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This commit is contained in:
Ruud
2012-02-11 16:28:06 +01:00
parent 3bbf1126c3
commit 02e01fb2d6
217 changed files with 26395 additions and 21194 deletions
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libs/sqlalchemy/ext/__init__.py
+1 -1
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@@ -1,5 +1,5 @@
# ext/__init__.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
libs/sqlalchemy/ext/associationproxy.py
+169 -56
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@@ -1,5 +1,5 @@
# ext/associationproxy.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
@@ -18,33 +18,28 @@ import weakref
from sqlalchemy import exceptions
from sqlalchemy import orm
from sqlalchemy import util
from sqlalchemy.orm import collections
from sqlalchemy.orm import collections, ColumnProperty
from sqlalchemy.sql import not_
def association_proxy(target_collection, attr, **kw):
"""Return a Python property implementing a view of *attr* over a collection.
Implements a read/write view over an instance's *target_collection*,
extracting *attr* from each member of the collection. The property acts
somewhat like this list comprehension::
[getattr(member, *attr*)
for member in getattr(instance, *target_collection*)]
Unlike the list comprehension, the collection returned by the property is
always in sync with *target_collection*, and mutations made to either
collection will be reflected in both.
"""Return a Python property implementing a view of a target
attribute which references an attribute on members of the
target.
The returned value is an instance of :class:`.AssociationProxy`.
Implements a Python property representing a relationship as a collection of
simpler values. The proxied property will mimic the collection type of
simpler values, or a scalar value. The proxied property will mimic the collection type of
the target (list, dict or set), or, in the case of a one to one relationship,
a simple scalar value.
:param target_collection: Name of the relationship attribute we'll proxy to,
usually created with :func:`~sqlalchemy.orm.relationship`.
:param target_collection: Name of the attribute we'll proxy to.
This attribute is typically mapped by
:func:`~sqlalchemy.orm.relationship` to link to a target collection, but
can also be a many-to-one or non-scalar relationship.
:param attr: Attribute on the associated instances we'll proxy for.
:param attr: Attribute on the associated instance or instances we'll proxy for.
For example, given a target collection of [obj1, obj2], a list created
by this proxy property would look like [getattr(obj1, *attr*),
@@ -75,7 +70,7 @@ def association_proxy(target_collection, attr, **kw):
situation.
:param \*\*kw: Passes along any other keyword arguments to
:class:`AssociationProxy`.
:class:`.AssociationProxy`.
"""
return AssociationProxy(target_collection, attr, **kw)
@@ -85,21 +80,23 @@ class AssociationProxy(object):
"""A descriptor that presents a read/write view of an object attribute."""
def __init__(self, target_collection, attr, creator=None,
getset_factory=None, proxy_factory=None, proxy_bulk_set=None):
"""Arguments are:
getset_factory=None, proxy_factory=None,
proxy_bulk_set=None):
"""Construct a new :class:`.AssociationProxy`.
The :func:`.association_proxy` function is provided as the usual
entrypoint here, though :class:`.AssociationProxy` can be instantiated
and/or subclassed directly.
target_collection
Name of the collection we'll proxy to, usually created with
'relationship()' in a mapper setup.
:param target_collection: Name of the collection we'll proxy to,
usually created with :func:`.relationship`.
attr
Attribute on the collected instances we'll proxy for. For example,
:param attr: Attribute on the collected instances we'll proxy for. For example,
given a target collection of [obj1, obj2], a list created by this
proxy property would look like [getattr(obj1, attr), getattr(obj2,
attr)]
creator
Optional. When new items are added to this proxied collection, new
:param creator: Optional. When new items are added to this proxied collection, new
instances of the class collected by the target collection will be
created. For list and set collections, the target class constructor
will be called with the 'value' for the new instance. For dict
@@ -108,8 +105,7 @@ class AssociationProxy(object):
If you want to construct instances differently, supply a 'creator'
function that takes arguments as above and returns instances.
getset_factory
Optional. Proxied attribute access is automatically handled by
:param getset_factory: Optional. Proxied attribute access is automatically handled by
routines that get and set values based on the `attr` argument for
this proxy.
@@ -118,16 +114,14 @@ class AssociationProxy(object):
`setter` functions. The factory is called with two arguments, the
abstract type of the underlying collection and this proxy instance.
proxy_factory
Optional. The type of collection to emulate is determined by
:param proxy_factory: Optional. The type of collection to emulate is determined by
sniffing the target collection. If your collection type can't be
determined by duck typing or you'd like to use a different
collection implementation, you may supply a factory function to
produce those collections. Only applicable to non-scalar relationships.
proxy_bulk_set
Optional, use with proxy_factory. See the _set() method for
details.
:param proxy_bulk_set: Optional, use with proxy_factory. See
the _set() method for details.
"""
self.target_collection = target_collection
@@ -137,33 +131,97 @@ class AssociationProxy(object):
self.proxy_factory = proxy_factory
self.proxy_bulk_set = proxy_bulk_set
self.scalar = None
self.owning_class = None
self.key = '_%s_%s_%s' % (
type(self).__name__, target_collection, id(self))
self.collection_class = None
@property
def remote_attr(self):
"""The 'remote' :class:`.MapperProperty` referenced by this
:class:`.AssociationProxy`.
New in 0.7.3.
See also:
:attr:`.AssociationProxy.attr`
:attr:`.AssociationProxy.local_attr`
"""
return getattr(self.target_class, self.value_attr)
@property
def local_attr(self):
"""The 'local' :class:`.MapperProperty` referenced by this
:class:`.AssociationProxy`.
New in 0.7.3.
See also:
:attr:`.AssociationProxy.attr`
:attr:`.AssociationProxy.remote_attr`
"""
return getattr(self.owning_class, self.target_collection)
@property
def attr(self):
"""Return a tuple of ``(local_attr, remote_attr)``.
This attribute is convenient when specifying a join
using :meth:`.Query.join` across two relationships::
sess.query(Parent).join(*Parent.proxied.attr)
New in 0.7.3.
See also:
:attr:`.AssociationProxy.local_attr`
:attr:`.AssociationProxy.remote_attr`
"""
return (self.local_attr, self.remote_attr)
def _get_property(self):
return (orm.class_mapper(self.owning_class).
get_property(self.target_collection))
@property
@util.memoized_property
def target_class(self):
"""The class the proxy is attached to."""
"""The intermediary class handled by this :class:`.AssociationProxy`.
Intercepted append/set/assignment events will result
in the generation of new instances of this class.
"""
return self._get_property().mapper.class_
def _target_is_scalar(self):
return not self._get_property().uselist
@util.memoized_property
def scalar(self):
"""Return ``True`` if this :class:`.AssociationProxy` proxies a scalar
relationship on the local side."""
scalar = not self._get_property().uselist
if scalar:
self._initialize_scalar_accessors()
return scalar
@util.memoized_property
def _value_is_scalar(self):
return not self._get_property().\
mapper.get_property(self.value_attr).uselist
def __get__(self, obj, class_):
if self.owning_class is None:
self.owning_class = class_ and class_ or type(obj)
if obj is None:
return self
elif self.scalar is None:
self.scalar = self._target_is_scalar()
if self.scalar:
self._initialize_scalar_accessors()
if self.scalar:
return self._scalar_get(getattr(obj, self.target_collection))
@@ -183,10 +241,6 @@ class AssociationProxy(object):
def __set__(self, obj, values):
if self.owning_class is None:
self.owning_class = type(obj)
if self.scalar is None:
self.scalar = self._target_is_scalar()
if self.scalar:
self._initialize_scalar_accessors()
if self.scalar:
creator = self.creator and self.creator or self.target_class
@@ -278,13 +332,63 @@ class AssociationProxy(object):
return self._get_property().comparator
def any(self, criterion=None, **kwargs):
return self._comparator.any(getattr(self.target_class, self.value_attr).has(criterion, **kwargs))
"""Produce a proxied 'any' expression using EXISTS.
