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Subpackages

pydal.adapters package

Submodules

pydal.adapters.base module

class pydal.adapters.base.AdapterMeta

Bases: type

Metaclass to support manipulation of adapter classes.

At the moment is used to intercept entity_quoting argument passed to DAL.

class pydal.adapters.base.BaseAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.connection.ConnectionPool

ADD(first, second)

AGGREGATE(first, what)

ALLOW_NULL()

AND(first, second)

AS(first, second)

BELONGS(first, second)

CASE(query, t, f)

CAST(first, second)

COALESCE(first, second)

COALESCE_ZERO(first)

COMMA(first, second)

CONCAT(*items)

CONTAINS(first, second, case_sensitive=True)

COUNT(first, distinct=None)

DIV(first, second)

ENDSWITH(first, second)

EPOCH(first)

EQ(first, second=None)

EXPAND_CASE(query, true_false)

EXTRACT(first, what)

FALSE = 'F'

FALSE_exp = '0'

GE(first, second=None)

GT(first, second=None)

ILIKE(first, second, escape=None)

Case insensitive like operator

INVERT(first)

JOIN()

LE(first, second=None)

LEFT_JOIN()

LENGTH(first)

LIKE(first, second, escape=None)

Case sensitive like operator

LOWER(first)

LT(first, second=None)

MOD(first, second)

MUL(first, second)

NE(first, second=None)

NOT(first)

NOT_NULL(default, field_type)

ON(first, second)

OR(first, second)

PRIMARY_KEY(key)

QUOTE_TEMPLATE = '"%s"'

RANDOM()

RAW(first)

REGEXP(first, second)

Regular expression operator

REPLACE(first, tup)

STARTSWITH(first, second)

SUB(first, second)

SUBSTRING(field, parameters)

TRUE = 'T'

TRUE_exp = '1'

T_SEP = ' '

UPPER(first)

adapt(obj)

alias(table, alias)

Given a table object, makes a new table object with alias name.

build_parsemap()

bulk_insert(table, items)

can_join()

can_select_for_update = True

close_connection()

commit()

commit_on_alter_table = False

commit_prepared(key)

common_filter(query, tablenames)

concat_add(tablename)

connection = None

connector(*args, **kwargs)

constraint_name(table, fieldname)

count(query, distinct=None)

create_sequence_and_triggers(query, table, **args)

create_table(table, migrate=True, fake_migrate=False, polymodel=None)

current_cursor_in_use = False

cursors_in_use = []

dbpath = None

delete(tablename, query)

distributed_transaction_begin(key)

driver = None

driver_auto_json = []

driver_name = None

drivers = ()

drop(table, mode='')

execute(*a, **b)

execute_test_query()

expand(expression, field_type=None, colnames=False)

expand_all(fields, tablenames)

file_close(fileobj)

file_delete(filename)

file_exists(filename)

file_open(filename, mode='rb', lock=True)

find_driver(adapter_args, uri=None)

folder = None

get_cursor()

get_table(*queries)

id_query(table)

insert(table, fields)

isOperationalError(exception)

isProgrammingError(exception)

is_numerical_type(ftype)

iterparse(sql, fields, colnames, blob_decode=True, cacheable=False)

Iterator to parse one row at a time. It doen’t support the old style virtual fields

iterselect(query, fields, attributes)

lastrowid(table)

like_escaper_default(term)

log(message, table=None)

Logs migrations

It will not log changes if logfile is not specified. Defaults to sql.log

log_execute(*a, **b)

migrate_table(table, sql_fields, sql_fields_old, sql_fields_aux, logfile, fake_migrate=False)

parse(rows, fields, colnames, blob_decode=True, cacheable=False)

parse_blob(value, field_type)

parse_boolean(value, field_type)

parse_date(value, field_type)

parse_datetime(value, field_type)

parse_decimal(value, field_type)

parse_double(value, field_type)

parse_id(value, field_type)

parse_integer(value, field_type)

parse_json(value, field_type)

parse_list_integers(value, field_type)

parse_list_references(value, field_type)

parse_list_strings(value, field_type)

parse_reference(value, field_type)

parse_time(value, field_type)

parse_value(value, field_type, blob_decode=True)

prepare(key)

represent(obj, fieldtype)

represent_exceptions(obj, fieldtype)

rollback()

rollback_prepared(key)

rowslice(rows, minimum=0, maximum=None)

By default this function does nothing; overload when db does not do slicing.

save_dbt(table, sql_fields_current)

select(query, fields, attributes)

Always returns a Rows object, possibly empty.

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

sequence_name(tablename)

smart_adapt(obj)

sqlsafe_field(fieldname)

sqlsafe_table(tablename, ot=None)

support_distributed_transaction = False

table_alias(tbl)

tables(*queries)

test_query = 'SELECT 1;'

trigger_name(tablename)

truncate(table, mode=' ')

types = {'reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s', 'text': 'TEXT', 'float': 'DOUBLE', 'datetime': 'TIMESTAMP', 'bigint': 'INTEGER', 'id': 'INTEGER PRIMARY KEY AUTOINCREMENT', 'reference FK': ', CONSTRAINT "FK_%(constraint_name)s" FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'json': 'TEXT', 'big-id': 'INTEGER PRIMARY KEY AUTOINCREMENT', 'blob': 'BLOB', 'big-reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s', 'string': 'CHAR(%(length)s)', 'list:string': 'TEXT', 'date': 'DATE', 'integer': 'INTEGER', 'password': 'CHAR(%(length)s)', 'list:integer': 'TEXT', 'double': 'DOUBLE', 'decimal': 'DOUBLE', 'upload': 'CHAR(%(length)s)', 'list:reference': 'TEXT', 'boolean': 'CHAR(1)', 'time': 'TIME'}

update(tablename, query, fields)

uploads_in_blob = False

varquote(name)

class pydal.adapters.base.NoSQLAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

ADD(first, second)

AGGREGATE(first, what)

AND(first, second)

AS(first, second)

DIV(first, second)

ENDSWITH(first, second=None)

EXTRACT(first, what)

ILIKE(first, second)

LEFT_JOIN()

LENGTH(first)

LOWER(first)

MUL(first, second)

ON(first, second)

OR(first, second)

PRIMARY_KEY(key)

QUOTE_TEMPLATE = '%s'

RANDOM()

STARTSWITH(first, second=None)

SUB(first, second)

SUBSTRING(field, parameters)

UPPER(first)

can_join()

can_select_for_update = False

close_connection()

remember: no transactions on many NoSQL

commit()

remember: no transactions on many NoSQL

commit_prepared(key)

concat_add(table)

constraint_name(table, fieldname)

create_sequence_and_triggers(query, table, **args)

distributed_transaction_begin(key)

drop(table, mode)

execute(*a, **b)

execute_test_query()

NoSql DBs don’t have a universal query language. Override this specifc driver if need to test connection status. Throw exception on failure.

id_query(table)

lastrowid(table)

log_execute(*a, **b)

migrate_table(*a, **b)

parse_list_integers(value, field_type)

parse_list_references(value, field_type)

parse_list_strings(value, field_type)

prepare(key)

represent(obj, fieldtype)

represent_exceptions(obj, fieldtype)

rollback()

remember: no transactions on many NoSQL

rollback_prepared(key)

rowslice(rows, minimum=0, maximum=None)

pydal.adapters.couchdb module

class pydal.adapters.couchdb.CouchDBAdapter(db, uri='couchdb://127.0.0.1:5984', pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.NoSQLAdapter

AND(first, second)

COMMA(first, second)

EQ(first, second)

NE(first, second)

OR(first, second)

count(query, distinct=None)

create_table(table, migrate=True, fake_migrate=False, polymodel=None)

delete(tablename, query)

drivers = ('couchdb',)

expand(expression, field_type=None)

file_close(fileobj)

file_exists(filename)

file_open(filename, mode='rb', lock=True)

insert(table, fields)

represent(obj, fieldtype)

select(query, fields, attributes)

types = {'string': <type 'str'>, 'reference': <type 'long'>, 'text': <type 'str'>, 'id': <type 'long'>, 'float': <type 'float'>, 'bigint': <type 'long'>, 'upload': <type 'str'>, 'datetime': <type 'datetime.datetime'>, 'json': <type 'str'>, 'boolean': <type 'bool'>, 'blob': <type 'str'>, 'list:string': <type 'list'>, 'double': <type 'float'>, 'date': <type 'datetime.date'>, 'integer': <type 'long'>, 'password': <type 'str'>, 'list:integer': <type 'list'>, 'time': <type 'datetime.time'>, 'list:reference': <type 'list'>}

update(tablename, query, fields)

uploads_in_blob = True

pydal.adapters.cubrid module

class pydal.adapters.cubrid.CubridAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.mysql.MySQLAdapter

REGEX_URI = <_sre.SRE_Pattern object at 0x16ffd10>

after_connection()

drivers = ('cubriddb',)

pydal.adapters.db2 module

class pydal.adapters.db2.DB2Adapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

LEFT_JOIN()

RANDOM()

drivers = ('ibm_db_dbi', 'pyodbc')

execute(command, placeholders=None)

lastrowid(table)

represent_exceptions(obj, fieldtype)

rowslice(rows, minimum=0, maximum=None)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'CLOB', 'float': 'REAL', 'datetime': 'TIMESTAMP', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT GENERATED ALWAYS AS IDENTITY PRIMARY KEY NOT NULL', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'json': 'CLOB', 'big-id': 'BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY NOT NULL', 'blob': 'BLOB', 'big-reference': 'BIGINT, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'CLOB', 'date': 'DATE', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'CLOB', 'double': 'DOUBLE', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'CLOB', 'boolean': 'CHAR(1)', 'time': 'TIME'}

pydal.adapters.firebird module

class pydal.adapters.firebird.FireBirdAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

CONTAINS(first, second, case_sensitive=False)

EPOCH(first)

LENGTH(first)

NOT_NULL(default, field_type)

RANDOM()

