribute Names and Values

By convention, a tool receiving ABC Data should process only the data it knows and should ignore unknown attributes or objects. This is important to allow the data structure to evolve and provide some forward and backward compatibility. When an ABCD payload contains data elements that a receiver does not know about, the receiver should still be able to process the known objects and attributes.

  • Attributes are name/value pairs.

  • Attribute names are always strings, not numbers, not booleans, not any other data format. In these strings, leading and trailing white spaces (spaces, tabs, line returns, etc) are not significant and can be safely ignored or removed.

  • Attribute values are one of the standard JSON types: string, number, boolean or null. In strings, leading and trailing white spaces (spaces, tabs, line returns, etc) are not significant and can be safely ignored or removed.

  • Self-explicit names should be used rather than obscure names or abbreviations: names should be self-explicit and self-evident.

Except for the data organization conventions described here and the use of the well-known object and attribute names, nothing is mandatory in the ABCD format. This means that even partial, incomplete or sketchy data about code can be transferred in this format.

The meaning of well known object names such as Product, Component, Package, File, Party and License is defined in this document.

Name conventions

  • Names are strings composed ONLY of ASCII letters, numbers or underscores. Names cannot start with a number. Names cannot contain spaces nor other punctuation, not even a dot or period.

  • Names are NOT case sensitive: upper or lowercase does not matter and the standard is to use lowercase. It is a mistake to use upper or mixed case but this is something a parser receiving ABC Data should recover from nicely by converting the names to lowercase.

  • Names are made of English words: there is no provision currently for non-English names. Tools that deal with multilingual content may define their own conventions to provide content in other languages. ABCD may add one of these conventions in the future.

  • Parser implementation can be smarter and gentler: For names, anything that is not ASCII or number or underscore can be accepted by a parser and could be replaced by an underscore, including a starting digit if any. Or a parser may provide a warning if there is an unknown name that is very close to a well known name. Or a parser may accept CamelCase and transform names to underscore_case and perform another transformation to conventional ABC Data.

  • Names are singular or plural: When a name refers to more than one item, the name of the field is plural and the value is a list of values. For instance “url” and “urls”.

  • Top level known objects are ALWAYS plural and stored in lists: “parties” or “files” or “products” or “components”. This makes it easier to write tools because the top level types are always lists, even when there is a single object in that list.

  • A value must not be used as a name: in an attribute name/value pair, the name is always a name, not a value and every value must have a name.

  • For instance, this JSON snippet would not be correct where a URL is used as a name:

    {"http://someurl.com": "this is the home URL"}
    
  • Use rather this form to specify a name for the URL attribute:

    {"url": "http://someurl.com", "note": "this is the home URL"}
    
  • But this would be correct when using a list of plain values where “urls” is plural:

    {"urls": ["http://someurl.com", "http://someurl2.com"]}
    
  • An attribute names without a value is not needed. Only names with values are needed, and attributes without values can be omitted: each tool may do what it wants for these cases. For instance it may be handy to provide all attributes even if not defined in an API payload. But when serializing data as YAML, meant for human editing, including all empty values may not help with reading and processing the YAML text. An undefined attribute without a set value should be assigned with the null JSON value: this has the same meaning as if the attribute was not specified and absent from the payload. If you want to specify that an attribute has an empty value and does not have a value (as opposed to have an unknown value) use an empty string instead.

  • Avoid abbreviated names, with some exceptions. Names should always be fully spelled out except for:

    • url: uniform resource locator

    • uri: uniform resource identifier

    • urn: uniform resource name

    • vcs: version control system

    • uuid: universally unique identifier, used for uuid4 string https://tools.ietf.org/html/rfc4122.html

    • id: identifier

    • info: information

    • os: operating system

    • arch: architecture

  • For some common names we use the common compound form such as:

    • codebase: and not code_base

    • filename: and not file_name

    • homepage: and not home_page

Well known attribute names include:

  • name: the name of a product, component, license or package.

  • version: the version of a product, component, package.

  • description: description text.

  • type: some type information about an object. For instance, a File type could be: directory, file or link.

  • keywords: a list of keywords about an object. For example, the keywords of a component used to “tag” a component.

  • path: the value is the path to a file or directory, either absolute or relative and using the POSIX convention (a forward slash as separator). For Windows paths, replace backslash with forward slashes. Directories should end with a slash in a canonical form.

  • key: the value is some key string, slug-like, case-insensitive and composed only of ASCII letters and digits, dash, dot and underscore. No white spaces. For example: org.apache.maven-parent

  • role: the value describes the role of a Party in a relationship with other objects. For instance a Party may be the “owner” or “author” of a Component or Package.

  • uuid: a uuid4 string https://tools.ietf.org/html/rfc4122.html

  • algorithms for checksums: to store checksums we use a name/value pairs where the name is an algorithm such as sha1 and the value is a checksum in hexadecimal such as “sha1”: “asasa231212” . The value is the standard/default string created by command line tools such as sha1sum. Supported algorithms may evolve over time. Common checksums include md5, sha1, sha256, sha512.

  • notes: some text notes. This is an exception to the singular/plural rule for names: notes is a single text field and not a list.

As the usage of the ABCD structure matures, more well known names will be documented in a vocabulary.

Value conventions

  • Attribute values are one of the standard JSON types: string, number, boolean or null. In strings, leading and trailing white spaces (spaces, tabs, line returns, etc) are not significant and can be safely ignored or removed.

  • To represent a date/time use the ISO format such as 2016-08-15 defaulting to UTC time zone if the time zone is not specified in the date/time stamp.

  • All string values are UTF-8 encoded.