This expression will be a composed product
using the :meth:`.RelationshipProperty.Comparator.any`
and/or :meth:`.RelationshipProperty.Comparator.has`
operators of the underlying proxied attributes.
"""
if self._value_is_scalar:
value_expr = getattr(self.target_class, self.value_attr).has(criterion, **kwargs)
else:
value_expr = getattr(self.target_class, self.value_attr).any(criterion, **kwargs)
# check _value_is_scalar here, otherwise
# we're scalar->scalar - call .any() so that
# the "can't call any() on a scalar" msg is raised.
if self.scalar and not self._value_is_scalar:
return self._comparator.has(
value_expr
)
else:
return self._comparator.any(
value_expr
)
def has(self, criterion=None, **kwargs):
return self._comparator.has(getattr(self.target_class, self.value_attr).has(criterion, **kwargs))
"""Produce a proxied 'has' expression using EXISTS.
This expression will be a composed product
using the :meth:`.RelationshipProperty.Comparator.any`
and/or :meth:`.RelationshipProperty.Comparator.has`
operators of the underlying proxied attributes.
"""
return self._comparator.has(
getattr(self.target_class, self.value_attr).\
has(criterion, **kwargs)
)
def contains(self, obj):
return self._comparator.any(**{self.value_attr: obj})
"""Produce a proxied 'contains' expression using EXISTS.
This expression will be a composed product
using the :meth:`.RelationshipProperty.Comparator.any`
, :meth:`.RelationshipProperty.Comparator.has`,
and/or :meth:`.RelationshipProperty.Comparator.contains`
operators of the underlying proxied attributes.
"""
if self.scalar and not self._value_is_scalar:
return self._comparator.has(
getattr(self.target_class, self.value_attr).contains(obj)
)
else:
return self._comparator.any(**{self.value_attr: obj})
def __eq__(self, obj):
return self._comparator.has(**{self.value_attr: obj})
@@ -664,11 +768,20 @@ class _AssociationDict(_AssociationCollection):
len(a))
elif len(a) == 1:
seq_or_map = a[0]
for item in seq_or_map:
if isinstance(item, tuple):
self[item[0]] = item[1]
else:
# discern dict from sequence - took the advice
# from http://www.voidspace.org.uk/python/articles/duck_typing.shtml
# still not perfect :(
if hasattr(seq_or_map, 'keys'):
for item in seq_or_map:
self[item] = seq_or_map[item]
else:
try:
for k, v in seq_or_map:
self[k] = v
except ValueError:
raise ValueError(
"dictionary update sequence "
"requires 2-element tuples")
for key, value in kw:
self[key] = value
libs/sqlalchemy/ext/compiler.py
+174 -3
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@@ -1,5 +1,5 @@
# ext/compiler.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
@@ -91,6 +91,11 @@ Produces::
"INSERT INTO mytable (SELECT mytable.x, mytable.y, mytable.z FROM mytable WHERE mytable.x > :x_1)"
.. note::
The above ``InsertFromSelect`` construct probably wants to have "autocommit"
enabled. See :ref:`enabling_compiled_autocommit` for this step.
Cross Compiling between SQL and DDL compilers
---------------------------------------------
@@ -106,6 +111,50 @@ constraint that embeds a SQL expression::
ddlcompiler.sql_compiler.process(constraint.expression)
)
.. _enabling_compiled_autocommit:
Enabling Autocommit on a Construct
==================================
Recall from the section :ref:`autocommit` that the :class:`.Engine`, when asked to execute
a construct in the absence of a user-defined transaction, detects if the given
construct represents DML or DDL, that is, a data modification or data definition statement, which
requires (or may require, in the case of DDL) that the transaction generated by the DBAPI be committed
(recall that DBAPI always has a transaction going on regardless of what SQLAlchemy does). Checking
for this is actually accomplished
by checking for the "autocommit" execution option on the construct. When building a construct like
an INSERT derivation, a new DDL type, or perhaps a stored procedure that alters data, the "autocommit"
option needs to be set in order for the statement to function with "connectionless" execution
(as described in :ref:`dbengine_implicit`).
Currently a quick way to do this is to subclass :class:`.Executable`, then add the "autocommit" flag
to the ``_execution_options`` dictionary (note this is a "frozen" dictionary which supplies a generative
``union()`` method)::
from sqlalchemy.sql.expression import Executable, ClauseElement
class MyInsertThing(Executable, ClauseElement):
_execution_options = \\
Executable._execution_options.union({'autocommit': True})
More succinctly, if the construct is truly similar to an INSERT, UPDATE, or DELETE, :class:`.UpdateBase`
can be used, which already is a subclass of :class:`.Executable`, :class:`.ClauseElement` and includes the
``autocommit`` flag::
from sqlalchemy.sql.expression import UpdateBase
class MyInsertThing(UpdateBase):
def __init__(self, ...):
...
DDL elements that subclass :class:`.DDLElement` already have the "autocommit" flag turned on.
Changing the default compilation of existing constructs
=======================================================
@@ -147,7 +196,10 @@ Changing Compilation of Types
Subclassing Guidelines
======================
A big part of using the compiler extension is subclassing SQLAlchemy expression constructs. To make this easier, the expression and schema packages feature a set of "bases" intended for common tasks. A synopsis is as follows:
A big part of using the compiler extension is subclassing SQLAlchemy
expression constructs. To make this easier, the expression and
schema packages feature a set of "bases" intended for common tasks.
A synopsis is as follows:
* :class:`~sqlalchemy.sql.expression.ClauseElement` - This is the root
expression class. Any SQL expression can be derived from this base, and is
@@ -201,7 +253,121 @@ A big part of using the compiler extension is subclassing SQLAlchemy expression
can be passed directly to an ``execute()`` method. It is already implicit
within ``DDLElement`` and ``FunctionElement``.
Further Examples
================
"UTC timestamp" function
-------------------------
A function that works like "CURRENT_TIMESTAMP" except applies the appropriate conversions
so that the time is in UTC time. Timestamps are best stored in relational databases
as UTC, without time zones. UTC so that your database doesn't think time has gone
backwards in the hour when daylight savings ends, without timezones because timezones
are like character encodings - they're best applied only at the endpoints of an
application (i.e. convert to UTC upon user input, re-apply desired timezone upon display).
