Welcome to DataSounds’s documentation!¶
Contents:
Readme¶
DataSounds¶
Get sounds from temporal series, or another sequecial data. Visit us at www.datasounds.org.
Installation¶
At the command line:
$ git clone http://github.com/DataSounds/DataSounds.git
$ cd DataSounds
$ python setup.py install
Or using pip (program to easily install Python packages), which dinamicaly access the Python Package Index PyPI.
$ pip install DataSounds
Or, with the controled python ecosystem virtualenvwrapper. After install virtualenvwrapper, follow the instructions below:
$ mkvirtualenv DataSounds
$ workon DataSounds
(DataSounds) $ git clone http://github.com/DataSounds/DataSounds.git
(DataSounds) $ cd DataSounds
(DataSounds) $ python setup.py install
Dependencies¶
Numpy is a necessary packages to use DataSounds.
Numpy can be installed using pip. If you use virtualenvwrapper, this could be done inside your virtual environment. Normally, Numpy is installed as a dependency of DataSounds and should work if it was sucessfully compiled.
Usage¶
from DataSounds.sounds import get_music, w2Midi
import numpy as np
data = np.random.rand(24)
music = get_music(data)
w2Midi('my_musica_data', music)
w2Midi writes a .midi file inside the current directory. In this case my_music_data.midi will be saved on disk. Enjoy it!
Contributing¶
Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.
You can contribute in many ways:
Types of Contributions¶
Report Bugs¶
Report bugs at https://github.com/DataSounds/DataSounds/issues.
If you are reporting a bug, please include:
- Your operating system name and version.
- Any details about your local setup that might be helpful in troubleshooting.
- Detailed steps to reproduce the bug.
Fix Bugs¶
Look through the GitHub issues for bugs. Anything tagged with “bug” is open to whoever wants to implement it.
Implement Features¶
Look through the GitHub issues for features. Anything tagged with “feature” is open to whoever wants to implement it.
Write Documentation¶
DataSounds could always use more documentation, whether as part of the official DataSounds docs, in docstrings, or even on the web in blog posts, articles, and such.
Submit Feedback¶
The best way to send feedback is to file an issue at https://github.com/DataSounds/DataSounds/issues.
If you are proposing a feature:
- Explain in detail how it would work.
- Keep the scope as narrow as possible, to make it easier to implement.
- Remember that this is a volunteer-driven project, and that contributions are welcome :)
Get Started!¶
Ready to contribute? Here’s how to set up DataSounds for local development.
Fork the DataSounds repo on GitHub.
Clone your fork locally:
$ git clone git@github.com:your_name_here/DataSounds.git
Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
$ mkvirtualenv devDS $ cd DataSounds/ $ python setup.py develop
Create a branch for local development:
$ git checkout -b name-of-your-bugfix-or-feature
Now you can make your changes locally.
When you’re done making changes, check that your changes pass through tests, including testing other Python versions with tox:
$ python setup.py test $ tox
To get the necessary packeges just install it as follows inside yours virtualenv:
$ pip install -r dev-requirements.txt
Commit your changes and push your branch to GitHub:
$ git add . $ git commit -m "Your detailed description of your changes." $ git push origin name-of-your-bugfix-or-feature
Submit a pull request through the GitHub website.
Pull Request Guidelines¶
Before you submit a pull request, check that it meets these guidelines:
- The pull request should include tests.
- If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
- The pull request should work for Python 2.6, 2.7, and 3.3, and for PyPy. Check https://travis-ci.org/DataSounds/DataSounds/pull_requests and make sure that the tests pass for all supported Python versions.
Credits¶
DataSounds development Lead¶
- Arnaldo Russo <arnaldo@datasounds.org>
- Luiz Irber <luiz@datasounds.org>
Contributors¶
None yet. Why not be the first?