Well known name prefixes or suffixes can be used to provide a type hint for the value type or meaning:

  • xxx_count, xxx_number, xxx_level: the value is an integer number. Example: results_count or curation_level

  • date_xxx or xxx_date: the value is a date/time stamp in ISO format such as 2016-08-16 (See https://www.ietf.org/rfc/rfc3339.txt ). Examples: last_modified_date, date_created

  • xxx_url: the value is a URL for web http(s) or ftp url that points to an existing valid web resource (that could possibly no longer exist on the web). Example: homepage_url or api_url

  • xxx_uri: the value is a URI typically used as an identifier that may not point to an existing web resource. Example: git://github.com/nexb/scancode-toolkit

  • xxx_file or xxx_path: the value is a file path. This can come handy for external files such as a license file. Example: notice_file

  • xxx_filename: the value is a file name. Example: notice_filename

  • xxx_text: the value is a long text. This is only a hint that it may be large and may span multiple lines. Example: notice_text

  • xxx_line: such as start_line and end_line: the value is a line number. The first line number is 1.

  • xxx_status: such as configuration_status. Indicates that the value is about some status.

  • xxx_name: such as short_name. Indicates that the value is a name. Commonly used for long_name, short_name. The bare name shout be preferred for the obvious and most common way an object is named.

  • xxx_flag, is_xxx, has_xxx: such as is_license_notice. Indicates that the string value is a boolean.

Object identifiers

We like objects to be identifiable. There is a natural way to identify and name most objects: for instance, the full name of a person or organization or the name and version of a Component or Package or the path to a File, are all natural identifiers to an object.

However, natural names are not always enough to fully identify an object and may need extra context to reference an object unambiguously. There could be several persons or organizations with the same name at a different address. Or the foo-1.4 Package could be available as a public RubyGem and also as an NPM; or a private Python package foo-1.4 has been created by a company and is also available on Pypi. Or the “foo” Package is the name of a Linux Package, an NPM and a Ruby Package but these three packages are for unrelated components.

Hence each object may need several attributes to be fully identifiable.

For example, public package managers ensure that a name is unique within the confines of a source. “logging” is the unique name of a single Sourceforge project at https://sourceforge.net/projects/logging/. “logging” is the unique name of an Apache project at the Apache Foundation http://logging.apache.org/.

Yet, these two names point to completely different software. In most cases, providing information about the “source” where an identifier is guaranteed to be unique is enough to ensure proper identification. This “source” is easily identified by its internet source name, and an internet source name is guaranteed to be unique globally. The “source” of identifiers is not mandatory but it is strongly encouraged to use as an attribute to provide good unique identifiers. Still, tools exchanging ABC Data must be able to exchange under-specified and partially identified data and may sometimes rely on comparing many attributes of two objects to decide if they are the same.

The minimal way to identify top level objects is the combination of a “source” and a unique identifier within this source. The source can be implicit when two parties are exchanging data privately or explicit using the “source” attribute.

Within a source, we use the most obvious and natural identifies for an object. For example:

  • For Products, Components and Packages we can use their name and version.

  • For Files we use a path of a file or directory, possibly relative to a package or a product codebase; or a checksum of a file or archive such as a sha1.

  • For Parties, we use a name possibly supplemented with a URL or email.

  • For all object types we can use a “universally unique id” or UUID-4 (https://tools.ietf.org/html/rfc4122.html)

  • For all object types, we can use a key, which is a slug-like string identifier such as a license key.

  • For all object types, we can use a URN (https://en.wikipedia.org/wiki/Uniform_resource_name) Tools may also define their own URNs, namespaces and names such as a DejaCode urn is, urn:dje:component:16fusb:1.0

Beyond direct identification, an object may have several alternative identifiers, aka “external references”. For instance a Package may have different names and slightly different versions in the Linux, Debian or Fedora distros and a Pypi Package with yet another name where all these Packages are for the same Component and the same code. Or a Party such as the Eclipse Foundation may be named differently in DejaCode and the NVD CPEs.

To support these cases, the “external_reference(s)” attribute can be used where needed in any object to reference one or more external identifiers and what is the source for this identifier (note: “external” is really a matter of point of view of who owns or produces the ABC Data).  An attribute with name suffix of “xxx_reference” may also be used to provide a simpler external reference, such as “approval_reference”.

For example, this ABC Data could describe the external id of Party to a CPE and to TechnoPedia (here in a YAML format):

parties:
  - name: Apache Foundation
    homepage_url: http://apache.org
    type: organization
    external_references:
        - source: nvd.nist.gov
          identifier: apache
        - source: technopedia.com
          identifier: Apache Foundation (The)
        - source: googlecode.com
          identifier: apache-foundation

Other identifiers may also be used, as needed by some tools, such as in hyperlinked APIs.

Organizing data and relationships

Describing relationships between objects is essential in AboutCode Data. There are two ways to describe these relationships: by referencing or by embedding objects.

When using a reference, you relate objects by providing identifiers to these objects and may provide additional object details in separate lists. When embedding, you include not only the reference but also the related object details in another object data. This could include all data about an object or a subset as needed.

For example, this components list embeds a list of two packages.