For Postgresql and Microsoft SQL Server::
from sqlalchemy.sql import expression
from sqlalchemy.ext.compiler import compiles
from sqlalchemy.types import DateTime
class utcnow(expression.FunctionElement):
type = DateTime()
@compiles(utcnow, 'postgresql')
def pg_utcnow(element, compiler, **kw):
return "TIMEZONE('utc', CURRENT_TIMESTAMP)"
@compiles(utcnow, 'mssql')
def ms_utcnow(element, compiler, **kw):
return "GETUTCDATE()"
Example usage::
from sqlalchemy import (
Table, Column, Integer, String, DateTime, MetaData
)
metadata = MetaData()
event = Table("event", metadata,
Column("id", Integer, primary_key=True),
Column("description", String(50), nullable=False),
Column("timestamp", DateTime, server_default=utcnow())
)
"GREATEST" function
-------------------
The "GREATEST" function is given any number of arguments and returns the one that is
of the highest value - it's equivalent to Python's ``max`` function. A SQL
standard version versus a CASE based version which only accommodates two
arguments::
from sqlalchemy.sql import expression
from sqlalchemy.ext.compiler import compiles
from sqlalchemy.types import Numeric
class greatest(expression.FunctionElement):
type = Numeric()
name = 'greatest'
@compiles(greatest)
def default_greatest(element, compiler, **kw):
return compiler.visit_function(element)
@compiles(greatest, 'sqlite')
@compiles(greatest, 'mssql')
@compiles(greatest, 'oracle')
def case_greatest(element, compiler, **kw):
arg1, arg2 = list(element.clauses)
return "CASE WHEN %s > %s THEN %s ELSE %s END" % (
compiler.process(arg1),
compiler.process(arg2),
compiler.process(arg1),
compiler.process(arg2),
)
Example usage::
Session.query(Account).\\
filter(
greatest(
Account.checking_balance,
Account.savings_balance) > 10000
)
"false" expression
------------------
Render a "false" constant expression, rendering as "0" on platforms that don't have a "false" constant::
from sqlalchemy.sql import expression
from sqlalchemy.ext.compiler import compiles
class sql_false(expression.ColumnElement):
pass
@compiles(sql_false)
def default_false(element, compiler, **kw):
return "false"
@compiles(sql_false, 'mssql')
@compiles(sql_false, 'mysql')
@compiles(sql_false, 'oracle')
def int_false(element, compiler, **kw):
return "0"
Example usage::
from sqlalchemy import select, union_all
exp = union_all(
select([users.c.name, sql_false().label("enrolled")]),
select([customers.c.name, customers.c.enrolled])
)
"""
from sqlalchemy import exc
def compiles(class_, *specs):
def decorate(fn):
@@ -234,6 +400,11 @@ class _dispatcher(object):
# TODO: yes, this could also switch off of DBAPI in use.
fn = self.specs.get(compiler.dialect.name, None)
if not fn:
fn = self.specs['default']
try:
fn = self.specs['default']
except KeyError:
raise exc.CompileError(
"%s construct has no default "
"compilation handler." % type(element))
return fn(element, compiler, **kw)
libs/sqlalchemy/ext/declarative.py
Regular → Executable
+523 -217
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libs/sqlalchemy/ext/horizontal_shard.py
+56 -53
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@@ -1,5 +1,5 @@
# ext/horizontal_shard.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
@@ -14,16 +14,67 @@ the source distrbution.
"""
import sqlalchemy.exceptions as sa_exc
from sqlalchemy import exc as sa_exc
from sqlalchemy import util
from sqlalchemy.orm.session import Session
from sqlalchemy.orm.query import Query
__all__ = ['ShardedSession', 'ShardedQuery']
class ShardedQuery(Query):
def __init__(self, *args, **kwargs):
super(ShardedQuery, self).__init__(*args, **kwargs)
self.id_chooser = self.session.id_chooser
self.query_chooser = self.session.query_chooser
self._shard_id = None
def set_shard(self, shard_id):
"""return a new query, limited to a single shard ID.
all subsequent operations with the returned query will
be against the single shard regardless of other state.
"""
q = self._clone()
q._shard_id = shard_id
return q
def _execute_and_instances(self, context):
def iter_for_shard(shard_id):
context.attributes['shard_id'] = shard_id
result = self._connection_from_session(
mapper=self._mapper_zero(),
shard_id=shard_id).execute(
context.statement,
self._params)
return self.instances(result, context)
if self._shard_id is not None:
return iter_for_shard(self._shard_id)
else:
partial = []
for shard_id in self.query_chooser(self):
partial.extend(iter_for_shard(shard_id))
# if some kind of in memory 'sorting'
# were done, this is where it would happen
return iter(partial)
def get(self, ident, **kwargs):
if self._shard_id is not None:
return super(ShardedQuery, self).get(ident)
else:
ident = util.to_list(ident)
for shard_id in self.id_chooser(self, ident):
o = self.set_shard(shard_id).get(ident, **kwargs)
if o is not None:
return o
else:
return None
class ShardedSession(Session):
def __init__(self, shard_chooser, id_chooser, query_chooser, shards=None, **kwargs):
def __init__(self, shard_chooser, id_chooser, query_chooser, shards=None,
query_cls=ShardedQuery, **kwargs):
"""Construct a ShardedSession.
:param shard_chooser: A callable which, passed a Mapper, a mapped instance, and possibly a
@@ -45,13 +96,12 @@ class ShardedSession(Session):
objects.
"""
super(ShardedSession, self).__init__(**kwargs)
super(ShardedSession, self).__init__(query_cls=query_cls, **kwargs)
self.shard_chooser = shard_chooser
self.id_chooser = id_chooser
self.query_chooser = query_chooser
self.__binds = {}
self._mapper_flush_opts = {'connection_callable':self.connection}
self._query_cls = ShardedQuery
self.connection_callable = self.connection
if shards is not None:
for k in shards:
self.bind_shard(k, shards[k])
@@ -75,51 +125,4 @@ class ShardedSession(Session):
def bind_shard(self, shard_id, bind):
self.__binds[shard_id] = bind
class ShardedQuery(Query):
def __init__(self, *args, **kwargs):
super(ShardedQuery, self).__init__(*args, **kwargs)
self.id_chooser = self.session.id_chooser
self.query_chooser = self.session.query_chooser
self._shard_id = None
def set_shard(self, shard_id):
"""return a new query, limited to a single shard ID.
all subsequent operations with the returned query will
be against the single shard regardless of other state.
"""
q = self._clone()
q._shard_id = shard_id
return q
def _execute_and_instances(self, context):
if self._shard_id is not None:
result = self.session.connection(
mapper=self._mapper_zero(),
shard_id=self._shard_id).execute(context.statement, self._params)
return self.instances(result, context)
else:
partial = []
for shard_id in self.query_chooser(self):
result = self.session.connection(
mapper=self._mapper_zero(),
shard_id=shard_id).execute(context.statement, self._params)
partial = partial + list(self.instances(result, context))
# if some kind of in memory 'sorting'
# were done, this is where it would happen
return iter(partial)
def get(self, ident, **kwargs):
if self._shard_id is not None:
return super(ShardedQuery, self).get(ident)
else:
ident = util.to_list(ident)
for shard_id in self.id_chooser(self, ident):
o = self.set_shard(shard_id).get(ident, **kwargs)
if o is not None:
return o
else:
return None
libs/sqlalchemy/ext/hybrid.py
+677
View File
@@ -0,0 +1,677 @@
# ext/hybrid.py
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""Define attributes on ORM-mapped classes that have "hybrid" behavior.