REGEX_URI = <_sre.SRE_Pattern object at 0x1717300>

SUBSTRING(field, parameters)

commit_on_alter_table = True

create_sequence_and_triggers(query, table, **args)

drivers = ('kinterbasdb', 'firebirdsql', 'fdb', 'pyodbc')

lastrowid(table)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

sequence_name(tablename)

support_distributed_transaction = True

trigger_name(tablename)

types = {'reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'BLOB SUB_TYPE 1', 'float': 'FLOAT', 'datetime': 'TIMESTAMP', 'bigint': 'BIGINT', 'id': 'INTEGER PRIMARY KEY', 'json': 'BLOB SUB_TYPE 1', 'big-id': 'BIGINT PRIMARY KEY', 'blob': 'BLOB SUB_TYPE 0', 'big-reference': 'BIGINT REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'BLOB SUB_TYPE 1', 'date': 'DATE', 'integer': 'INTEGER', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'BLOB SUB_TYPE 1', 'double': 'DOUBLE PRECISION', 'decimal': 'DECIMAL(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'BLOB SUB_TYPE 1', 'boolean': 'CHAR(1)', 'time': 'TIME'}

class pydal.adapters.firebird.FireBirdEmbeddedAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.firebird.FireBirdAdapter

REGEX_URI = <_sre.SRE_Pattern object at 0x1718310>

drivers = ('kinterbasdb', 'firebirdsql', 'fdb', 'pyodbc')

pydal.adapters.google_adapters module

Adapter for GAE

pydal.adapters.imap module

class pydal.adapters.imap.IMAPAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.NoSQLAdapter

IMAP server adapter

This class is intended as an interface with email IMAP servers to perform simple queries in the web2py DAL query syntax, so email read, search and other related IMAP mail services (as those implemented by brands like Google(r), and Yahoo!(r) can be managed from web2py applications.

The code uses examples by Yuji Tomita on this post: http://yuji.wordpress.com/2011/06/22/python-imaplib-imap-example-with-gmail/#comment-1137 and is based in docs for Python imaplib, python email and email IETF’s (i.e. RFC2060 and RFC3501)

This adapter was tested with a small set of operations with Gmail(r). Other services requests could raise command syntax and response data issues.

It creates its table and field names “statically”, meaning that the developer should leave the table and field definitions to the DAL instance by calling the adapter’s .define_tables() method. The tables are defined with the IMAP server mailbox list information.

.define_tables() returns a dictionary mapping dal tablenames to the server mailbox names with the following structure:

{<tablename>: str <server mailbox name>}

Here is a list of supported fields:

Field	Type	Description
uid	string
answered	boolean	Flag
created	date
content	list:string	A list of dict text or html parts
to	string
cc	string
bcc	string
size	integer	the amount of octets of the message*
deleted	boolean	Flag
draft	boolean	Flag
flagged	boolean	Flag
sender	string
recent	boolean	Flag
seen	boolean	Flag
subject	string
mime	string	The mime header declaration
email	string	The complete RFC822 message (*)
attachments	list	Each non text part as dict
encoding	string	The main detected encoding

(*) At the application side it is measured as the length of the RFC822 message string

WARNING: As row id’s are mapped to email sequence numbers, make sure your imap client web2py app does not delete messages during select or update actions, to prevent updating or deleting different messages. Sequence numbers change whenever the mailbox is updated. To avoid this sequence numbers issues, it is recommended the use of uid fields in query references (although the update and delete in separate actions rule still applies).

# This is the code recommended to start imap support
# at the app's model:

imapdb = DAL("imap://user:password@server:port", pool_size=1) # port 993 for ssl
imapdb.define_tables()

Here is an (incomplete) list of possible imap commands:

# Count today's unseen messages
# smaller than 6000 octets from the
# inbox mailbox

q = imapdb.INBOX.seen == False
q &= imapdb.INBOX.created == datetime.date.today()
q &= imapdb.INBOX.size < 6000
unread = imapdb(q).count()

# Fetch last query messages
rows = imapdb(q).select()

# it is also possible to filter query select results with limitby and
# sequences of mailbox fields

set.select(<fields sequence>, limitby=(<int>, <int>))

# Mark last query messages as seen
messages = [row.uid for row in rows]
seen = imapdb(imapdb.INBOX.uid.belongs(messages)).update(seen=True)

# Delete messages in the imap database that have mails from mr. Gumby

deleted = 0
for mailbox in imapdb.tables
    deleted += imapdb(imapdb[mailbox].sender.contains("gumby")).delete()

# It is possible also to mark messages for deletion instead of ereasing them
# directly with set.update(deleted=True)


# This object give access
# to the adapter auto mailbox
# mapped names (which native
# mailbox has what table name)

imapdb.mailboxes <dict> # tablename, server native name pairs

# To retrieve a table native mailbox name use:
imapdb.<table>.mailbox

### New features v2.4.1:

# Declare mailboxes statically with tablename, name pairs
# This avoids the extra server names retrieval

imapdb.define_tables({"inbox": "INBOX"})

# Selects without content/attachments/email columns will only
# fetch header and flags

imapdb(q).select(imapdb.INBOX.sender, imapdb.INBOX.subject)

AND(first, second)

BELONGS(first, second)

CONTAINS(first, second, case_sensitive=False)

EQ(first, second)

GE(first, second)

GT(first, second)

LE(first, second)

LT(first, second)

NE(first, second=None)

NOT(first)

OR(first, second)

REGEX_URI = <_sre.SRE_Pattern object at 0x170d6c0>

convert_date(date, add=None, imf=False)

count(query, distinct=None)

create_table(*args, **kwargs)

dbengine = 'imap'

define_tables(mailbox_names=None)

Auto create common IMAP fileds

This function creates fields definitions “statically” meaning that custom fields as in other adapters should not be supported and definitions handled on a service/mode basis (local syntax for Gmail(r), Ymail(r)

Returns a dictionary with tablename, server native mailbox name pairs.

delete(tablename, query)

drivers = ('imaplib',)

encode_text(text, charset, errors='replace')

convert text for mail to unicode

get_charset(message)

get_last_message(tablename)

get_mailboxes()

Query the mail database for mailbox names

get_query_mailbox(query)

get_uid_bounds(tablename)

static header_represent(f, r)

insert(table, fields)

is_flag(flag)

reconnect(f=None)

IMAP4 Pool connection method

imap connection lacks of self cursor command. A custom command should be provided as a replacement for connection pooling to prevent uncaught remote session closing

select(query, fields, attributes)

Searches and Fetches records and return web2py rows

types = {'boolean': <type 'bool'>, 'string': <type 'str'>, 'list:string': <type 'str'>, 'integer': <type 'int'>, 'date': <type 'datetime.date'>, 'text': <type 'str'>, 'blob': <type 'str'>, 'bigint': <type 'long'>, 'id': <type 'long'>, 'datetime': <type 'datetime.datetime'>}

update(tablename, query, fields)

uri = None

MESSAGE is an identifier for sequence number

pydal.adapters.informix module

class pydal.adapters.informix.InformixAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

NOT_NULL(default, field_type)

RANDOM()

REGEX_URI = <_sre.SRE_Pattern object at 0x1702a80>

drivers = ('informixdb',)

execute(command)

lastrowid(table)

represent_exceptions(obj, fieldtype)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'BLOB SUB_TYPE 1', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': 'FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s CONSTRAINT TFK_%(table_name)s_%(field_name)s', 'id': 'SERIAL', 'reference FK': 'REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s CONSTRAINT FK_%(table_name)s_%(field_name)s', 'json': 'BLOB SUB_TYPE 1', 'big-id': 'BIGSERIAL', 'blob': 'BLOB SUB_TYPE 0', 'big-reference': 'BIGINT REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'BLOB SUB_TYPE 1', 'date': 'DATE', 'integer': 'INTEGER', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'BLOB SUB_TYPE 1', 'double': 'DOUBLE PRECISION', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'BLOB SUB_TYPE 1', 'boolean': 'CHAR(1)', 'time': 'CHAR(8)'}

class pydal.adapters.informix.InformixSEAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.informix.InformixAdapter

work in progress

rowslice(rows, minimum=0, maximum=None)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

pydal.adapters.ingres module

class pydal.adapters.ingres.IngresAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

LEFT_JOIN()

RANDOM()

create_sequence_and_triggers(query, table, **args)

drivers = ('pyodbc',)

lastrowid(table)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'CLOB', 'float': 'FLOAT', 'datetime': 'TIMESTAMP WITHOUT TIME ZONE', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'int not null unique with default next value for ii***lineitemsequence', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'json': 'CLOB', 'big-id': 'bigint not null unique with default next value for ii***lineitemsequence', 'blob': 'BLOB', 'big-reference': 'BIGINT, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'CLOB', 'date': 'ANSIDATE', 'integer': 'INTEGER4', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'CLOB', 'double': 'FLOAT8', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'CLOB', 'boolean': 'CHAR(1)', 'time': 'TIME WITHOUT TIME ZONE'}

class pydal.adapters.ingres.IngresUnicodeAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.ingres.IngresAdapter

drivers = ('pyodbc',)

types = {'reference': 'INTEGER4, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'NCLOB', 'float': 'FLOAT', 'datetime': 'TIMESTAMP WITHOUT TIME ZONE', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INTEGER4 not null unique with default next value for ii***lineitemsequence', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'json': 'NCLOB', 'big-id': 'BIGINT not null unique with default next value for ii***lineitemsequence', 'blob': 'BLOB', 'big-reference': 'BIGINT, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'NVARCHAR(%(length)s)', 'list:string': 'NCLOB', 'date': 'ANSIDATE', 'integer': 'INTEGER4', 'password': 'NVARCHAR(%(length)s)', 'list:integer': 'NCLOB', 'double': 'FLOAT8', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'NCLOB', 'boolean': 'CHAR(1)', 'time': 'TIME WITHOUT TIME ZONE'}

pydal.adapters.mongo module

class pydal.adapters.mongo.Binary

Bases: object

class pydal.adapters.mongo.MongoBlob

Bases: pydal.adapters.mongo.Binary

MONGO_BLOB_BYTES = 0

MONGO_BLOB_NON_UTF8_STR = 1

static decode(value)

class pydal.adapters.mongo.MongoDBAdapter(db, uri='mongodb://127.0.0.1:5984/db', pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.NoSQLAdapter

ADD(first, *args, **kwargs)

AGGREGATE(first, *args, **kwargs)

AND(first, second)

AS(first, *args, **kwargs)

AS_MARK = '__#AS#__'

BELONGS(first, second)

CMP_OPS_AGGREGATION_PIPELINE(op, first, second)

COALESCE(first, *args, **kwargs)

COMMA(first, second)

CONTAINS(first, second, case_sensitive=True)

COUNT(first, *args, **kwargs)

DIV(first, *args, **kwargs)

ENDSWITH(first, second)

EPOCH(first, *args, **kwargs)

EQ(first, second=None, *args, **kwargs)

EXPAND_CASE(first, *args, **kwargs)

EXTRACT(first, *args, **kwargs)

class Expanded(adapter, crud, query, fields=(), tablename=None, groupby=None, distinct=False, having=None)

Bases: object

Class to encapsulate a pydal expression and track the parse expansion and its results.