Note: “components” is always a list, even when it has a single component:

{"components": [{
    "source": "http://apache.org",
    "name": "Apache httpd",
    "version": "2.3",
    "packages": [
        {"name": "httpd",
         "version": "2.3.4",
         "download_url": "http://apache.org/dist/httpd/httpd-2.3.4.zip",
         "sha1": "acbf23256361abcdf",
         "size": 3267,
         "filename": "httpd-2.3.4.zip"
        },

        {"name": "httpd",
         "version": "2.3.5",
         "download_url": "http://apache.org/dist/httpd/httpd-2.3.5.tar.gz",
         "sha1": "ac8823256361adfcdf",
         "size": 33267,
         "filename": "httpd-2.3.5.tar.gz"
        }
    ]
}]}

In this example, the component list references two packages that are listed separately and uses the checksum as package identifiers for the reference. This data is strictly equivalent to the previous example but using a different layout. When all the data is provided, the effect of embedding or referencing objects results in the same data, just organized differently:

{"components": [{
    "source": "http://apache.org",
    "name": "Apache httpd",
    "version": "2.3",
    "packages": [
        {"sha1": "aacbf23256361abcdf"},
        {"sha1": "ac8823256361adfcdf"}
    ]
}],

"packages": [
    {"name": "httpd", "version": "2.3.4",
     "download_url":
     "http://apache.org/dist/httpd/httpd-2.3.4.zip",
     "sha1": "acbf23256361abcdf", "size": 23267, "filename": "httpd-2.3.4.zip"},

    {"name": "httpd", "version": "2.3.5",
     "download_url": "http://apache.org/dist/httpd/httpd-2.3.5.tar.gz",
     "sha1": "ac8823256361adfcdf", "size": 33267, "filename": "httpd-2.3.5.tar.gz"}
]}

In this third example the packages are referencing one component instead. That component is always wrapped in a components list. The component detail data is not provided. The details may be available elsewhere in a tool that tracks components:

"packages": [
    {"name": "httpd", "version": "2.3.4",
     "download_url": "http://apache.org/dist/httpd/httpd-2.3.4.zip",
     "sha1": "acbf23256361abcdf", "size": 23267, "filename": "httpd-2.3.4.zip",
     "components": [
        {"source": "http://apache.org", "name": "Apache httpd", "version": "2.3"}
     ]
    },

    {"name": "httpd", "version": "2.3.5",
     "download_url":"http://apache.org/dist/httpd/httpd-2.3.5.tar.gz",
     "sha1": "ac8823256361adfcdf", "size": 33267, "filename": "httpd-2.3.5.tar.gz",
     "components": [
        {"source": "http://apache.org", "name": "Apache httpd", "version": "2.3"}
     ]
    }
]

Relationships can be documented with this approach in different ways. Typically when the primary concern is about a Product, then the Product object may embed data about its Components. When the primary concern is Packages, they may embed or reference Products or Components or files. For example:

  • A tool may prefer to provide data with products or components as top level objects. The components used in a Product are naturally embedded in the products.

  • A tool concerned more with files, will provide files as top level objects and may embed package details when they are found for a file or directory path.

  • Another tool may focus on packages and provide packages first with component references and possibly embedded files. A matching tool may provide packages first and reference matched files. The file paths of a package are naturally embedded in the package, though using references may help keep the data simpler when there is a large volume of files.

  • A tool that generates attribution documentation may focus first on components and second on licenses or packages references.

  • A tool dealing with security vulnerabilities may define a Vulnerability object and reference Packages and Files that are affected by a Vulnerability.

To better understand the embedding or referencing relationships:

  • using references is similar to a tabular data layout, akin to a relational database table structure

  • using embedding is similar to a tree data layout such as in a file/directory tree or nested data such as XML.

Another way to think about these relationships is a “GROUP BY” statement in SQL. The data can be grouped-by Component, then Packages or grouped-by Files then Components.

Both referencing and embedding layouts can be combined freely and are not mutually exclusive. When using both at the same time, some care is needed to avoid creating documents with conflicting or duplicated data that is referenced and embedded at the same time.

Using references is often useful when there is an agreement on how to reference objects between two tools or parties. For instance, when using nexB tools, a unique and well defined license key is used to reference a license rather than embedding the full license details. A concise reference to the name and version of a public package from a well known package repository such as RPM or Maven can be used to the same effect. Or an SPDX license identifier can be used to reference an SPDX-listed license without having to embed its full license text.

The nature of the relationship between two objects can be specified when it is not obvious and requires some extra specification.  Each tool can define additional attributes to document these. For instance a common relationship between a party and a product or component is a role such as owner. For packages a role can be maintainer, author, etc.  Or the license of a file or package may be the “asserted” license by the project authors. It may differ from the “detected” license from a scan or code inspection and may further differ from a “concluded” license or a “selected” license when there is a license choice. At the package and license level the types of relationships documented in the SPDX specification are a good source for more details. For example this component references two parties where one is the author and the other is the maintainer documented using a role attribute:

"components": [{
    "source": "http://apache.org",
    "name": "Apache httpd",
    "version": "2.3",
    "parties": [
        {"name": "John Doe", "type": "person", "role": "author"},
        {"name": "Jane Smith", "type": "person", "role": "maintainer"},
        {"name": "Jane Smith", "type": "person", "role": "owner"},
    ]
}]

Document format conventions

The default ABC Data format is JSON (though it can be serialized to anything else that would preserve its structure). YAML is also supported and preferred for storage of simple documents that document one or a few top level objects and that need to be edited by a human.

The data structure by nested name/value pairs attributes and lists of values maps naturally to the corresponding JSON and YAML constructs. In JSON-speak these are arrays (lists) and objects (name/value pairs).

ABC Data can be provided as simple files or embedded in some API payload. As files, their content can be either JSON or YAML and should have either a .json or .yml extension by convention. For backwards compatibility with previous AboutCode conventions, the .ABOUT extension can be used for YAML documents. For instance this is used in the legacy about_code_tool and its successors. The DocumentCode tool can store individual attribution data in a .ABOUT yml file.