"hybrid" means the attribute has distinct behaviors defined at the
class level and at the instance level.
The :mod:`~sqlalchemy.ext.hybrid` extension provides a special form of method
decorator, is around 50 lines of code and has almost no dependencies on the rest
of SQLAlchemy. It can in theory work with any class-level expression generator.
Consider a table ``interval`` as below::
from sqlalchemy import MetaData, Table, Column, Integer
metadata = MetaData()
interval_table = Table('interval', metadata,
Column('id', Integer, primary_key=True),
Column('start', Integer, nullable=False),
Column('end', Integer, nullable=False)
)
We can define higher level functions on mapped classes that produce SQL
expressions at the class level, and Python expression evaluation at the
instance level. Below, each function decorated with :func:`.hybrid_method`
or :func:`.hybrid_property` may receive ``self`` as an instance of the class,
or as the class itself::
from sqlalchemy.ext.hybrid import hybrid_property, hybrid_method
from sqlalchemy.orm import mapper, Session, aliased
class Interval(object):
def __init__(self, start, end):
self.start = start
self.end = end
@hybrid_property
def length(self):
return self.end - self.start
@hybrid_method
def contains(self,point):
return (self.start <= point) & (point < self.end)
@hybrid_method
def intersects(self, other):
return self.contains(other.start) | self.contains(other.end)
mapper(Interval, interval_table)
Above, the ``length`` property returns the difference between the ``end`` and
``start`` attributes. With an instance of ``Interval``, this subtraction occurs
in Python, using normal Python descriptor mechanics::
>>> i1 = Interval(5, 10)
>>> i1.length
5
At the class level, the usual descriptor behavior of returning the descriptor
itself is modified by :class:`.hybrid_property`, to instead evaluate the function
body given the ``Interval`` class as the argument::
>>> print Interval.length
interval."end" - interval.start
>>> print Session().query(Interval).filter(Interval.length > 10)
SELECT interval.id AS interval_id, interval.start AS interval_start,
interval."end" AS interval_end
FROM interval
WHERE interval."end" - interval.start > :param_1
ORM methods such as :meth:`~.Query.filter_by` generally use ``getattr()`` to
locate attributes, so can also be used with hybrid attributes::
>>> print Session().query(Interval).filter_by(length=5)
SELECT interval.id AS interval_id, interval.start AS interval_start,
interval."end" AS interval_end
FROM interval
WHERE interval."end" - interval.start = :param_1
The ``contains()`` and ``intersects()`` methods are decorated with :class:`.hybrid_method`.
This decorator applies the same idea to methods which accept
zero or more arguments. The above methods return boolean values, and take advantage
of the Python ``|`` and ``&`` bitwise operators to produce equivalent instance-level and
SQL expression-level boolean behavior::
>>> i1.contains(6)
True
>>> i1.contains(15)
False
>>> i1.intersects(Interval(7, 18))
True
>>> i1.intersects(Interval(25, 29))
False
>>> print Session().query(Interval).filter(Interval.contains(15))
SELECT interval.id AS interval_id, interval.start AS interval_start,
interval."end" AS interval_end
FROM interval
WHERE interval.start <= :start_1 AND interval."end" > :end_1
>>> ia = aliased(Interval)
>>> print Session().query(Interval, ia).filter(Interval.intersects(ia))
SELECT interval.id AS interval_id, interval.start AS interval_start,
interval."end" AS interval_end, interval_1.id AS interval_1_id,
interval_1.start AS interval_1_start, interval_1."end" AS interval_1_end
FROM interval, interval AS interval_1
WHERE interval.start <= interval_1.start
AND interval."end" > interval_1.start
OR interval.start <= interval_1."end"
AND interval."end" > interval_1."end"
Defining Expression Behavior Distinct from Attribute Behavior
--------------------------------------------------------------
Our usage of the ``&`` and ``|`` bitwise operators above was fortunate, considering
our functions operated on two boolean values to return a new one. In many cases, the construction
of an in-Python function and a SQLAlchemy SQL expression have enough differences that two
separate Python expressions should be defined. The :mod:`~sqlalchemy.ext.hybrid` decorators
define the :meth:`.hybrid_property.expression` modifier for this purpose. As an example we'll
define the radius of the interval, which requires the usage of the absolute value function::
from sqlalchemy import func
class Interval(object):
# ...
@hybrid_property
def radius(self):
return abs(self.length) / 2
@radius.expression
def radius(cls):
return func.abs(cls.length) / 2
Above the Python function ``abs()`` is used for instance-level operations, the SQL function
``ABS()`` is used via the :attr:`.func` object for class-level expressions::
>>> i1.radius
2
>>> print Session().query(Interval).filter(Interval.radius > 5)
SELECT interval.id AS interval_id, interval.start AS interval_start,
interval."end" AS interval_end
FROM interval
WHERE abs(interval."end" - interval.start) / :abs_1 > :param_1
Defining Setters
----------------
Hybrid properties can also define setter methods. If we wanted ``length`` above, when
set, to modify the endpoint value::
class Interval(object):
# ...
@hybrid_property
def length(self):
return self.end - self.start
@length.setter
def length(self, value):
self.end = self.start + value
The ``length(self, value)`` method is now called upon set::
>>> i1 = Interval(5, 10)
>>> i1.length
5
>>> i1.length = 12
>>> i1.end
17
Working with Relationships
--------------------------
There's no essential difference when creating hybrids that work with related objects as
opposed to column-based data. The need for distinct expressions tends to be greater.
Consider the following declarative mapping which relates a ``User`` to a ``SavingsAccount``::
from sqlalchemy import Column, Integer, ForeignKey, Numeric, String
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.hybrid import hybrid_property
Base = declarative_base()
class SavingsAccount(Base):
__tablename__ = 'account'
id = Column(Integer, primary_key=True)
user_id = Column(Integer, ForeignKey('user.id'), nullable=False)
balance = Column(Numeric(15, 5))
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
name = Column(String(100), nullable=False)
accounts = relationship("SavingsAccount", backref="owner")
@hybrid_property
def balance(self):
if self.accounts:
return self.accounts[0].balance
else:
return None
@balance.setter
def balance(self, value):
if not self.accounts:
account = Account(owner=self)
else:
account = self.accounts[0]
account.balance = balance
@balance.expression
def balance(cls):
return SavingsAccount.balance
The above hybrid property ``balance`` works with the first ``SavingsAccount`` entry in the list of
accounts for this user. The in-Python getter/setter methods can treat ``accounts`` as a Python
list available on ``self``.
However, at the expression level, we can't travel along relationships to column attributes
directly since SQLAlchemy is explicit about joins. So here, it's expected that the ``User`` class will be
used in an appropriate context such that an appropriate join to ``SavingsAccount`` will be present::
>>> print Session().query(User, User.balance).join(User.accounts).filter(User.balance > 5000)
SELECT "user".id AS user_id, "user".name AS user_name, account.balance AS account_balance
FROM "user" JOIN account ON "user".id = account.user_id
WHERE account.balance > :balance_1
Note however, that while the instance level accessors need to worry about whether ``self.accounts``
is even present, this issue expresses itself differently at the SQL expression level, where we basically
would use an outer join::
>>> from sqlalchemy import or_
>>> print (Session().query(User, User.balance).outerjoin(User.accounts).