Two different MongoDB mechanisms are targeted here. If the query is sufficiently simple, then simple queries are generated. The bulk of the complexity here is however to support more complex queries that are targeted to the MongoDB Aggregation Pipeline.

This class supports four operations: ‘count’, ‘select’, ‘update’ and ‘delete’.

Behavior varies somewhat for each operation type. However building each pipeline stage is shared where the behavior is the same (or similar) for the different operations.

In general an attempt is made to build the query without using the pipeline, and if that fails then the query is rebuilt with the pipeline.

QUERY constructed in _build_pipeline_query():

$project : used to calculate expressions if needed $match: filters out records

FIELDS constructed in _expand_fields():

FIELDS:COUNT

$group : filter for distinct if needed $group: count the records remaining

FIELDS:SELECT

$group : implement aggregations if needed $project: implement expressions (etc) for select

FIELDS:UPDATE

$project: implement expressions (etc) for update

HAVING constructed in _add_having():

$project : used to calculate expressions $match: filters out records $project : used to filter out previous expression fields

annotate_expression(expression)

get_collection(safe=None)

MongoDBAdapter.GE(*args, **kwargs)

MongoDBAdapter.GROUP_MARK = '__#GROUP#__'

MongoDBAdapter.GT(*args, **kwargs)

MongoDBAdapter.ILIKE(first, second, escape=None)

MongoDBAdapter.INVERT(first)

MongoDBAdapter.LE(*args, **kwargs)

MongoDBAdapter.LENGTH(first)

https://jira.mongodb.org/browse/SERVER-5319 https://github.com/afchin/mongo/commit/f52105977e4d0ccb53bdddfb9c4528a3f3c40bdf

MongoDBAdapter.LIKE(first, second, case_sensitive=True, escape=None)

MongoDBAdapter.LOWER(first, *args, **kwargs)

MongoDBAdapter.LT(*args, **kwargs)

MongoDBAdapter.MOD(first, *args, **kwargs)

MongoDBAdapter.MUL(first, *args, **kwargs)

MongoDBAdapter.NE(first, second=None, *args, **kwargs)

MongoDBAdapter.NOT(first)

exception MongoDBAdapter.NotOnNoSqlError(message=None)

Bases: exceptions.NotImplementedError

MongoDBAdapter.ON(first, second)

MongoDBAdapter.OR(first, second)

MongoDBAdapter.RANDOM()

ORDER BY RANDOM()

https://github.com/mongodb/cookbook/blob/master/content/patterns/random-attribute.txt https://jira.mongodb.org/browse/SERVER-533 http://stackoverflow.com/questions/19412/how-to-request-a-random-row-in-sql

MongoDBAdapter.REGEXP(first, second, case_sensitive=True)

MongoDB provides regular expression capabilities for pattern matching strings in queries. MongoDB uses Perl compatible regular expressions (i.e. ‘PCRE’) version 8.36 with UTF-8 support.

MongoDBAdapter.REGEXP_MARK1 = '__#REGEXP_1#__'

MongoDBAdapter.REGEXP_MARK2 = '__#REGEXP_2#__'

MongoDBAdapter.REGEX_SELECT_AS_PARSER = <_sre.SRE_Pattern object>

MongoDBAdapter.STARTSWITH(first, second)

MongoDBAdapter.SUB(first, *args, **kwargs)

MongoDBAdapter.SUBSTRING(first, *args, **kwargs)

MongoDBAdapter.UPPER(first, *args, **kwargs)

MongoDBAdapter.bulk_insert(table, items)

MongoDBAdapter.check_fields_for_cmp(f)

MongoDBAdapter.check_notnull(table, values)

MongoDBAdapter.check_unique(table, values)

MongoDBAdapter.count(query, distinct=None, snapshot=True)

MongoDBAdapter.create_table(table, migrate=True, fake_migrate=False, polymodel=None)

MongoDBAdapter.delete(tablename, query, safe=None)

MongoDBAdapter.driver_auto_json = ['loads', 'dumps']

MongoDBAdapter.drivers = ('pymongo',)

MongoDBAdapter.drop(table, mode='')

MongoDBAdapter.expand(expression, field_type=None)

static MongoDBAdapter.has_field(expression)

MongoDBAdapter.insert(table, fields, safe=None)

Safe determines whether a asynchronous request is done or a synchronous action is done For safety, we use by default synchronous requests

MongoDBAdapter.needs_mongodb_aggregation_pipeline(f)

MongoDBAdapter.object_id(arg=None)

Convert input to a valid Mongodb ObjectId instance

self.object_id(“<random>”) -> ObjectId (not unique) instance

MongoDBAdapter.parse_blob(value, field_type)

static MongoDBAdapter.parse_data(expression, attribute, value=None)

MongoDBAdapter.parse_id(value, field_type)

MongoDBAdapter.parse_reference(value, field_type)

MongoDBAdapter.represent(obj, fieldtype)

MongoDBAdapter.select(query, fields, attributes, snapshot=False)

MongoDBAdapter.truncate(table, mode, safe=None)

MongoDBAdapter.types = {'string': <type 'str'>, 'reference': <type 'long'>, 'text': <type 'str'>, 'id': <type 'long'>, 'float': <type 'float'>, 'bigint': <type 'long'>, 'upload': <type 'str'>, 'datetime': <type 'datetime.datetime'>, 'json': <type 'str'>, 'boolean': <type 'bool'>, 'blob': <type 'str'>, 'list:string': <type 'list'>, 'double': <type 'float'>, 'date': <type 'datetime.date'>, 'integer': <type 'long'>, 'password': <type 'str'>, 'list:integer': <type 'list'>, 'time': <type 'datetime.time'>, 'list:reference': <type 'list'>}

MongoDBAdapter.update(tablename, query, fields, safe=None)

MongoDBAdapter.uploads_in_blob = False

MongoDBAdapter.validate_second(f)

pydal.adapters.mssql module

class pydal.adapters.mssql.MSSQL2Adapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLAdapter

ILIKE(first, second, escape=None)

Case insensitive like operator

drivers = ('pyodbc',)

execute(*a, **b)

represent(obj, fieldtype)

types = {'reference': 'INT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'NTEXT', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'NTEXT', 'blob': 'IMAGE', 'big-reference': 'BIGINT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'NVARCHAR(%(length)s)', 'list:string': 'NTEXT', 'date': 'DATETIME', 'integer': 'INT', 'password': 'NVARCHAR(%(length)s)', 'list:integer': 'NTEXT', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'NVARCHAR(%(length)s)', 'list:reference': 'NTEXT', 'boolean': 'BIT', 'time': 'CHAR(8)'}

class pydal.adapters.mssql.MSSQL3Adapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLAdapter

Experimental support for pagination in MSSQL

Requires MSSQL >= 2005, uses ROW_NUMBER()

rowslice(rows, minimum=0, maximum=None)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'VARCHAR(MAX)', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'VARCHAR(MAX)', 'blob': 'IMAGE', 'big-reference': 'BIGINT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'VARCHAR(MAX)', 'date': 'DATETIME', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'VARCHAR(MAX)', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'VARCHAR(MAX)', 'boolean': 'BIT', 'time': 'TIME(7)'}

class pydal.adapters.mssql.MSSQL3NAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLNAdapter

drivers = ('pyodbc',)

Experimental support for pagination in MSSQL Experimental: see MSSQLNAdapter docstring for warnings

Requires MSSQL >= 2005, uses ROW_NUMBER()

rowslice(rows, minimum=0, maximum=None)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'NVARCHAR(MAX)', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'NVARCHAR(MAX)', 'blob': 'IMAGE', 'big-reference': 'BIGINT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'NVARCHAR(%(length)s)', 'list:string': 'NVARCHAR(MAX)', 'date': 'DATETIME', 'integer': 'INT', 'password': 'NVARCHAR(%(length)s)', 'list:integer': 'NVARCHAR(MAX)', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'NVARCHAR(%(length)s)', 'list:reference': 'NVARCHAR(MAX)', 'boolean': 'BIT', 'time': 'TIME(7)'}

class pydal.adapters.mssql.MSSQL4Adapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLAdapter

Support for “native” pagination

Requires MSSQL >= 2012, uses OFFSET ... ROWS ... FETCH NEXT ... ROWS ONLY

rowslice(rows, minimum=0, maximum=None)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'VARCHAR(MAX)', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'VARCHAR(MAX)', 'blob': 'IMAGE', 'big-reference': 'BIGINT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'VARCHAR(MAX)', 'date': 'DATETIME', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'VARCHAR(MAX)', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'VARCHAR(MAX)', 'boolean': 'BIT', 'time': 'TIME(7)'}

class pydal.adapters.mssql.MSSQL4NAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLNAdapter

Experimental: see MSSQLNAdapter docstring for warnings Support for “native” pagination

Unicode-compatible version Requires MSSQL >= 2012, uses OFFSET ... ROWS ... FETCH NEXT ... ROWS ONLY After careful testing, this should be the de-facto adapter for recent MSSQL backends

rowslice(rows, minimum=0, maximum=None)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'NVARCHAR(MAX)', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'NVARCHAR(MAX)', 'blob': 'IMAGE', 'big-reference': 'BIGINT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'NVARCHAR(%(length)s)', 'list:string': 'NVARCHAR(MAX)', 'date': 'DATE', 'integer': 'INT', 'password': 'NVARCHAR(%(length)s)', 'list:integer': 'NVARCHAR(MAX)', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'NVARCHAR(%(length)s)', 'list:reference': 'NVARCHAR(MAX)', 'boolean': 'BIT', 'time': 'TIME(7)'}

class pydal.adapters.mssql.MSSQLAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

AGGREGATE(first, what)

ALLOW_NULL()

CAST(first, second)

CONCAT(*items)

CONTAINS(first, second, case_sensitive=True)

ENDSWITH(first, second)

EPOCH(first)

EXTRACT(field, what)

FALSE = 0

ILIKE(first, second, escape=None)

Case insensitive like operator

LEFT_JOIN()

LENGTH(first)

LIKE(first, second, escape=None)

Case sensitive like operator

PRIMARY_KEY(key)

QUOTE_TEMPLATE = '"%s"'

RANDOM()

REGEXP(first, second)

REGEX_ARGPATTERN = <_sre.SRE_Pattern object>

REGEX_DSN = <_sre.SRE_Pattern object>

REGEX_URI = <_sre.SRE_Pattern object at 0x17105f0>

STARTSWITH(first, second)

ST_ASTEXT(first)

ST_CONTAINS(first, second)

ST_DISTANCE(first, second)

ST_EQUALS(first, second)

ST_INTERSECTS(first, second)

ST_OVERLAPS(first, second)

ST_TOUCHES(first, second)

ST_WITHIN(first, second)

SUBSTRING(field, parameters)

TRUE = 1

T_SEP = 'T'

concat_add(tablename)

drivers = ('pyodbc',)

lastrowid(table)

like_escaper_default(term)

mssql_like_normalizer(term)

represent(obj, fieldtype)

rowslice(rows, minimum=0, maximum=None)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'TEXT', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'TEXT', 'blob': 'IMAGE', 'big-reference': 'BIGINT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'TEXT', 'date': 'DATETIME', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'TEXT', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'TEXT', 'boolean': 'BIT', 'time': 'CHAR(8)'}

varquote(name)

class pydal.adapters.mssql.MSSQLNAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLAdapter

ILIKE(first, second, escape=None)

Case insensitive like operator

drivers = ('pyodbc',)

Experimental – base class for handling unicode in MSSQL by default. Needs lots of testing. Try this on a fresh (or on a legacy) database. Using this in a database handled previously with non-unicode aware adapter is NOT supported

execute(*a, **b)

represent(obj, fieldtype)

types = {'reference': 'INT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'NTEXT', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'NTEXT', 'blob': 'IMAGE', 'big-reference': 'BIGINT %(null)s %(unique)s, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'NVARCHAR(%(length)s)', 'list:string': 'NTEXT', 'date': 'DATETIME', 'integer': 'INT', 'password': 'NVARCHAR(%(length)s)', 'list:integer': 'NTEXT', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'NVARCHAR(%(length)s)', 'list:reference': 'NTEXT', 'boolean': 'BIT', 'time': 'CHAR(8)'}

class pydal.adapters.mssql.SybaseAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLAdapter

drivers = 'Sybase'

types = {'reference': 'INT NULL, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'TEXT', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'INT IDENTITY PRIMARY KEY', 'geography': 'geography', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGINT IDENTITY PRIMARY KEY', 'json': 'TEXT', 'blob': 'IMAGE', 'big-reference': 'BIGINT NULL, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'CHAR VARYING(%(length)s)', 'list:string': 'TEXT', 'date': 'DATETIME', 'integer': 'INT', 'password': 'CHAR VARYING(%(length)s)', 'list:integer': 'TEXT', 'geometry': 'geometry', 'double': 'FLOAT', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'CHAR VARYING(%(length)s)', 'list:reference': 'TEXT', 'boolean': 'BIT', 'time': 'CHAR(8)'}

class pydal.adapters.mssql.VerticaAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.mssql.MSSQLAdapter

EXTRACT(first, what)

T_SEP = ' '

drivers = ('pyodbc',)

execute(a)

lastrowid(table)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'big-reference': 'BIGINT REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'reference': 'INT REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'BYTEA', 'decimal': 'DECIMAL(%(precision)s,%(scale)s)', 'float': 'FLOAT', 'bigint': 'BIGINT', 'upload': 'VARCHAR(%(length)s)', 'datetime': 'DATETIME', 'json': 'VARCHAR(%(length)s)', 'boolean': 'BOOLEAN', 'id': 'IDENTITY', 'blob': 'BYTEA', 'list:string': 'BYTEA', 'double': 'DOUBLE PRECISION', 'date': 'DATE', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'BYTEA', 'time': 'TIME', 'list:reference': 'BYTEA'}

pydal.adapters.mysql module

class pydal.adapters.mysql.MySQLAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

CAST(first, second)

CONCAT(*items)

EPOCH(first)

QUOTE_TEMPLATE = '`%s`'

RANDOM()

REGEXP(first, second)

REGEX_URI = <_sre.SRE_Pattern object at 0x16ffd10>

SUBSTRING(field, parameters)

after_connection()

commit_on_alter_table = True

commit_prepared(key)

distributed_transaction_begin(key)

drivers = ('MySQLdb', 'pymysql', 'mysqlconnector')

prepare(key)

rollback_prepared(key)

support_distributed_transaction = True

types = {'reference': 'INT %(null)s %(unique)s, INDEX %(index_name)s (%(field_name)s), FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'LONGTEXT', 'float': 'FLOAT', 'datetime': 'DATETIME', 'bigint': 'BIGINT', 'id': 'INT AUTO_INCREMENT NOT NULL', 'reference FK': ', CONSTRAINT `FK_%(constraint_name)s` FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'json': 'LONGTEXT', 'big-id': 'BIGINT AUTO_INCREMENT NOT NULL', 'blob': 'LONGBLOB', 'big-reference': 'BIGINT %(null)s %(unique)s, INDEX %(index_name)s (%(field_name)s), FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'LONGTEXT', 'date': 'DATE', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'LONGTEXT', 'double': 'DOUBLE', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'LONGTEXT', 'boolean': 'CHAR(1)', 'time': 'TIME'}

varquote(name)

pydal.adapters.oracle module

class pydal.adapters.oracle.OracleAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

LEFT_JOIN()

NOT_NULL(default, field_type)

RANDOM()

REGEXP(first, second)

after_connection()

commit_on_alter_table = False

constraint_name(tablename, fieldname)

create_sequence_and_triggers(query, table, **args)

drivers = ('cx_Oracle',)

execute(command, args=None)

insert(table, fields)

lastrowid(table)

oracle_fix = <_sre.SRE_Pattern object>

represent_exceptions(obj, fieldtype)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

sqlsafe_table(tablename, ot=None)

trigger_name(tablename)

types = {'reference': 'NUMBER, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'CLOB', 'float': 'FLOAT', 'datetime': 'DATE', 'bigint': 'NUMBER', 'reference TFK': ' CONSTRAINT FK_%(foreign_table)s_PK FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'NUMBER PRIMARY KEY', 'reference FK': ', CONSTRAINT FK_%(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'json': 'CLOB', 'big-id': 'NUMBER PRIMARY KEY', 'blob': 'CLOB', 'big-reference': 'NUMBER, CONSTRAINT %(constraint_name)s FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR2(%(length)s)', 'list:string': 'CLOB', 'date': 'DATE', 'integer': 'INT', 'password': 'VARCHAR2(%(length)s)', 'list:integer': 'CLOB', 'double': 'BINARY_DOUBLE', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR2(%(length)s)', 'list:reference': 'CLOB', 'boolean': 'CHAR(1)', 'time': 'CHAR(8)'}

pydal.adapters.postgres module

class pydal.adapters.postgres.JDBCPostgreSQLAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.postgres.PostgreSQLAdapter

REGEX_URI = <_sre.SRE_Pattern object at 0x1702a80>

after_connection()

drivers = ('zxJDBC',)

class pydal.adapters.postgres.NewPostgreSQLAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.postgres.PostgreSQLAdapter

ANY(first)

CONTAINS(first, second, case_sensitive=True)

EQ(first, second=None)

ILIKE(first, second, escape=None)

drivers = ('psycopg2', 'pg8000')

parse_list_integers(value, field_type)

parse_list_references(value, field_type)

parse_list_strings(value, field_type)

represent(obj, fieldtype)

types = {'reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s', 'text': 'TEXT', 'float': 'FLOAT', 'datetime': 'TIMESTAMP', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT "FK_%(foreign_table)s_PK" FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'SERIAL PRIMARY KEY', 'geography': 'GEOGRAPHY', 'reference FK': ', CONSTRAINT "FK_%(constraint_name)s" FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGSERIAL PRIMARY KEY', 'json': 'TEXT', 'blob': 'BYTEA', 'big-reference': 'BIGINT REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'TEXT[]', 'date': 'DATE', 'integer': 'INTEGER', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'BIGINT[]', 'geometry': 'GEOMETRY', 'double': 'FLOAT8', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'BIGINT[]', 'boolean': 'CHAR(1)', 'time': 'TIME'}

class pydal.adapters.postgres.PostgreSQLAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

ADD(first, second)

ILIKE(first, second, escape=None)

Case sensitive like operator

LIKE(first, second, escape=None)

Case sensitive like operator

QUOTE_TEMPLATE = '"%s"'

RANDOM()