The top level structure of an ABC Data block is always a JSON object or YAML dictionary. Depending on the context this top level structure may be wrapped in another data structure (for instance when exchanging AboutCode Data in some web api, the API may provide ABC Data as a payload in a “results” or “body” or “data” block and also have some “headers” or “meta” block).

The top level elements must contain at least one of the object names and a list of objects such as here with a list of files:

files:
    - path: this/foo/bar
      size: 123
      sha1: aaf35463472abcd
    - path: that/baz

Optionally an “aboutcode_version” attribute can be added at the top level to document which version of the AboutCode Data structure is used for a document. For example: aboutcode_version: 4.0

Order of attributes matters to help reading documents: tools that write ABC Data should attempt to  use a consistent order for objects and attribute names rather than a random ordering. However, some tools may not be able to set a specific order so thi is only a recommendation. The preferred order is to start with identifiers and keys and from the most important to the least important attributes, followed by attributes grouped logically together,  followed by related objects.

References between documents and payload, embedding other files

ABC Data may reference other data. For instance in a hyperlinked REST API a list of URLs to further invoke the API and get license’ details may be provided with an api_url attribute to identify which API calls to invoke. The ways to reference data and the semantics and mechanics of each of these embeddings or references needed to get the actual data are not specified here. Each tool may offer its own mechanism. A convention for an hyperlinked REST API JSON payload could be to use api_url(s) identifier to specify additional “GET”able endpoints. The AttributeCode tool use *_file attributes in YAML or JSON documents to reference external license and notices text files to load with the text content.

Another convention is used in ScanCode to reference license texts and license detection rules by key: An ABC Data YAML file contains the ABC Data. And side by side there is a file with the same base name and a LICENSE, SPDX or NOTICE, RULE, extension that contains the actual text corresponding to the license, the SPDX text or the rule text. The convention here is to use an implicit reference between files because they have the same base name and different extensions.

In the future, we may specify how to embed an external ABC Data file in another ABC Data file; this would only apply to file-based ABC Data payload though and could not apply to hyperlinked REST APIs.

Document-as-files naming, exchange and storage

Each tool handling ABC Data may name an ABC Data file in any manner and store the data in any way that is appropriate. The structure is a set of data exchange conventions and may be used for storage but nothing is specified on how to do this.

For consistency, tools consuming AboutCode Data are encouraged to use the same data structure internally and in their user interface to organize and name the data, but this is only a recommendation.

For instance, the AttributeCode tool uses a convention to store ABC Data as YAML in a file with a .ABOUT extension and uses the ABC Data structures internally and externally.

When exchanging data (for instance over an API), the API provider of ABC Data should support a request to return either embedded data or data by reference and ideally allow the caller to specify which objects and attributes it is interested in (possibly in the future using something like GraphQL).

When interacting with tools through an  API, the conversation could start by sending an ABC Data payload with some extra request data and receiving an ABC Data payload in return. For instance, when requesting matching packages from a matching tool, you could start by passing scan data with checksums for several files at once and receive detailed data for each of the matched files or packages.

Documenting and validating attributes

Each tool handling ABC Data may only be interested in processing certain objects and attributes when accepting data in, or when providing data out. Attributes that are unknown should be ignored. To document which objects and which attributes a tool can handle, a tool should provide some documentation. The documentation format is not specified here, but it could use a JSON schema in the future. This should include documentation regarding if and how data is validated, and when and how errors or warnings are triggered and provided when there is a validation error. For example, a validation could be to check that an SPDX license id exists at SPDX or that a URL is valid.

Notes on YAML format

YAML is the preferred file format for ABC Data destined for reading or writing primarily by humans.

  • Block-style is better.

  • When you write AboutCode Data as YAML, you should privilege block-style and avoid flow-style YAML which is less readable for humans.

  • Avoid Multi-document YAML.

  • Multi-document YAML documents should be avoided (when using the — separators).

  • Beware of parser shenanigans: Most YAML parsers recognize and convert automatically certain data types such as numbers, booleans or dates. You should be aware of this because the ABC Data strings may contain date stamps. You may want to configure a YAML parser to deactivate some of these automated format conversions to avoid unwanted conversions.

Notes on JSON Format

JSON is the preferred file format for ABC Data destined for reading and writing primarily by machines.

  • “Streamable”  JSON with JSON-lines.

A large JSON document may benefit from being readable line-by-line rather than loaded all at once in memory. For this purpose, the convention is to use JSON lines where each line in the document is a valid JSON document itself: this enables reading the document in line-by-line increments. The preferred way to do so is to provide one ABCD top level object per document where the first line contains meta information about the stream such as a notice, a tool version or  the aboutcode version.

  • Avoid escaped slash.

The JSON specification says you CAN escape forward slash, but this is optional. It is best to avoid escaping slash when not needed for better readability.

For instance for URLs this form:

"https://enterprise.dejacode.com/component_catalog/nexB/16fusb/1.0/"

should be preferred over this escaped form when backslashes are not needed:

"https:\\/\\/enterprise.dejacode.com\\/component_catalog\\/nexB\\/16fusb\\/1.0\\/"

Notes on embedding ABC Data in source code files.

It could be useful to include ABC Data directly in a source code file, such as to provide structured license and provenance data for a single file. This requires of course a file modification. While this is not a preferred use case, it can be handy to document your own code one file at a time. Using an external ABC Data file should be preferred but here are conventions for this use case:

  • The ABC Data should be embedded in a top level block of comments.

  • Inside that block of comments the preferred format is YAML.

  • How a tool collects that ABC Data when embedded in code is to be determined.

  • Tools offering such support should document and eventually enforce their own conventions.

Notes on spreadsheet and CSV files

ABC Data does not support or endorse using CSV or spreadsheets for data exchange.