... filter(or_(User.balance < 5000, User.balance == None)))
SELECT "user".id AS user_id, "user".name AS user_name, account.balance AS account_balance
FROM "user" LEFT OUTER JOIN account ON "user".id = account.user_id
WHERE account.balance < :balance_1 OR account.balance IS NULL
.. _hybrid_custom_comparators:
Building Custom Comparators
---------------------------
The hybrid property also includes a helper that allows construction of custom comparators.
A comparator object allows one to customize the behavior of each SQLAlchemy expression
operator individually. They are useful when creating custom types that have
some highly idiosyncratic behavior on the SQL side.
The example class below allows case-insensitive comparisons on the attribute
named ``word_insensitive``::
from sqlalchemy.ext.hybrid import Comparator, hybrid_property
from sqlalchemy import func, Column, Integer, String
from sqlalchemy.orm import Session
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class CaseInsensitiveComparator(Comparator):
def __eq__(self, other):
return func.lower(self.__clause_element__()) == func.lower(other)
class SearchWord(Base):
__tablename__ = 'searchword'
id = Column(Integer, primary_key=True)
word = Column(String(255), nullable=False)
@hybrid_property
def word_insensitive(self):
return self.word.lower()
@word_insensitive.comparator
def word_insensitive(cls):
return CaseInsensitiveComparator(cls.word)
Above, SQL expressions against ``word_insensitive`` will apply the ``LOWER()``
SQL function to both sides::
>>> print Session().query(SearchWord).filter_by(word_insensitive="Trucks")
SELECT searchword.id AS searchword_id, searchword.word AS searchword_word
FROM searchword
WHERE lower(searchword.word) = lower(:lower_1)
The ``CaseInsensitiveComparator`` above implements part of the :class:`.ColumnOperators`
interface. A "coercion" operation like lowercasing can be applied to all comparison operations
(i.e. ``eq``, ``lt``, ``gt``, etc.) using :meth:`.Operators.operate`::
class CaseInsensitiveComparator(Comparator):
def operate(self, op, other):
return op(func.lower(self.__clause_element__()), func.lower(other))
Hybrid Value Objects
--------------------
Note in our previous example, if we were to compare the ``word_insensitive`` attribute of
a ``SearchWord`` instance to a plain Python string, the plain Python string would not
be coerced to lower case - the ``CaseInsensitiveComparator`` we built, being returned
by ``@word_insensitive.comparator``, only applies to the SQL side.
A more comprehensive form of the custom comparator is to construct a *Hybrid Value Object*.
This technique applies the target value or expression to a value object which is then
returned by the accessor in all cases. The value object allows control
of all operations upon the value as well as how compared values are treated, both
on the SQL expression side as well as the Python value side. Replacing the
previous ``CaseInsensitiveComparator`` class with a new ``CaseInsensitiveWord`` class::
class CaseInsensitiveWord(Comparator):
"Hybrid value representing a lower case representation of a word."
def __init__(self, word):
if isinstance(word, basestring):
self.word = word.lower()
elif isinstance(word, CaseInsensitiveWord):
self.word = word.word
else:
self.word = func.lower(word)
def operate(self, op, other):
if not isinstance(other, CaseInsensitiveWord):
other = CaseInsensitiveWord(other)
return op(self.word, other.word)
def __clause_element__(self):
return self.word
def __str__(self):
return self.word
key = 'word'
"Label to apply to Query tuple results"
Above, the ``CaseInsensitiveWord`` object represents ``self.word``, which may be a SQL function,
or may be a Python native. By overriding ``operate()`` and ``__clause_element__()``
to work in terms of ``self.word``, all comparison operations will work against the
"converted" form of ``word``, whether it be SQL side or Python side.
Our ``SearchWord`` class can now deliver the ``CaseInsensitiveWord`` object unconditionally
from a single hybrid call::
class SearchWord(Base):
__tablename__ = 'searchword'
id = Column(Integer, primary_key=True)
word = Column(String(255), nullable=False)
@hybrid_property
def word_insensitive(self):
return CaseInsensitiveWord(self.word)
The ``word_insensitive`` attribute now has case-insensitive comparison behavior
universally, including SQL expression vs. Python expression (note the Python value is
converted to lower case on the Python side here)::
>>> print Session().query(SearchWord).filter_by(word_insensitive="Trucks")
SELECT searchword.id AS searchword_id, searchword.word AS searchword_word
FROM searchword
WHERE lower(searchword.word) = :lower_1
SQL expression versus SQL expression::
>>> sw1 = aliased(SearchWord)
>>> sw2 = aliased(SearchWord)
>>> print Session().query(sw1.word_insensitive, sw2.word_insensitive).filter(sw1.word_insensitive > sw2.word_insensitive)
SELECT lower(searchword_1.word) AS lower_1, lower(searchword_2.word) AS lower_2
FROM searchword AS searchword_1, searchword AS searchword_2
WHERE lower(searchword_1.word) > lower(searchword_2.word)
Python only expression::
>>> ws1 = SearchWord(word="SomeWord")
>>> ws1.word_insensitive == "sOmEwOrD"
True
>>> ws1.word_insensitive == "XOmEwOrX"
False
>>> print ws1.word_insensitive
someword
The Hybrid Value pattern is very useful for any kind of value that may have multiple representations,
such as timestamps, time deltas, units of measurement, currencies and encrypted passwords.
See Also:
`Hybrids and Value Agnostic Types <http://techspot.zzzeek.org/2011/10/21/hybrids-and-value-agnostic-types/>`_ - on the techspot.zzzeek.org blog
`Value Agnostic Types, Part II <http://techspot.zzzeek.org/2011/10/29/value-agnostic-types-part-ii/>`_ - on the techspot.zzzeek.org blog
.. _hybrid_transformers:
Building Transformers
----------------------
A *transformer* is an object which can receive a :class:`.Query` object and return a
new one. The :class:`.Query` object includes a method :meth:`.with_transformation`
that simply returns a new :class:`.Query` transformed by the given function.
We can combine this with the :class:`.Comparator` class to produce one type
of recipe which can both set up the FROM clause of a query as well as assign
filtering criterion.
Consider a mapped class ``Node``, which assembles using adjacency list into a hierarchical
tree pattern::
from sqlalchemy import Column, Integer, ForeignKey
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Node(Base):
__tablename__ = 'node'
id =Column(Integer, primary_key=True)
parent_id = Column(Integer, ForeignKey('node.id'))
parent = relationship("Node", remote_side=id)
Suppose we wanted to add an accessor ``grandparent``. This would return the ``parent`` of
``Node.parent``. When we have an instance of ``Node``, this is simple::
from sqlalchemy.ext.hybrid import hybrid_property
class Node(Base):
# ...
@hybrid_property
def grandparent(self):
return self.parent.parent
For the expression, things are not so clear. We'd need to construct a :class:`.Query` where we
:meth:`~.Query.join` twice along ``Node.parent`` to get to the ``grandparent``. We can instead
return a transforming callable that we'll combine with the :class:`.Comparator` class
to receive any :class:`.Query` object, and return a new one that's joined to the ``Node.parent``
attribute and filtered based on the given criterion::
from sqlalchemy.ext.hybrid import Comparator
class GrandparentTransformer(Comparator):
def operate(self, op, other):
def transform(q):
cls = self.__clause_element__()
parent_alias = aliased(cls)
return q.join(parent_alias, cls.parent).\\
filter(op(parent_alias.parent, other))
return transform
Base = declarative_base()
class Node(Base):
__tablename__ = 'node'
id =Column(Integer, primary_key=True)
parent_id = Column(Integer, ForeignKey('node.id'))
parent = relationship("Node", remote_side=id)
@hybrid_property
def grandparent(self):
return self.parent.parent
@grandparent.comparator
def grandparent(cls):
return GrandparentTransformer(cls)
The ``GrandparentTransformer`` overrides the core :meth:`.Operators.operate` method
at the base of the :class:`.Comparator` hierarchy to return a query-transforming
callable, which then runs the given comparison operation in a particular context.