REGEXP(first, second)

REGEX_URI = <_sre.SRE_Pattern object at 0x16c58e0>

ST_ASGEOJSON(first, second)

http://postgis.org/docs/ST_AsGeoJSON.html

ST_ASTEXT(first)

http://postgis.org/docs/ST_AsText.html

ST_CONTAINS(first, second)

http://postgis.org/docs/ST_Contains.html

ST_DISTANCE(first, second)

http://postgis.org/docs/ST_Distance.html

ST_DWITHIN(first, tup)

http://postgis.org/docs/ST_DWithin.html

ST_EQUALS(first, second)

http://postgis.org/docs/ST_Equals.html

ST_INTERSECTS(first, second)

http://postgis.org/docs/ST_Intersects.html

ST_OVERLAPS(first, second)

http://postgis.org/docs/ST_Overlaps.html

ST_SIMPLIFY(first, second)

http://postgis.org/docs/ST_Simplify.html

ST_SIMPLIFYPRESERVETOPOLOGY(first, second)

http://postgis.org/docs/ST_SimplifyPreserveTopology.html

ST_TOUCHES(first, second)

http://postgis.org/docs/ST_Touches.html

ST_WITHIN(first, second)

http://postgis.org/docs/ST_Within.html

ST_X(first)

http://postgis.org/docs/ST_X.html

ST_Y(first)

http://postgis.org/docs/ST_Y.html

adapt(obj)

after_connection()

commit_prepared(key)

create_sequence_and_triggers(query, table, **args)

distributed_transaction_begin(key)

drivers = ('psycopg2', 'pg8000')

execute(*a, **b)

lastrowid(table=None)

prepare(key)

represent(obj, fieldtype)

rollback_prepared(key)

sequence_name(table)

support_distributed_transaction = True

try_json()

types = {'reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s', 'text': 'TEXT', 'float': 'FLOAT', 'datetime': 'TIMESTAMP', 'bigint': 'BIGINT', 'reference TFK': ' CONSTRAINT "FK_%(foreign_table)s_PK" FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s) ON DELETE %(on_delete_action)s', 'id': 'SERIAL PRIMARY KEY', 'geography': 'GEOGRAPHY', 'reference FK': ', CONSTRAINT "FK_%(constraint_name)s" FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'big-id': 'BIGSERIAL PRIMARY KEY', 'json': 'TEXT', 'blob': 'BYTEA', 'big-reference': 'BIGINT REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'TEXT', 'date': 'DATE', 'integer': 'INTEGER', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'TEXT', 'geometry': 'GEOMETRY', 'double': 'FLOAT8', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'TEXT', 'boolean': 'CHAR(1)', 'time': 'TIME'}

varquote(name)

pydal.adapters.sapdb module

class pydal.adapters.sapdb.SAPDBAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

REGEX_URI = <_sre.SRE_Pattern object at 0x16c58e0>

create_sequence_and_triggers(query, table, **args)

drivers = ('sapdb',)

lastrowid(table)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

sequence_name(table)

support_distributed_transaction = False

types = {'reference': 'INT, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'text': 'LONG', 'float': 'FLOAT', 'datetime': 'TIMESTAMP', 'bigint': 'BIGINT', 'id': 'INT PRIMARY KEY', 'json': 'LONG', 'big-id': 'BIGINT PRIMARY KEY', 'blob': 'LONG', 'big-reference': 'BIGINT, FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'string': 'VARCHAR(%(length)s)', 'list:string': 'LONG', 'date': 'DATE', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'LONG', 'double': 'DOUBLE PRECISION', 'decimal': 'FIXED(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'LONG', 'boolean': 'CHAR(1)', 'time': 'TIME'}

pydal.adapters.sqlite module

class pydal.adapters.sqlite.JDBCSQLiteAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.sqlite.SQLiteAdapter

after_connection()

drivers = ('zxJDBC_sqlite',)

execute(a)

class pydal.adapters.sqlite.SQLiteAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

EXTRACT(field, what)

REGEXP(first, second)

after_connection()

can_select_for_update = None

delete(tablename, query)

drivers = ('sqlite2', 'sqlite3')

select(query, fields, attributes)

Simulate SELECT ... FOR UPDATE with BEGIN IMMEDIATE TRANSACTION. Note that the entire database, rather than one record, is locked (it will be locked eventually anyway by the following UPDATE).

static web2py_extract(lookup, s)

static web2py_regexp(expression, item)

class pydal.adapters.sqlite.SpatiaLiteAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, srid=4326, after_connection=None)

Bases: pydal.adapters.sqlite.SQLiteAdapter

ST_ASGEOJSON(first, second)

ST_ASTEXT(first)

ST_CONTAINS(first, second)

ST_DISTANCE(first, second)

ST_EQUALS(first, second)

ST_INTERSECTS(first, second)

ST_OVERLAPS(first, second)

ST_SIMPLIFY(first, second)

ST_TOUCHES(first, second)

ST_WITHIN(first, second)

after_connection()

drivers = ('sqlite3', 'sqlite2')

represent(obj, fieldtype)

types = {'string': 'CHAR(%(length)s)', 'reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s', 'text': 'TEXT', 'float': 'DOUBLE', 'datetime': 'TIMESTAMP', 'bigint': 'INTEGER', 'list:string': 'TEXT', 'date': 'DATE', 'integer': 'INTEGER', 'password': 'CHAR(%(length)s)', 'list:integer': 'TEXT', 'id': 'INTEGER PRIMARY KEY AUTOINCREMENT', 'reference FK': ', CONSTRAINT "FK_%(constraint_name)s" FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s', 'geometry': 'GEOMETRY', 'double': 'DOUBLE', 'decimal': 'DOUBLE', 'big-id': 'INTEGER PRIMARY KEY AUTOINCREMENT', 'list:reference': 'TEXT', 'json': 'TEXT', 'boolean': 'CHAR(1)', 'upload': 'CHAR(%(length)s)', 'blob': 'BLOB', 'time': 'TIME', 'big-reference': 'INTEGER REFERENCES %(foreign_key)s ON DELETE %(on_delete_action)s %(null)s %(unique)s'}

pydal.adapters.teradata module

class pydal.adapters.teradata.TeradataAdapter(db, uri, pool_size=0, folder=None, db_codec='UTF-8', credential_decoder=<function IDENTITY>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None)

Bases: pydal.adapters.base.BaseAdapter

LEFT_JOIN()

close(action='commit', really=True)

drivers = ('pyodbc',)

select_limitby(sql_s, sql_f, sql_t, sql_w, sql_o, limitby)

types = {'reference': 'INT', 'text': 'VARCHAR(2000)', 'float': 'REAL', 'datetime': 'TIMESTAMP', 'bigint': 'BIGINT', 'reference TFK': ' FOREIGN KEY (%(field_name)s) REFERENCES %(foreign_table)s (%(foreign_key)s)', 'id': 'INT GENERATED ALWAYS AS IDENTITY', 'reference FK': ' REFERENCES %(foreign_key)s', 'json': 'VARCHAR(4000)', 'big-id': 'BIGINT GENERATED ALWAYS AS IDENTITY', 'blob': 'BLOB', 'big-reference': 'BIGINT', 'string': 'VARCHAR(%(length)s)', 'list:string': 'VARCHAR(4000)', 'date': 'DATE', 'integer': 'INT', 'password': 'VARCHAR(%(length)s)', 'list:integer': 'VARCHAR(4000)', 'geometry': 'ST_GEOMETRY', 'double': 'DOUBLE', 'decimal': 'NUMERIC(%(precision)s,%(scale)s)', 'upload': 'VARCHAR(%(length)s)', 'list:reference': 'VARCHAR(4000)', 'boolean': 'CHAR(1)', 'time': 'TIME'}

Module contents

pydal.adapters.GoogleDatastoreAdapter = None

make the import available for BaseAdapter

pydal.helpers package

Submodules

pydal.helpers.classes module

class pydal.helpers.classes.BasicStorage(*args, **kwargs)

Bases: object

clear(*args, **kwargs)

copy(*args, **kwargs)

get(key, default=None)

has_key(key)

items()

iteritems()

iterkeys()

itervalues()

keys()

pop(*args, **kwargs)

update(*args, **kwargs)

values()

class pydal.helpers.classes.DatabaseStoredFile(db, filename, mode)

close()

close_connection()

escape(obj)

static exists(db, filename)

read(bytes=None)

readline()

static try_create_web2py_filesystem(db)

web2py_filesystems = set([])

write(data)

class pydal.helpers.classes.FakeCursor

Bases: object

The Python Database API Specification has a cursor() method, which NoSql drivers generally don’t support. If the exception in this function is taken then it likely means that some piece of functionality has not yet been implemented in the driver. And something is using the cursor.

https://www.python.org/dev/peps/pep-0249/

warn_bad_usage(attr)

class pydal.helpers.classes.FakeDriver(*args, **kwargs)

Bases: pydal.helpers.classes.BasicStorage

close()

commit()

cursor()

class pydal.helpers.classes.MethodAdder(table)

Bases: object

register(method_name=None)

class pydal.helpers.classes.NullCursor

Bases: pydal.helpers.classes.FakeCursor

lastrowid = 1

class pydal.helpers.classes.NullDriver(*args, **kwargs)

Bases: pydal.helpers.classes.FakeDriver

class pydal.helpers.classes.RecordDeleter(table, id)

Bases: object

class pydal.helpers.classes.RecordUpdater(colset, table, id)

Bases: object

class pydal.helpers.classes.Reference

Bases: long

get(key, default=None)

pydal.helpers.classes.Reference_pickler(data)

pydal.helpers.classes.Reference_unpickler(data)

class pydal.helpers.classes.SQLALL(table)

Bases: object

Helper class providing a comma-separated string having all the field names (prefixed by table name and ‘.’)

normally only called from within gluon.dal

class pydal.helpers.classes.SQLCallableList

Bases: list

class pydal.helpers.classes.SQLCustomType(type='string', native=None, encoder=None, decoder=None, validator=None, _class=None, widget=None, represent=None)