CSV and other spreadsheet file formats are NOT recommended to store ABC Data. In most cases you cannot store a correct data set in a spreadsheet. However, these tools are also widely used and convenient. Here are some recommendations when you need  to communicate ABC data in a CSV or spreadsheet format: even though ABC Data is naturally nested and tree-like, it should be possible to serialize certain ABCD objects as flat, tabular data.

  • Naming columns

The table column names may need to be adjusted to correctly reference the multiple level of object and attribute nesting using a dot as a separator. The dot or period is otherwise not allowed in attribute names. For example, you could use files.path for files or components.name to reference a component name. Some tools may prefer to create tabular files with their own column names and layout, and provide mappings to ABC Data attribute and object names.

  • Example for an inventory:

Since ABC Data can be related by reference, the preferred (and cumbersome) way to store ABC Data in a spreadsheet is to use one tab for each object type and use identifying attributes to relate objects between each others across tabs. For instance, in a Bill of Materials (BOM) spreadsheet for a Product, you could use a tab to describe the Product attributes and another tab to describe the Components used in this Product and possibly additional tabs to describe the related packages and files corresponding to these

  • Care is needed for Packages, Components and other names and for dates, versions, unicode and UTF-8 to avoid damaging content (aka. mojibake)

Spreadsheet tools such as Excel or LibreOffice  automatically recognize and convert data to their own format: a date of 20016-08-17 may be converted to a date number when a CSV is loaded and difficult to recover as a correct original date stamp string afterwards. Or a version 1.0 may be irreversibly converted to 1 or 1.90 to 1.9 losing important version information.

Spreadsheet tools may not recognize and handle properly UTF-8 texts and damage descriptions and texts. These tools may also treat strings starting with the equal sign as a formula. When incorrectly recognizing special accentuated characters this may damage texts creating what is called “mojibake” (See https://en.wikipedia.org/wiki/Mojibake)

Always use these tools with caution and be prepared for damage to your data if you use these tools to save or create ABC Data.

Impact on AttributeCode

As an integration tool, AttributeCode itself may specify only a very few elements.

The new structure will need to be implemented. Here could be an example in YAML:

aboutcode_version: 4.0
components:
 -  source: dejacode.com
    name: bitarray
    version: 0.8.1
    homepage_url: https://github.com/ilanschnell/bitarray
    copyright: Copyright (c) Ilan Schnell and others
    files:
        - path: some/directory/
           type: dir
        - path: bitarray-0.8.1-cp27-cp27m-macosx_10_9_intel.whl
        - path: someotherdir/bitarray-0.8.1-cp27-cp27m-manylinux1_i686.whl
        - path: bitarray-0.8.1-cp27-cp27m-manylinux1_x86_64.whl
        - path: bitarray-0.8.1-cp27-cp27m-win_amd64.whl
        - path: bitarray-0.8.1-cp27-cp27m-win32.whl
        - path: bitarray-0.8.1-cp27-cp27mu-manylinux1_i686.whl
        - path: bitarray-0.8.1-cp27-cp27mu-manylinux1_x86_64.whl
        - path: bitarray-0.8.1-cp27-none-macosx_10_6_intel.whl
        - path: bitarray-0.8.1.tar.gz

    parties:
      - role: owner
        name: Ilan Schnell

    packages:
      - download_url: http://pypi.python.org/packages/source/b/bitarray/bitarray-0.8.1.tar.gz
        sha1: 468456384529abcdef342

    license_expression: psf

    licenses:
      - source: scancode.com
        key: psf
        text_file: PSF.LICENSE

And here would be similar data in JSON:

{"components": [{
               "name": "bitarray",
               "version": "0.8.1"
               "homepage_url": "https://github.com/ilanschnell/bitarray",
               "copyright": "Copyright (c) Ilan Schnell and others",
               "license_expression": "psf",
               "licenses": [{"key": "psf", "text_file": "PSF.LICENSE", "source": "scancode.com"}],
               "packages": [{"download_url": "http://pypi.python.org/packages/source/b/bitarray/bitarray-0.8.1.tar.gz"
                            "sha1": "468456384529abcdef342"
                }],
               "parties": [{"name": "Ilan Schnell", "role": "owner"}],

               "files": [{"path": "some/directory/", "type": "dir"},
                         {"path": "bitarray-0.8.1-cp27-cp27m-macosx_10_9_intel.whl"},
                         {"path": "bitarray-0.8.1-cp27-cp27m-manylinux1_i686.whl"},
                         {"path": "bitarray-0.8.1-cp27-cp27m-manylinux1_x86_64.whl"},
                         {"path": "bitarray-0.8.1-cp27-cp27m-win_amd64.whl"},
                         {"path": "bitarray-0.8.1-cp27-cp27m-win32.whl"},
                         {"path": "bitarray-0.8.1-cp27-cp27mu-manylinux1_i686.whl"},
                         {"path": "bitarray-0.8.1-cp27-cp27mu-manylinux1_x86_64.whl"},
                         {"path": "bitarray-0.8.1-cp27-none-macosx_10_6_intel.whl"},
                         {"path": "bitarray-0.8.1.tar.gz"}],
               }],

 aboutcode_version: "4.0"}
Impact on ScanCode Toolkit

The new format will need to be implemented for scan results in general and for packages in particular.

ScanCode will specify Package and several attributes related to scanning and referencing clues for files, directories and packages.

Alternatively Packages could be extracted to an independent PackagedCode library.