Such as, in the example above, the ``operate`` method is called, given the
:attr:`.Operators.eq` callable as well as the right side of the comparison
``Node(id=5)``. A function ``transform`` is then returned which will transform
a :class:`.Query` first to join to ``Node.parent``, then to compare ``parent_alias``
using :attr:`.Operators.eq` against the left and right sides, passing into
:class:`.Query.filter`:
.. sourcecode:: pycon+sql
>>> from sqlalchemy.orm import Session
>>> session = Session()
{sql}>>> session.query(Node).\\
... with_transformation(Node.grandparent==Node(id=5)).\\
... all()
SELECT node.id AS node_id, node.parent_id AS node_parent_id
FROM node JOIN node AS node_1 ON node_1.id = node.parent_id
WHERE :param_1 = node_1.parent_id
{stop}
We can modify the pattern to be more verbose but flexible by separating
the "join" step from the "filter" step. The tricky part here is ensuring
that successive instances of ``GrandparentTransformer`` use the same
:class:`.AliasedClass` object against ``Node``. Below we use a simple
memoizing approach that associates a ``GrandparentTransformer``
with each class::
class Node(Base):
# ...
@grandparent.comparator
def grandparent(cls):
# memoize a GrandparentTransformer
# per class
if '_gp' not in cls.__dict__:
cls._gp = GrandparentTransformer(cls)
return cls._gp
class GrandparentTransformer(Comparator):
def __init__(self, cls):
self.parent_alias = aliased(cls)
@property
def join(self):
def go(q):
return q.join(self.parent_alias, Node.parent)
return go
def operate(self, op, other):
return op(self.parent_alias.parent, other)
.. sourcecode:: pycon+sql
{sql}>>> session.query(Node).\\
... with_transformation(Node.grandparent.join).\\
... filter(Node.grandparent==Node(id=5))
SELECT node.id AS node_id, node.parent_id AS node_parent_id
FROM node JOIN node AS node_1 ON node_1.id = node.parent_id
WHERE :param_1 = node_1.parent_id
{stop}
The "transformer" pattern is an experimental pattern that starts
to make usage of some functional programming paradigms.
While it's only recommended for advanced and/or patient developers,
there's probably a whole lot of amazing things it can be used for.
"""
from sqlalchemy import util
from sqlalchemy.orm import attributes, interfaces
class hybrid_method(object):
"""A decorator which allows definition of a Python object method with both
instance-level and class-level behavior.
"""
def __init__(self, func, expr=None):
"""Create a new :class:`.hybrid_method`.
Usage is typically via decorator::
from sqlalchemy.ext.hybrid import hybrid_method
class SomeClass(object):
@hybrid_method
def value(self, x, y):
return self._value + x + y
@value.expression
def value(self, x, y):
return func.some_function(self._value, x, y)
"""
self.func = func
self.expr = expr or func
def __get__(self, instance, owner):
if instance is None:
return self.expr.__get__(owner, owner.__class__)
else:
return self.func.__get__(instance, owner)
def expression(self, expr):
"""Provide a modifying decorator that defines a SQL-expression producing method."""
self.expr = expr
return self
class hybrid_property(object):
"""A decorator which allows definition of a Python descriptor with both
instance-level and class-level behavior.
"""
def __init__(self, fget, fset=None, fdel=None, expr=None):
"""Create a new :class:`.hybrid_property`.
Usage is typically via decorator::
from sqlalchemy.ext.hybrid import hybrid_property
class SomeClass(object):
@hybrid_property
def value(self):
return self._value
@value.setter
def value(self, value):
self._value = value
"""
self.fget = fget
self.fset = fset
self.fdel = fdel
self.expr = expr or fget
util.update_wrapper(self, fget)
def __get__(self, instance, owner):
if instance is None:
return self.expr(owner)
else:
return self.fget(instance)
def __set__(self, instance, value):
if self.fset is None:
raise AttributeError("can't set attribute")
self.fset(instance, value)
def __delete__(self, instance):
if self.fdel is None:
raise AttributeError("can't delete attribute")
self.fdel(instance)
def setter(self, fset):
"""Provide a modifying decorator that defines a value-setter method."""
self.fset = fset
return self
def deleter(self, fdel):
"""Provide a modifying decorator that defines a value-deletion method."""
self.fdel = fdel
return self
def expression(self, expr):
"""Provide a modifying decorator that defines a SQL-expression producing method."""
self.expr = expr
return self
def comparator(self, comparator):
"""Provide a modifying decorator that defines a custom comparator producing method.
The return value of the decorated method should be an instance of
:class:`~.hybrid.Comparator`.
"""
proxy_attr = attributes.\
create_proxied_attribute(self)
def expr(owner):
return proxy_attr(owner, self.__name__, self, comparator(owner))
self.expr = expr
return self
class Comparator(interfaces.PropComparator):
"""A helper class that allows easy construction of custom :class:`~.orm.interfaces.PropComparator`
classes for usage with hybrids."""
def __init__(self, expression):
self.expression = expression
def __clause_element__(self):
expr = self.expression
while hasattr(expr, '__clause_element__'):
expr = expr.__clause_element__()
return expr
def adapted(self, adapter):
# interesting....
return self
libs/sqlalchemy/ext/mutable.py
+563
View File
@@ -0,0 +1,563 @@
# ext/mutable.py
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""Provide support for tracking of in-place changes to scalar values,
which are propagated into ORM change events on owning parent objects.
The :mod:`sqlalchemy.ext.mutable` extension replaces SQLAlchemy's legacy approach to in-place
mutations of scalar values, established by the :class:`.types.MutableType`
class as well as the ``mutable=True`` type flag, with a system that allows
change events to be propagated from the value to the owning parent, thereby
removing the need for the ORM to maintain copies of values as well as the very
expensive requirement of scanning through all "mutable" values on each flush
call, looking for changes.
.. _mutable_scalars:
Establishing Mutability on Scalar Column Values
===============================================
A typical example of a "mutable" structure is a Python dictionary.
Following the example introduced in :ref:`types_toplevel`, we
begin with a custom type that marshals Python dictionaries into
JSON strings before being persisted::
from sqlalchemy.types import TypeDecorator, VARCHAR
import json
class JSONEncodedDict(TypeDecorator):
"Represents an immutable structure as a json-encoded string."
impl = VARCHAR
def process_bind_param(self, value, dialect):
if value is not None:
value = json.dumps(value)
return value
def process_result_value(self, value, dialect):
if value is not None:
value = json.loads(value)
return value
The usage of ``json`` is only for the purposes of example. The :mod:`sqlalchemy.ext.mutable`
extension can be used
with any type whose target Python type may be mutable, including
:class:`.PickleType`, :class:`.postgresql.ARRAY`, etc.