Bases: object

Allows defining of custom SQL types

Parameters:

• type – the web2py type (default = ‘string’)
• native – the backend type
• encoder – how to encode the value to store it in the backend
• decoder – how to decode the value retrieved from the backend
• validator – what validators to use ( default = None, will use the default validator for type)

Example::

Define as:

decimal = SQLCustomType(

type =’double’, native =’integer’, encoder =(lambda x: int(float(x) * 100)), decoder = (lambda x: Decimal(“0.00”) + Decimal(str(float(x)/100)) ) )

db.define_table(

‘example’, Field(‘value’, type=decimal) )

endswith(text=None)

startswith(text=None)

class pydal.helpers.classes.Serializable

Bases: object

as_dict(flat=False, sanitize=True)

as_json(sanitize=True)

as_xml(sanitize=True)

as_yaml(sanitize=True)

class pydal.helpers.classes.UseDatabaseStoredFile

file_close(fileobj)

file_delete(filename)

file_exists(filename)

file_open(filename, mode='rb', lock=True)

pydal.helpers.classes.pickle_basicstorage(s)

pydal.helpers.methods module

pydal.helpers.methods.archive_record(qset, fs, archive_table, current_record)

pydal.helpers.methods.auto_represent(field)

pydal.helpers.methods.auto_validators(field)

pydal.helpers.methods.bar_decode_integer(value)

pydal.helpers.methods.bar_decode_string(value)

pydal.helpers.methods.bar_encode(items)

pydal.helpers.methods.bar_escape(item)

pydal.helpers.methods.cleanup(text)

Validates that the given text is clean: only contains [0-9a-zA-Z_]

pydal.helpers.methods.geoLine(*line)

pydal.helpers.methods.geoPoint(x, y)

pydal.helpers.methods.geoPolygon(*line)

pydal.helpers.methods.hide_password(uri)

pydal.helpers.methods.int2uuid(n)

pydal.helpers.methods.list_represent(values, row=None)

pydal.helpers.methods.pluralize(singular, rules=[(<_sre.SRE_Pattern object at 0x7f04d81806b0>, <_sre.SRE_Pattern object at 0x7f04d81806b0>, 'children'), (<_sre.SRE_Pattern object at 0x7f04d819e9d0>, <_sre.SRE_Pattern object at 0x7f04d819e9d0>, 'eet'), (<_sre.SRE_Pattern object at 0x7f04d8176930>, <_sre.SRE_Pattern object at 0x7f04d8176930>, 'eeth'), (<_sre.SRE_Pattern object at 0x7f04d81769f0>, <_sre.SRE_Pattern object at 0x7f04d8180780>, 'l\\1aves'), (<_sre.SRE_Pattern object at 0x7f04d819ea80>, <_sre.SRE_Pattern object at 0x7f04d819ea80>, 'ses'), (<_sre.SRE_Pattern object at 0x7f04d819eb30>, <_sre.SRE_Pattern object at 0x7f04d819eb30>, 'men'), (<_sre.SRE_Pattern object at 0x7f04d819ebe0>, <_sre.SRE_Pattern object at 0x7f04d819ebe0>, 'ives'), (<_sre.SRE_Pattern object at 0x7f04d819ec90>, <_sre.SRE_Pattern object at 0x7f04d819ec90>, 'eaux'), (<_sre.SRE_Pattern object at 0x7f04d815e530>, <_sre.SRE_Pattern object at 0x7f04d815e530>, 'lves'), (<_sre.SRE_Pattern object at 0x7f04d8180850>, <_sre.SRE_Pattern object at 0x7f04d87a8920>, 'es'), (<_sre.SRE_Pattern object at 0x7f04db994e30>, <_sre.SRE_Pattern object at 0x7f04d87a8920>, 'es'), (<_sre.SRE_Pattern object at 0x7f04d8082220>, <_sre.SRE_Pattern object at 0x7f04d8063d20>, 'ies'), (<_sre.SRE_Pattern object at 0x7f04d87a8920>, <_sre.SRE_Pattern object at 0x7f04d87a8920>, 's')])

pydal.helpers.methods.smart_query(fields, text)

pydal.helpers.methods.use_common_filters(query)

pydal.helpers.methods.uuid2int(uuidv)

pydal.helpers.methods.varquote_aux(name, quotestr='%s')

pydal.helpers.methods.xorify(orderby)

pydal.helpers.regex module

Module contents

Submodules

pydal.base module

This file is part of the web2py Web Framework

Copyrighted by Massimo Di Pierro <mdipierro@cs.depaul.edu>

License: LGPLv3 (http://www.gnu.org/licenses/lgpl.html)

This file contains the DAL support for many relational databases, including:

• SQLite & SpatiaLite
• MySQL
• Postgres
• Firebird
• Oracle
• MS SQL
• DB2
• Interbase
• Ingres
• Informix (9+ and SE)
• SapDB (experimental)
• Cubrid (experimental)
• CouchDB (experimental)
• MongoDB (in progress)
• Google:nosql
• Google:sql
• Teradata
• IMAP (experimental)

Example of usage:

>>> # from dal import DAL, Field

### create DAL connection (and create DB if it doesn't exist)
>>> db = DAL(('sqlite://storage.sqlite','mysql://a:b@localhost/x'),
... folder=None)

### define a table 'person' (create/alter as necessary)
>>> person = db.define_table('person',Field('name','string'))

### insert a record
>>> id = person.insert(name='James')

### retrieve it by id
>>> james = person(id)

### retrieve it by name
>>> james = person(name='James')

### retrieve it by arbitrary query
>>> query = (person.name=='James') & (person.name.startswith('J'))
>>> james = db(query).select(person.ALL)[0]

### update one record
>>> james.update_record(name='Jim')
<Row {'id': 1, 'name': 'Jim'}>

### update multiple records by query
>>> db(person.name.like('J%')).update(name='James')
1

### delete records by query
>>> db(person.name.lower() == 'jim').delete()
0

### retrieve multiple records (rows)
>>> people = db(person).select(orderby=person.name,
... groupby=person.name, limitby=(0,100))

### further filter them
>>> james = people.find(lambda row: row.name == 'James').first()
>>> print james.id, james.name
1 James

### check aggregates
>>> counter = person.id.count()
>>> print db(person).select(counter).first()(counter)
1

### delete one record
>>> james.delete_record()
1

### delete (drop) entire database table
>>> person.drop()

Supported DAL URI strings:

'sqlite://test.db'
'spatialite://test.db'
'sqlite:memory'
'spatialite:memory'
'jdbc:sqlite://test.db'
'mysql://root:none@localhost/test'
'postgres://mdipierro:password@localhost/test'
'postgres:psycopg2://mdipierro:password@localhost/test'
'postgres:pg8000://mdipierro:password@localhost/test'
'jdbc:postgres://mdipierro:none@localhost/test'
'mssql://web2py:none@A64X2/web2py_test'
'mssql2://web2py:none@A64X2/web2py_test' # alternate mappings
'mssql3://web2py:none@A64X2/web2py_test' # better pagination (requires >= 2005)
'mssql4://web2py:none@A64X2/web2py_test' # best pagination (requires >= 2012)
'oracle://username:password@database'
'firebird://user:password@server:3050/database'
'db2:ibm_db_dbi://DSN=dsn;UID=user;PWD=pass'
'db2:pyodbc://driver=DB2;hostname=host;database=database;uid=user;pwd=password;port=port'
'firebird://username:password@hostname/database'
'firebird_embedded://username:password@c://path'
'informix://user:password@server:3050/database'
'informixu://user:password@server:3050/database' # unicode informix
'ingres://database'  # or use an ODBC connection string, e.g. 'ingres://dsn=dsn_name'
'google:datastore' # for google app engine datastore (uses ndb by default)
'google:sql' # for google app engine with sql (mysql compatible)
'teradata://DSN=dsn;UID=user;PWD=pass; DATABASE=database' # experimental
'imap://user:password@server:port' # experimental
'mongodb://user:password@server:port/database' # experimental

For more info:

help(DAL)
help(Field)

class pydal.base.DAL(uri='sqlite://dummy.db', pool_size=0, folder=None, db_codec='UTF-8', check_reserved=None, migrate=True, fake_migrate=False, migrate_enabled=True, fake_migrate_all=False, decode_credentials=False, driver_args=None, adapter_args=None, attempts=5, auto_import=False, bigint_id=False, debug=False, lazy_tables=False, db_uid=None, do_connect=True, after_connection=None, tables=None, ignore_field_case=True, entity_quoting=False, table_hash=None)

Bases: pydal.helpers.classes.Serializable, pydal.helpers.classes.BasicStorage

An instance of this class represents a database connection

Parameters:

• uri (str) –

  contains information for connecting to a database. Defaults to ‘sqlite://dummy.db’

  Note

  experimental: you can specify a dictionary as uri parameter i.e. with:

  db = DAL({"uri": "sqlite://storage.sqlite",
            "tables": {...}, ...})
  

  for an example of dict input you can check the output of the scaffolding db model with

  db.as_dict()

  Note that for compatibility with Python older than version 2.6.5 you should cast your dict input keys to str due to a syntax limitation on kwarg names. for proper DAL dictionary input you can use one of:

  obj = serializers.cast_keys(dict, [encoding="utf-8"])
  #or else (for parsing json input)
  obj = serializers.loads_json(data, unicode_keys=False)
  

• pool_size – How many open connections to make to the database object.
• folder – where .table files will be created. Automatically set within web2py. Use an explicit path when using DAL outside web2py
• db_codec – string encoding of the database (default: ‘UTF-8’)
• table_hash – database identifier with .tables. If your connection hash change you can still using old .tables if they have db_hash as prefix
• check_reserved –

  list of adapters to check tablenames and column names against sql/nosql reserved keywords. Defaults to None