The changes will minimize impact on the layout of the scan results. Here is an example of a scan payload in ABCD format: this is essentially the standard scan format:

{
  "scancode_notice": "Generated with ScanCode and provided .......",
  "scancode_version": "2.0.0.dev0",
  "files_count": 7,
  "files": [
    {
      "path": "samples/JGroups/src/",
      "type": "directory",
      "files_count": 29
      "licenses" : [
          { "key":"apache-2.0",
            "concluded": true}
      ]
    }
    {
      "path": "samples/JGroups/src/GuardedBy.java",
      "date": "2015-12-10",
      "programming_language": "Java",
      "sha1": "981d67087e65e9a44957c026d4b10817cf77d966",
      "name": "GuardedBy.java",
      "extension": ".java",
      "file_type": "ASCII text",
      "is_text": true,
      "is_source": true,
      "md5": "c5064400f759d3e81771005051d17dc1",
      "type": "file",
      "is_archive": null,
      "mime_type": "text/plain",
      "size": 813,
      "copyrights": [
        {
          "end_line": 12,
          "start_line": 9,
          "holder": "Brian Goetz and Tim Peierls",
          "statement": "Copyright (c) 2005 Brian Goetz and Tim Peierls"
        }
      ],
      "licenses": [
        { "detected": true,
          "key": "cc-by-2.5",
          "short_name": "CC-BY-2.5",
          "homepage_url": "http://creativecommons.org/licenses/by/2.5/",
          "dejacode_url": "https://enterprise.dejacode.com/license_library/Demo/cc-by-2.5/",
          "text_url": "http://creativecommons.org/licenses/by/2.5/legalcode",
          "owner": {
            "name": "Creative Commons",
          },
          "detection_score": 100.0,
          "start_line": 11,
          "end_line": 11,
          "category": "Attribution",
          "external_reference": {
            "source": "spdx.org",
            "key": "CC-BY-2.5"
            "url": "http://spdx.org/licenses/CC-BY-2.5",
          },
        }
      ],
    },
    {
      "path": "samples/JGroups/src/ImmutableReference.java",
      "date": "2015-12-10",
      "md5": "48ca3c72fb9a65c771a321222f118b88",
      "type": "file",
      "mime_type": "text/plain",
      "size": "1838",
      "programming_language": "Java",
      "sha1": "30f56b876d5576d9869e2c5c509b08db57110592",
      "name": "ImmutableReference.java",
      "extension": ".java",
      "file_type": "ASCII text",
      "is_text": true,
      "license_expression": "lgpl-2.1-plus and lgpl-2.0-plus",
      "is_source": true,
      "copyrights": [{
        "end_line": 5,
        "start_line": 2,
        "holder": "Red Hat, Inc.",
        "statement": "Copyright 2010, Red Hat, Inc."
      }],
      "licenses": [
        { "detected": true,
          "key": "lgpl-2.1-plus",
          "category": "Copyleft Limited",
          "homepage_url": "http://www.gnu.org/licenses/old-licenses/lgpl-2.1-standalone.html",
          "start_line": 7,
          "end_line": 10,
          "short_name": "LGPL 2.1 or later",
          "owner": "Free Software Foundation (FSF)",
          "dejacode_url": "https://enterprise.dejacode.com/license_library/Demo/lgpl-2.1-plus/",
          "detection_score": 100.0,
          "external_reference": {
            "url": "http://spdx.org/licenses/LGPL-2.1+",
            "source": "spdx.org",
            "key": "LGPL-2.1+"
          }
        },
        { "concluded": true,
          "key": "lgpl-2.0-plus",
          "short_name": "LGPL 2.0 or later",
          "homepage_url": "http://www.gnu.org/licenses/old-licenses/lgpl-2.0.html",
          "end_line": 20,
          "dejacode_url": "https://enterprise.dejacode.com/license_library/Demo/lgpl-2.0-plus/",
          "text_url": "http://www.gnu.org/licenses/old-licenses/lgpl-2.0-standalone.html",
          "owner": "Free Software Foundation (FSF)",
          "start_line": 12,
          "detection_score": 47.46,
          "category": "Copyleft Limited",
          "external_reference": {
            "url": "http://spdx.org/licenses/LGPL-2.0+",
            "source": "spdx.org",
            "key": "LGPL-2.0+"
          }
        }
      ],
    },
    {
      "path": "samples/arch/zlib.tar.gz",
      "file_type": "gzip compressed data, last modified: Wed Jul 15 11:08:19 2015, from Unix",
      "date": "2015-12-10",
      "is_binary": true,
      "md5": "20b2370751abfc08bb3556c1d8114b5a",
      "sha1": "576f0ccfe534d7f5ff5d6400078d3c6586de3abd",
      "name": "zlib.tar.gz",
      "extension": ".gz",
      "size": 28103,
      "type": "file",
      "is_archive": true,
      "mime_type": "application/x-gzip",
      "packages": [
        {
          "type": "plain tarball"
        }
      ],
    }
  ]
}
AboutCode Manager

As a primary GUI for data review and integration, AboutCode Manager will need to be fluent in ABC Data to read/write ABC Data locally and remotely through API from several sources.

The short term changes would include:

  • Support reading ABC Data from ScanCode

  • Writing ABC Data, adding conclusions as related objects in the proper lists

New and Future tools
  • TraceCode: would likely specify low level attributes for files (such as debug symbols, etc) and how files are related from devel to deploy and back.

  • VulnerableCode: would likely specify a new Vulnerability object and the related attributes and may track several identifiers to the NIST NVD CPE and CVE.

  • DeltaCode: would likely specify attributes to describe the changes between codebases, files, packages.

Copyright (c) 2016 nexB Inc.

Documentation Guide

Help

AboutCode is a suite of open source projects.