When using the :mod:`sqlalchemy.ext.mutable` extension, the value itself
tracks all parents which reference it. Here we will replace the usage
of plain Python dictionaries with a dict subclass that implements
the :class:`.Mutable` mixin::
import collections
from sqlalchemy.ext.mutable import Mutable
class MutationDict(Mutable, dict):
@classmethod
def coerce(cls, key, value):
"Convert plain dictionaries to MutationDict."
if not isinstance(value, MutationDict):
if isinstance(value, dict):
return MutationDict(value)
# this call will raise ValueError
return Mutable.coerce(key, value)
else:
return value
def __setitem__(self, key, value):
"Detect dictionary set events and emit change events."
dict.__setitem__(self, key, value)
self.changed()
def __delitem__(self, key):
"Detect dictionary del events and emit change events."
dict.__delitem__(self, key)
self.changed()
The above dictionary class takes the approach of subclassing the Python
built-in ``dict`` to produce a dict
subclass which routes all mutation events through ``__setitem__``. There are
many variants on this approach, such as subclassing ``UserDict.UserDict``,
the newer ``collections.MutableMapping``, etc. The part that's important to this
example is that the :meth:`.Mutable.changed` method is called whenever an in-place change to the
datastructure takes place.
We also redefine the :meth:`.Mutable.coerce` method which will be used to
convert any values that are not instances of ``MutationDict``, such
as the plain dictionaries returned by the ``json`` module, into the
appropriate type. Defining this method is optional; we could just as well created our
``JSONEncodedDict`` such that it always returns an instance of ``MutationDict``,
and additionally ensured that all calling code uses ``MutationDict``
explicitly. When :meth:`.Mutable.coerce` is not overridden, any values
applied to a parent object which are not instances of the mutable type
will raise a ``ValueError``.
Our new ``MutationDict`` type offers a class method
:meth:`~.Mutable.as_mutable` which we can use within column metadata
to associate with types. This method grabs the given type object or
class and associates a listener that will detect all future mappings
of this type, applying event listening instrumentation to the mapped
attribute. Such as, with classical table metadata::
from sqlalchemy import Table, Column, Integer
my_data = Table('my_data', metadata,
Column('id', Integer, primary_key=True),
Column('data', MutationDict.as_mutable(JSONEncodedDict))
)
Above, :meth:`~.Mutable.as_mutable` returns an instance of ``JSONEncodedDict``
(if the type object was not an instance already), which will intercept any
attributes which are mapped against this type. Below we establish a simple
mapping against the ``my_data`` table::
from sqlalchemy import mapper
class MyDataClass(object):
pass
# associates mutation listeners with MyDataClass.data
mapper(MyDataClass, my_data)
The ``MyDataClass.data`` member will now be notified of in place changes
to its value.
There's no difference in usage when using declarative::
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class MyDataClass(Base):
__tablename__ = 'my_data'
id = Column(Integer, primary_key=True)
data = Column(MutationDict.as_mutable(JSONEncodedDict))
Any in-place changes to the ``MyDataClass.data`` member
will flag the attribute as "dirty" on the parent object::
>>> from sqlalchemy.orm import Session
>>> sess = Session()
>>> m1 = MyDataClass(data={'value1':'foo'})
>>> sess.add(m1)
>>> sess.commit()
>>> m1.data['value1'] = 'bar'
>>> assert m1 in sess.dirty
True
The ``MutationDict`` can be associated with all future instances
of ``JSONEncodedDict`` in one step, using :meth:`~.Mutable.associate_with`. This
is similar to :meth:`~.Mutable.as_mutable` except it will intercept
all occurrences of ``MutationDict`` in all mappings unconditionally, without
the need to declare it individually::
MutationDict.associate_with(JSONEncodedDict)
class MyDataClass(Base):
__tablename__ = 'my_data'
id = Column(Integer, primary_key=True)
data = Column(JSONEncodedDict)
Supporting Pickling
--------------------
The key to the :mod:`sqlalchemy.ext.mutable` extension relies upon the
placement of a ``weakref.WeakKeyDictionary`` upon the value object, which
stores a mapping of parent mapped objects keyed to the attribute name under
which they are associated with this value. ``WeakKeyDictionary`` objects are
not picklable, due to the fact that they contain weakrefs and function
callbacks. In our case, this is a good thing, since if this dictionary were
picklable, it could lead to an excessively large pickle size for our value
objects that are pickled by themselves outside of the context of the parent.
The developer responsiblity here is only to provide a ``__getstate__`` method
that excludes the :meth:`~.MutableBase._parents` collection from the pickle
stream::
class MyMutableType(Mutable):
def __getstate__(self):
d = self.__dict__.copy()
d.pop('_parents', None)
return d
With our dictionary example, we need to return the contents of the dict itself
(and also restore them on __setstate__)::
class MutationDict(Mutable, dict):
# ....
def __getstate__(self):
return dict(self)
def __setstate__(self, state):
self.update(state)
In the case that our mutable value object is pickled as it is attached to one
or more parent objects that are also part of the pickle, the :class:`.Mutable`
mixin will re-establish the :attr:`.Mutable._parents` collection on each value
object as the owning parents themselves are unpickled.
.. _mutable_composites:
Establishing Mutability on Composites
=====================================
Composites are a special ORM feature which allow a single scalar attribute to
be assigned an object value which represents information "composed" from one
or more columns from the underlying mapped table. The usual example is that of
a geometric "point", and is introduced in :ref:`mapper_composite`.
As of SQLAlchemy 0.7, the internals of :func:`.orm.composite` have been
greatly simplified and in-place mutation detection is no longer enabled by
default; instead, the user-defined value must detect changes on its own and
propagate them to all owning parents. The :mod:`sqlalchemy.ext.mutable`
extension provides the helper class :class:`.MutableComposite`, which is a
slight variant on the :class:`.Mutable` class.
As is the case with :class:`.Mutable`, the user-defined composite class
subclasses :class:`.MutableComposite` as a mixin, and detects and delivers
change events to its parents via the :meth:`.MutableComposite.changed` method.