  • ‘common’ List of sql keywords that are common to all database types such as “SELECT, INSERT”. (recommended)
  • ‘all’ Checks against all known SQL keywords
  • ‘<adaptername>’’ Checks against the specific adapters list of keywords
  • ‘<adaptername>_nonreserved’ Checks against the specific adapters list of nonreserved keywords. (if available)
• migrate – sets default migrate behavior for all tables
• fake_migrate – sets default fake_migrate behavior for all tables
• migrate_enabled – If set to False disables ALL migrations
• fake_migrate_all – If set to True fake migrates ALL tables
• attempts – Number of times to attempt connecting
• auto_import – If set to True, tries import automatically table definitions from the databases folder (works only for simple models)
• bigint_id – If set, turn on bigint instead of int for id and reference fields
• lazy_tables – delays table definition until table access
• after_connection – can a callable that will be executed after the connection

Example

Use as:

db = DAL('sqlite://test.db')

or:

db = DAL(**{"uri": ..., "tables": [...]...}) # experimental

db.define_table('tablename', Field('fieldname1'),
                             Field('fieldname2'))

class Row(*args, **kwargs)

Bases: pydal.helpers.classes.BasicStorage

A dictionary that lets you do d[‘a’] as well as d.a this is only used to store a Row

as_dict(datetime_to_str=False, custom_types=None)

as_json(mode='object', default=None, colnames=None, serialize=True, **kwargs)

serializes the row to a JSON object kwargs are passed to .as_dict method only “object” mode supported

serialize = False used by Rows.as_json

TODO: return array mode with query column order

mode and colnames are not implemented

as_xml(row_name='row', colnames=None, indent=' ')

get(key, default=None)

class DAL.Table(db, tablename, *fields, **args)

Bases: pydal.helpers.classes.Serializable, pydal.helpers.classes.BasicStorage

Represents a database table

Example::

You can create a table as::

db = DAL(...) db.define_table(‘users’, Field(‘name’))

And then:

db.users.insert(name='me') # print db.users._insert(...) to see SQL
db.users.drop()

as_dict(flat=False, sanitize=True)

bulk_insert(items)

here items is a list of dictionaries

drop(mode='')

fields

import_from_csv_file(csvfile, id_map=None, null='<NULL>', unique='uuid', id_offset=None, *args, **kwargs)

Import records from csv file. Column headers must have same names as table fields. Field ‘id’ is ignored. If column names read ‘table.file’ the ‘table.’ prefix is ignored.

• ‘unique’ argument is a field which must be unique (typically a uuid field)
• ‘restore’ argument is default False; if set True will remove old values in table first.
• ‘id_map’ if set to None will not map ids

The import will keep the id numbers in the restored table. This assumes that there is an field of type id that is integer and in incrementing order. Will keep the id numbers in restored table.

insert(**fields)

on(query)

sqlsafe

sqlsafe_alias

truncate(mode=None)

update(*args, **kwargs)

update_or_insert(_key=<function <lambda>>, **values)

validate_and_insert(**fields)

validate_and_update(_key=<function <lambda>>, **fields)

validate_and_update_or_insert(_key=<function <lambda>>, **fields)

with_alias(alias)

DAL.as_dict(flat=False, sanitize=True)

DAL.can_join()

DAL.check_reserved_keyword(name)

Validates name against SQL keywords Uses self.check_reserve which is a list of operators to use.

DAL.close()

DAL.commit()

DAL.define_table(tablename, *fields, **args)

static DAL.distributed_transaction_begin(*instances)

static DAL.distributed_transaction_commit(*instances)

DAL.executesql(query, placeholders=None, as_dict=False, fields=None, colnames=None, as_ordered_dict=False)

Executes an arbitrary query

Parameters:

• query (str) – the query to submit to the backend
• placeholders – is optional and will always be None. If using raw SQL with placeholders, placeholders may be a sequence of values to be substituted in or, (if supported by the DB driver), a dictionary with keys matching named placeholders in your SQL.
• as_dict – will always be None when using DAL. If using raw SQL can be set to True and the results cursor returned by the DB driver will be converted to a sequence of dictionaries keyed with the db field names. Results returned with as_dict=True are the same as those returned when applying .to_list() to a DAL query. If “as_ordered_dict”=True the behaviour is the same as when “as_dict”=True with the keys (field names) guaranteed to be in the same order as returned by the select name executed on the database.
• fields –

  list of DAL Fields that match the fields returned from the DB. The Field objects should be part of one or more Table objects defined on the DAL object. The “fields” list can include one or more DAL Table objects in addition to or instead of including Field objects, or it can be just a single table (not in a list). In that case, the Field objects will be extracted from the table(s).

  Note

  if either fields or colnames is provided, the results will be converted to a DAL Rows object using the db._adapter.parse() method

• colnames – list of field names in tablename.fieldname format

Note

It is also possible to specify both “fields” and the associated “colnames”. In that case, “fields” can also include DAL Expression objects in addition to Field objects. For Field objects in “fields”, the associated “colnames” must still be in tablename.fieldname format. For Expression objects in “fields”, the associated “colnames” can be any arbitrary labels.

DAL Table objects referred to by “fields” or “colnames” can be dummy tables and do not have to represent any real tables in the database. Also, note that the “fields” and “colnames” must be in the same order as the fields in the results cursor returned from the DB.

DAL.export_to_csv_file(ofile, *args, **kwargs)

static DAL.get_instances()

Returns a dictionary with uri as key with timings and defined tables:

{'sqlite://storage.sqlite': {
    'dbstats': [(select auth_user.email from auth_user, 0.02009)],
    'dbtables': {
        'defined': ['auth_cas', 'auth_event', 'auth_group',
            'auth_membership', 'auth_permission', 'auth_user'],
        'lazy': '[]'
        }
    }
}

DAL.has_representer(name)

DAL.import_from_csv_file(ifile, id_map=None, null='<NULL>', unique='uuid', map_tablenames=None, ignore_missing_tables=False, *args, **kwargs)

DAL.import_table_definitions(path, migrate=False, fake_migrate=False, tables=None)

DAL.lazy_define_table(tablename, *fields, **args)

DAL.logger = <logging.Logger object>

DAL.parse_as_rest(patterns, args, vars, queries=None, nested_select=True)

Example

Use as:

db.define_table('person',Field('name'),Field('info'))
db.define_table('pet',
    Field('ownedby',db.person),
    Field('name'),Field('info')
)

@request.restful()
def index():
    def GET(*args,**vars):
        patterns = [
            "/friends[person]",
            "/{person.name}/:field",
            "/{person.name}/pets[pet.ownedby]",
            "/{person.name}/pets[pet.ownedby]/{pet.name}",
            "/{person.name}/pets[pet.ownedby]/{pet.name}/:field",
            ("/dogs[pet]", db.pet.info=='dog'),
            ("/dogs[pet]/{pet.name.startswith}", db.pet.info=='dog'),
            ]
        parser = db.parse_as_rest(patterns,args,vars)
        if parser.status == 200:
            return dict(content=parser.response)
        else:
            raise HTTP(parser.status,parser.error)

    def POST(table_name,**vars):
        if table_name == 'person':
            return db.person.validate_and_insert(**vars)
        elif table_name == 'pet':
            return db.pet.validate_and_insert(**vars)
        else:
            raise HTTP(400)
    return locals()

DAL.represent(name, *args, **kwargs)

DAL.representers = {}

DAL.rollback()

DAL.serializers = None

static DAL.set_folder(folder)

DAL.smart_query(fields, text)

DAL.tables

DAL.uuid(x)

DAL.validators = None

DAL.validators_method = None

DAL.where(query=None, ignore_common_filters=None)

pydal.base.DAL_pickler(db)

pydal.base.DAL_unpickler(db_uid)

class pydal.base.MetaDAL

Bases: type

pydal.connection module

class pydal.connection.ConnectionPool

Bases: object

POOLS = {}

after_connection()

after_connection_hook()

Hook for the after_connection parameter

check_active_connection = True

close(action='commit', really=True)

static close_all_instances(action)

to close cleanly databases in a multithreaded environment

find_or_make_work_folder()

reconnect(f=None)

Defines: self.connection and self.cursor if self.pool_size>0 it will try pull the connection from the pool if the connection is not active (closed by db server) it will loop if not self.pool_size or no active connections in pool makes a new one

static set_folder(folder)

pydal.objects module

class pydal.objects.BasicRows

Bases: object

Abstract class for Rows and IterRows

as_csv()

Serializes the table into a csv file

as_dict(key='id', compact=True, storage_to_dict=True, datetime_to_str=False, custom_types=None)

Returns the data as a dictionary of dictionaries (storage_to_dict=True) or records (False)

Parameters:

• key – the name of the field to be used as dict key, normally the id
• compact – ? (default True)
• storage_to_dict – when True returns a dict, otherwise a list(default True)
• datetime_to_str – convert datetime fields as strings (default False)

as_json(mode='object', default=None)

Serializes the rows to a JSON list or object with objects mode=’object’ is not implemented (should return a nested object structure)

as_list(compact=True, storage_to_dict=True, datetime_to_str=False, custom_types=None)

Returns the data as a list or dictionary.

Parameters:

• storage_to_dict – when True returns a dict, otherwise a list
• datetime_to_str – convert datetime fields as strings

as_trees(parent_name='parent_id', children_name='children', render=False)

returns the data as list of trees.