AboutCode Projects

  • ScanCode Toolkit: This is a set of code scanning tools to detect the origin and license of code and dependencies. ScanCode Toolkit uses a plug-in architecture to run a series of scan-related tools in one process flow. This is the most popular project and is used by hundreds of software teams. https://github.com/nexB/scancode-toolkit . The lead maintainer is @pombredanne

  • Scancode Workbench (formerly AboutCode Manager) This is a desktop application (based on Electron) to review the results of a scan and document your conclusions about the origin and license of software components and packages. https://github.com/nexB/aboutcode-manager . The lead maintainer is @majurg

  • AboutCode Toolkit: This is a set of command line tools to document the provenance of your code and generate attribution notices. AboutCode Toolkit uses small yaml files to document code provenance inside a codebase. https://github.com/nexB/aboutcode-toolkit . The lead maintainer is @chinyeungli

  • TraceCode Toolkit: This is a set of tools to trace files from your deployment or distribution packages back to their origin in a development codebase or repository. The primary tool uses strace https://github.com/strace/strace/ to trace system calls on Linux and construct a build graph from syscalls to show which files are used to build a binary. We are contributors to strace. Maintained by @pombredanne

  • Conan: “conan” stands for “CONtainer ANalysis” and is a tool to analyze the structure and provenance of software components in Docker images using static analysis. https://github.com/nexB/conan Maintained by @pombredanne

  • license-expression: This is a library to parse, analyze, compare and normalize SPDX-like license expressions using a boolean logic expression engine. See https://spdx.org/spdx-specification-21-web-version#h.jxpfx0ykyb60 to understand what a license expression is. See https://github.com/nexB/license-expression for the code. The underlying boolean engine is at https://github.com/bastikr/boolean.py . Both are co-maintained by @pombredanne

  • ABCD aka AboutCode Data: is a simple set of conventions to define data structures that all the AboutCode tools can understand and use to exchange data. The specification lives in this repository. .ABOUT files and ScanCode tooklit data are examples of this approach. Other projects such as https://libraries.io and OSS Review Toolkit also use these conventions.

  • DeltaCode is a command line tool to compare scans and determine if and where there are material differences that affect licensing. The lead maintainer is @majurg

  • VulnerableCode: an emerging server-side application to collect and track known package vulnerabilities.

License

AboutCode includes documents that are dedicated to the Public Domain using the Creative Commons CC0 1.0 Universal (CC0 1.0) Public Domain Dedication: http://creativecommons.org/publicdomain/zero/1.0/

Document Maintenance

Document Software Setup

AboutCode documentation is built using Sphinx. See http://www.sphinx-doc.org/en/master/index.html

AboutCode documentation is distributed using “Read the Docs”. See https://readthedocs.org/

Individual document files are in reStructuredText format. See http://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html

You create, build, and preview AboutCode documentation on your local machine.

You commit your updates to the AboutCode repository on GitHub, which triggers an automatic rebuild of https://aboutcode.readthedocs.io/en/latest/index.html

Clone AboutCode

To get started, create or identify a working directory on your local machine.

Open that directory and execute the following command in a terminal session:

git clone https://github.com/nexB/aboutcode.git

That will create an /aboutcode directory in your working directory. Now you can install the dependencies in a virtualenv:

cd aboutcode
virtualenv -p /usr/bin/python3.6 docs-venv
source docs-venv/bin/activate

Now, the following prerequisites are installed

  • Sphinx

  • sphinx_rtd_theme (the format theme used by ReadTheDocs)

  • docs8 (style linter)

pip install Sphinx sphinx_rtd_theme doc8

Now you can build the HTML documents locally:

cd docs
make html

Assuming that your Sphinx installation was successful, Sphinx should build a local instance of the documentation .html files:

open build/html/index.html

In case this command did not work, for example on Ubuntu 18.04 you may get a message like “Couldn’t get a file descriptor referring to the console”, try:

see build/html/index.html

You now have a local build of the AboutCode documents.

Improve AboutCode Documents

Before you begin creating and modifying AboutCode documents, be sure that you understand the basics of reStructuredText as explained at http://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html

Ensure that you have the latest AboutCode files:

git pull
git status

Use your favorite text editor to create and modify .rst files to make your documentation improvements.

Review your work:

cd docs
make html
open build/html/index.html

AboutCode uses Travis-CI to test build status and check links, so run this script at your local system before creating a Pull Request.

cd docs
./scripts/sphinx_build_link_check.sh
./scripts/doc8_style_check.sh

Share AboutCode Document Improvements

Follow standard git procedures to upload your new and modified files. The following commands are examples:

git status
git add source/index.rst
git add source/how-to-scan.rst
git status
git commit -m "New how-to document that explains how to scan"
git status
git push
git status

The AboutCode webhook with ReadTheDocs should rebuild the documentation after your Pull Request is Merged.

Refer the Pro Git Book available online for Git tutorials covering more complex topics on Branching, Merging, Rebasing etc.

Continuous Integration

The documentations are checked on every new commit through Travis-CI, so that common errors are avoided and documentation standards are enforced. Travis-CI presently checks for these 3 aspects of the documentation :

  1. Successful Builds (By using sphinx-build)

  2. No Broken Links (By Using link-check)

  3. Linting Errors (By Using Doc8)

So run these scripts at your local system before creating a Pull Request:

cd docs
./scripts/sphinx_build_link_check.sh
./scripts/doc8_style_check.sh

Style Checks Using Doc8

How To Run Style Tests

In the project root, run the following command:

$ doc8 --max-line-length 100 docs/source/ --ignore D000

A sample output is:

Scanning...
Validating...
docs/source/scancode-toolkit/misc/licence_policy_plugin.rst:37: D002 Trailing whitespace
docs/source/scancode-toolkit/misc/faq.rst:45: D003 Tabulation used for indentation
docs/source/scancode-toolkit/misc/faq.rst:9: D001 Line too long
docs/source/scancode-toolkit/misc/support.rst:6: D005 No newline at end of file
========
Total files scanned = 34
Total files ignored = 0
Total accumulated errors = 326
Detailed error counts:
    - CheckCarriageReturn = 0
    - CheckIndentationNoTab = 75
    - CheckMaxLineLength = 190
    - CheckNewlineEndOfFile = 13
    - CheckTrailingWhitespace = 47
    - CheckValidity = 1

Now fix the errors and run again till there isn’t any style error in the documentation.

What is Checked?

PyCQA is an Organization for code quality tools (and plugins) for the Python programming language. Doc8 is a sub-project of the same Organization. Refer this README for more details.

What is checked:

  • invalid rst format - D000

  • lines should not be longer than 100 characters - D001

    • RST exception: line with no whitespace except in the beginning

    • RST exception: lines with http or https URLs

    • RST exception: literal blocks

    • RST exception: rst target directives

  • no trailing whitespace - D002

  • no tabulation for indentation - D003

  • no carriage returns (use UNIX newlines) - D004

  • no newline at end of file - D005

Interspinx

Aboutcode documentation uses Intersphinx to create links to other Sphinx Documentations, to maintain links to other Aboutcode Projects.

To link sections in the same documentation, standart reST labels are used. Refer Cross-Referencing for more information.

For example:

.. _my-reference-label:

Section to cross-reference
--------------------------

This is the text of the section.

It refers to the section itself, see :ref:`my-reference-label`.

Now, using Intersphinx, you can create these labels in one Sphinx Documentation and then referance these labels from another Sphinx Documentation, hosted in different locations.

You just have to add the following in the conf.py file for your Sphinx Documentation, where you want to add the links:

extensions = [
'sphinx.ext.intersphinx'
]

intersphinx_mapping = {'scancode-toolkit': ('https://scancode-toolkit.readthedocs.io/en/latest/', None)}

To show all Intersphinx links and their targets of an Intersphinx mapping file, run:

python -msphinx.ext.intersphinx https://scancode-toolkit.readthedocs.io/en/latest/objects.inv

Warning

python -msphinx.ext.intersphinx https://scancode-toolkit.readthedocs.io/objects.inv will give error.

This enables you to create links to the scancode-toolkit Documentation in your own Documentation, where you modified the configuration file. Links can be added like this:

For more details refer :ref:`scancode-toolkit:doc_style_guide`.

You can also not use the scancode-toolkit label assigned to all links from scancode-toolkit.readthedocs.io, if you don’t have a label having the same name in your Sphinx Documentation. Example:

For more details refer :ref:`doc_style_guide`.

If you have a label in your documentation which is also present in the documentation linked by Intersphinx, and you link to that label, it will create a link to the local label.

For more information, refer this tutorial named Using Intersphinx.

Extra Style Checks

  1. Headings

    (Refer) Normally, there are no heading levels assigned to certain characters as the structure is determined from the succession of headings. However, this convention is used in Python’s Style Guide for documenting which you may follow:

    # with overline, for parts

    • with overline, for chapters

    =, for sections

    -, for subsections

    ^, for sub-subsections

    “, for paragraphs

  2. Heading Underlines

    Do not use underlines that are longer/shorter than the title headline itself. As in:

Correct :

Extra Style Checks
------------------

Incorrect :

Extra Style Checks
------------------------

Note

Underlines shorter than the Title text generates Errors on sphinx-build.

  1. Internal Links

    Using :ref: is advised over standard reStructuredText links to sections (like `Section title`_) because it works across files, when section headings are changed, will raise warnings if incorrect, and works for all builders that support cross-references. However, external links are created by using the standard `Section title`_ method.

  2. Eliminate Redundancy

    If a section/file has to be repeated somewhere else, do not write the exact same section/file twice. Use .. include: ../README.rst instead. Here, ../ refers to the documentation root, so file location can be used accordingly. This enables us to link documents from other upstream folders.

  3. Using :ref: only when necessary

    Use :ref: to create internal links only when needed, i.e. it is referenced somewhere. Do not create references for all the sections and then only reference some of them, because this created unnecessary references. This also generates ERROR in restructuredtext-lint.

  4. Spelling

    You should check for spelling errors before you push changes. Aspell is a GNU project Command Line tool you can use for this purpose. Download and install Aspell, then execute aspell check <file-name> for all the files changed. Be careful about not changing commands or other stuff as Aspell gives prompts for a lot of them. Also delete the temporary .bak files generated. Refer the manual for more information on how to use.

  5. Notes and Warning Snippets

    Every Note and Warning sections are to be kept in rst_snippets/note_snippets/ and rst_snippets/warning_snippets/ and then included to eliminate redundancy, as these are frequently used in multiple files.

Converting from Markdown

If you want to convert a .md file to a .rst file, this tool does it pretty well. You’d still have to clean up and check for errors as this contains a lot of bugs. But this is definitely better than converting everything by yourself.

This will be helpful in converting GitHub wiki’s (Markdown Files) to reStructuredtext files for Sphinx/ReadTheDocs hosting.

Getting Started

Tutorial Documents

How-To Documents

Reference Documents

Discussion Documents

Indices and Tables

Something Missing?

If something is missing in the documentation or if you found some part confusing, please file an issue with your suggestions for improvement. Use the “Documentation Improvement” template. Your help makes ScanCode docs better, we love hearing from you!