Parameters:

• parent_name – the name of the field holding the reference to the parent (default parent_id).
• children_name – the name where the children of each row will be stored as a list (default children).
• render – whether we will render the fields using their represent (default False) can be a list of fields to render or True to render all.

as_xml(row_name='row', rows_name='rows')

export_to_csv_file(ofile, null='<NULL>', *args, **kwargs)

Exports data to csv, the first line contains the column names

Parameters:

• ofile – where the csv must be exported to
• null – how null values must be represented (default ‘<NULL>’)
• delimiter – delimiter to separate values (default ‘,’)
• quotechar – character to use to quote string values (default ‘”’)
• quoting – quote system, use csv.QUOTE_*** (default csv.QUOTE_MINIMAL)
• represent – use the fields .represent value (default False)
• colnames – list of column names to use (default self.colnames)

This will only work when exporting rows objects!!!! DO NOT use this with db.export_to_csv()

json(mode='object', default=None)

Serializes the rows to a JSON list or object with objects mode=’object’ is not implemented (should return a nested object structure)

xml(strict=False, row_name='row', rows_name='rows')

Serializes the table using sqlhtml.SQLTABLE (if present)

class pydal.objects.Expression(db, op, first=None, second=None, type=None, **optional_args)

Bases: object

abs()

avg()

belongs(*value, **kwattr)

Accepts the following inputs:

field.belongs(1, 2)
field.belongs((1, 2))
field.belongs(query)

Does NOT accept:

field.belongs(1)

If the set you want back includes None values, you can do:

field.belongs((1, None), null=True)

coalesce(*others)

coalesce_zero()

contains(value, all=False, case_sensitive=False)

For GAE contains() is always case sensitive

day()

endswith(value)

epoch()

hour()

ilike(value, escape=None)

len()

like(value, case_sensitive=True, escape=None)

lower()

max()

min()

minutes()

month()

regexp(value)

replace(a, b)

seconds()

st_asgeojson(precision=15, options=0, version=1)

st_astext()

st_contains(value)

st_distance(other)

st_dwithin(value, distance)

st_equals(value)

st_intersects(value)

st_overlaps(value)

st_simplify(value)

st_simplifypreservetopology(value)

st_touches(value)

st_within(value)

st_x()

st_y()

startswith(value)

sum()

upper()

with_alias(alias)

year()

class pydal.objects.Field(fieldname, type='string', length=None, default=<function <lambda>>, required=False, requires=<function <lambda>>, ondelete='CASCADE', notnull=False, unique=False, uploadfield=True, widget=None, label=None, comment=None, writable=True, readable=True, update=None, authorize=None, autodelete=False, represent=None, uploadfolder=None, uploadseparate=False, uploadfs=None, compute=None, custom_store=None, custom_retrieve=None, custom_retrieve_file_properties=None, custom_delete=None, filter_in=None, filter_out=None, custom_qualifier=None, map_none=None, rname=None)

Bases: pydal.objects.Expression, pydal.helpers.classes.Serializable

Lazy

Represents a database field

Example

Usage:

a = Field(name, 'string', length=32, default=None, required=False,
    requires=IS_NOT_EMPTY(), ondelete='CASCADE',
    notnull=False, unique=False,
    uploadfield=True, widget=None, label=None, comment=None,
    uploadfield=True, # True means store on disk,
                      # 'a_field_name' means store in this field in db
                      # False means file content will be discarded.
    writable=True, readable=True, update=None, authorize=None,
    autodelete=False, represent=None, uploadfolder=None,
    uploadseparate=False # upload to separate directories by uuid_keys
                         # first 2 character and tablename.fieldname
                         # False - old behavior
                         # True - put uploaded file in
                         #   <uploaddir>/<tablename>.<fieldname>/uuid_key[:2]
                         #        directory)
    uploadfs=None        # a pyfilesystem where to store upload
    )

to be used as argument of DAL.define_table

alias of FieldMethod

Method

alias of FieldMethod

Virtual

alias of FieldVirtual

as_dict(flat=False, sanitize=True)

clone(point_self_references_to=False, **args)

count(distinct=None)

formatter(value)

retrieve(name, path=None, nameonly=False)

If nameonly==True return (filename, fullfilename) instead of (filename, stream)

retrieve_file_properties(name, path=None)

set_attributes(*args, **attributes)

sqlsafe

sqlsafe_name

store(file, filename=None, path=None)

validate(value)

class pydal.objects.FieldMethod(name, f=None, handler=None)

Bases: object

class pydal.objects.FieldVirtual(name, f=None, ftype='string', label=None, table_name=None)

Bases: object

class pydal.objects.IterRows(db, sql, fields, colnames, blob_decode, cacheable)

Bases: pydal.objects.BasicRows

first()

next()

class pydal.objects.LazyReferenceGetter(table, id)

Bases: object

class pydal.objects.LazySet(field, id)

Bases: object

count(distinct=None, cache=None)

delete()

delete_uploaded_files(upload_fields=None)

isempty()

nested_select(*fields, **attributes)

select(*fields, **attributes)

update(**update_fields)

update_naive(**update_fields)

validate_and_update(**update_fields)

where(query, ignore_common_filters=False)

class pydal.objects.Query(db, op, first=None, second=None, ignore_common_filters=False, **optional_args)

Bases: pydal.helpers.classes.Serializable

Necessary to define a set. It can be stored or can be passed to DAL.__call__() to obtain a Set

Example

Use as:

query = db.users.name=='Max'
set = db(query)
records = set.select()

as_dict(flat=False, sanitize=True)

Experimental stuff

This allows to return a plain dictionary with the basic query representation. Can be used with json/xml services for client-side db I/O

Example

Usage:

q = db.auth_user.id != 0
q.as_dict(flat=True)
{
"op": "NE",
"first":{
    "tablename": "auth_user",
    "fieldname": "id"
    },
"second":0
}

case(t=1, f=0)

class pydal.objects.Row(*args, **kwargs)

Bases: pydal.helpers.classes.BasicStorage

A dictionary that lets you do d[‘a’] as well as d.a this is only used to store a Row

as_dict(datetime_to_str=False, custom_types=None)

as_json(mode='object', default=None, colnames=None, serialize=True, **kwargs)

serializes the row to a JSON object kwargs are passed to .as_dict method only “object” mode supported

serialize = False used by Rows.as_json

TODO: return array mode with query column order

mode and colnames are not implemented

as_xml(row_name='row', colnames=None, indent=' ')

get(key, default=None)

class pydal.objects.Rows(db=None, records=[], colnames=[], compact=True, rawrows=None)

Bases: pydal.objects.BasicRows

A wrapper for the return value of a select. It basically represents a table. It has an iterator and each row is represented as a Row dictionary.

column(column=None)

exclude(f)

Removes elements from the calling Rows object, filtered by the function f, and returns a new Rows object containing the removed elements

find(f, limitby=None)

Returns a new Rows object, a subset of the original object, filtered by the function f

first()

group_by_value(*fields, **args)

Regroups the rows, by one of the fields

last()

render(i=None, fields=None)

Takes an index and returns a copy of the indexed row with values transformed via the “represent” attributes of the associated fields.

Parameters:

• i – index. If not specified, a generator is returned for iteration over all the rows.
• fields – a list of fields to transform (if None, all fields with “represent” attributes will be transformed)

setvirtualfields(**keyed_virtualfields)

For reference:

db.define_table('x', Field('number', 'integer'))
if db(db.x).isempty(): [db.x.insert(number=i) for i in range(10)]

from gluon.dal import lazy_virtualfield

class MyVirtualFields(object):
    # normal virtual field (backward compatible, discouraged)
    def normal_shift(self): return self.x.number+1
    # lazy virtual field (because of @staticmethod)
    @lazy_virtualfield
    def lazy_shift(instance, row, delta=4): return row.x.number+delta
db.x.virtualfields.append(MyVirtualFields())

for row in db(db.x).select():
    print row.number, row.normal_shift, row.lazy_shift(delta=7)

sort(f, reverse=False)

Returns a list of sorted elements (not sorted in place)

class pydal.objects.Set(db, query, ignore_common_filters=None)

Bases: pydal.helpers.classes.Serializable

Represents a set of records in the database. Records are identified by the query=Query(...) object. Normally the Set is generated by DAL.__call__(Query(...))

Given a set, for example:

myset = db(db.users.name=='Max')

you can:

myset.update(db.users.name='Massimo')
myset.delete() # all elements in the set
myset.select(orderby=db.users.id, groupby=db.users.name, limitby=(0, 10))

and take subsets:

subset = myset(db.users.id<5)

as_dict(flat=False, sanitize=True)

build(d)

Experimental: see .parse()

count(distinct=None, cache=None)

delete()

delete_uploaded_files(upload_fields=None)

isempty()

iterselect(*fields, **attributes)

nested_select(*fields, **attributes)

parse(dquery)

Experimental: Turn a dictionary into a Query object

select(*fields, **attributes)

update(**update_fields)

update_naive(**update_fields)

Same as update but does not call table._before_update and _after_update

validate_and_update(**update_fields)

where(query, ignore_common_filters=False)

class pydal.objects.Table(db, tablename, *fields, **args)

Bases: pydal.helpers.classes.Serializable, pydal.helpers.classes.BasicStorage

Represents a database table

Example::

You can create a table as::

db = DAL(...) db.define_table(‘users’, Field(‘name’))

And then:

db.users.insert(name='me') # print db.users._insert(...) to see SQL
db.users.drop()

as_dict(flat=False, sanitize=True)

bulk_insert(items)

here items is a list of dictionaries

drop(mode='')

fields

import_from_csv_file(csvfile, id_map=None, null='<NULL>', unique='uuid', id_offset=None, *args, **kwargs)

Import records from csv file. Column headers must have same names as table fields. Field ‘id’ is ignored. If column names read ‘table.file’ the ‘table.’ prefix is ignored.

• ‘unique’ argument is a field which must be unique (typically a uuid field)
• ‘restore’ argument is default False; if set True will remove old values in table first.
• ‘id_map’ if set to None will not map ids

The import will keep the id numbers in the restored table. This assumes that there is an field of type id that is integer and in incrementing order. Will keep the id numbers in restored table.

insert(**fields)

on(query)

sqlsafe

sqlsafe_alias

truncate(mode=None)

update(*args, **kwargs)

update_or_insert(_key=<function <lambda>>, **values)

validate_and_insert(**fields)

validate_and_update(_key=<function <lambda>>, **fields)

validate_and_update_or_insert(_key=<function <lambda>>, **fields)

with_alias(alias)

class pydal.objects.VirtualCommand(method, row)

Bases: object

pydal.objects.pickle_row(s)

Module contents