In the case of a composite class, the detection is usually via the usage of
Python descriptors (i.e. ``@property``), or alternatively via the special
Python method ``__setattr__()``. Below we expand upon the ``Point`` class
introduced in :ref:`mapper_composite` to subclass :class:`.MutableComposite`
and to also route attribute set events via ``__setattr__`` to the
:meth:`.MutableComposite.changed` method::
from sqlalchemy.ext.mutable import MutableComposite
class Point(MutableComposite):
def __init__(self, x, y):
self.x = x
self.y = y
def __setattr__(self, key, value):
"Intercept set events"
# set the attribute
object.__setattr__(self, key, value)
# alert all parents to the change
self.changed()
def __composite_values__(self):
return self.x, self.y
def __eq__(self, other):
return isinstance(other, Point) and \\
other.x == self.x and \\
other.y == self.y
def __ne__(self, other):
return not self.__eq__(other)
The :class:`.MutableComposite` class uses a Python metaclass to automatically
establish listeners for any usage of :func:`.orm.composite` that specifies our
``Point`` type. Below, when ``Point`` is mapped to the ``Vertex`` class,
listeners are established which will route change events from ``Point``
objects to each of the ``Vertex.start`` and ``Vertex.end`` attributes::
from sqlalchemy.orm import composite, mapper
from sqlalchemy import Table, Column
vertices = Table('vertices', metadata,
Column('id', Integer, primary_key=True),
Column('x1', Integer),
Column('y1', Integer),
Column('x2', Integer),
Column('y2', Integer),
)
class Vertex(object):
pass
mapper(Vertex, vertices, properties={
'start': composite(Point, vertices.c.x1, vertices.c.y1),
'end': composite(Point, vertices.c.x2, vertices.c.y2)
})
Any in-place changes to the ``Vertex.start`` or ``Vertex.end`` members
will flag the attribute as "dirty" on the parent object::
>>> from sqlalchemy.orm import Session
>>> sess = Session()
>>> v1 = Vertex(start=Point(3, 4), end=Point(12, 15))
>>> sess.add(v1)
>>> sess.commit()
>>> v1.end.x = 8
>>> assert v1 in sess.dirty
True
Supporting Pickling
--------------------
As is the case with :class:`.Mutable`, the :class:`.MutableComposite` helper
class uses a ``weakref.WeakKeyDictionary`` available via the
:meth:`.MutableBase._parents` attribute which isn't picklable. If we need to
pickle instances of ``Point`` or its owning class ``Vertex``, we at least need
to define a ``__getstate__`` that doesn't include the ``_parents`` dictionary.
Below we define both a ``__getstate__`` and a ``__setstate__`` that package up
the minimal form of our ``Point`` class::
class Point(MutableComposite):
# ...
def __getstate__(self):
return self.x, self.y
def __setstate__(self, state):
self.x, self.y = state
As with :class:`.Mutable`, the :class:`.MutableComposite` augments the
pickling process of the parent's object-relational state so that the
:meth:`.MutableBase._parents` collection is restored to all ``Point`` objects.
"""
from sqlalchemy.orm.attributes import flag_modified
from sqlalchemy import event, types
from sqlalchemy.orm import mapper, object_mapper
from sqlalchemy.util import memoized_property
import weakref
class MutableBase(object):
"""Common base class to :class:`.Mutable` and :class:`.MutableComposite`."""
@memoized_property
def _parents(self):
"""Dictionary of parent object->attribute name on the parent.
This attribute is a so-called "memoized" property. It initializes
itself with a new ``weakref.WeakKeyDictionary`` the first time
it is accessed, returning the same object upon subsequent access.
"""
return weakref.WeakKeyDictionary()
@classmethod
def coerce(cls, key, value):
"""Given a value, coerce it into this type.
By default raises ValueError.
"""
if value is None:
return None
raise ValueError("Attribute '%s' does not accept objects of type %s" % (key, type(value)))
@classmethod
def _listen_on_attribute(cls, attribute, coerce, parent_cls):
"""Establish this type as a mutation listener for the given
mapped descriptor.
"""
key = attribute.key
if parent_cls is not attribute.class_:
return
# rely on "propagate" here
parent_cls = attribute.class_
def load(state, *args):
"""Listen for objects loaded or refreshed.
Wrap the target data member's value with
``Mutable``.
"""
val = state.dict.get(key, None)
if val is not None:
if coerce:
val = cls.coerce(key, val)
state.dict[key] = val
val._parents[state.obj()] = key
def set(target, value, oldvalue, initiator):
"""Listen for set/replace events on the target
data member.
Establish a weak reference to the parent object
on the incoming value, remove it for the one
outgoing.
"""
if not isinstance(value, cls):
value = cls.coerce(key, value)
if value is not None:
value._parents[target.obj()] = key
if isinstance(oldvalue, cls):
oldvalue._parents.pop(target.obj(), None)
return value
def pickle(state, state_dict):
val = state.dict.get(key, None)
if val is not None:
if 'ext.mutable.values' not in state_dict:
state_dict['ext.mutable.values'] = []
state_dict['ext.mutable.values'].append(val)
def unpickle(state, state_dict):
if 'ext.mutable.values' in state_dict:
for val in state_dict['ext.mutable.values']:
val._parents[state.obj()] = key
event.listen(parent_cls, 'load', load, raw=True, propagate=True)
event.listen(parent_cls, 'refresh', load, raw=True, propagate=True)
event.listen(attribute, 'set', set, raw=True, retval=True, propagate=True)
event.listen(parent_cls, 'pickle', pickle, raw=True, propagate=True)
event.listen(parent_cls, 'unpickle', unpickle, raw=True, propagate=True)
class Mutable(MutableBase):
"""Mixin that defines transparent propagation of change
events to a parent object.
See the example in :ref:`mutable_scalars` for usage information.
"""
def changed(self):
"""Subclasses should call this method whenever change events occur."""
for parent, key in self._parents.items():
flag_modified(parent, key)
@classmethod
def associate_with_attribute(cls, attribute):
"""Establish this type as a mutation listener for the given
mapped descriptor.
"""
cls._listen_on_attribute(attribute, True, attribute.class_)
@classmethod
def associate_with(cls, sqltype):
"""Associate this wrapper with all future mapped columns
of the given type.
This is a convenience method that calls ``associate_with_attribute`` automatically.
.. warning::
The listeners established by this method are *global*
to all mappers, and are *not* garbage collected. Only use
:meth:`.associate_with` for types that are permanent to an application,
not with ad-hoc types else this will cause unbounded growth
in memory usage.
"""
def listen_for_type(mapper, class_):
for prop in mapper.iterate_properties:
if hasattr(prop, 'columns'):
if isinstance(prop.columns[0].type, sqltype):
cls.associate_with_attribute(getattr(class_, prop.key))
event.listen(mapper, 'mapper_configured', listen_for_type)
@classmethod
def as_mutable(cls, sqltype):
"""Associate a SQL type with this mutable Python type.
This establishes listeners that will detect ORM mappings against
the given type, adding mutation event trackers to those mappings.
The type is returned, unconditionally as an instance, so that
:meth:`.as_mutable` can be used inline::
Table('mytable', metadata,
Column('id', Integer, primary_key=True),
Column('data', MyMutableType.as_mutable(PickleType))
)
Note that the returned type is always an instance, even if a class
is given, and that only columns which are declared specifically with that
type instance receive additional instrumentation.
To associate a particular mutable type with all occurrences of a
particular type, use the :meth:`.Mutable.associate_with` classmethod
of the particular :meth:`.Mutable` subclass to establish a global
association.
.. warning::
The listeners established by this method are *global*
to all mappers, and are *not* garbage collected. Only use
:meth:`.as_mutable` for types that are permanent to an application,
not with ad-hoc types else this will cause unbounded growth
in memory usage.
"""
sqltype = types.to_instance(sqltype)
def listen_for_type(mapper, class_):
for prop in mapper.iterate_properties:
if hasattr(prop, 'columns'):
if prop.columns[0].type is sqltype:
cls.associate_with_attribute(getattr(class_, prop.key))
event.listen(mapper, 'mapper_configured', listen_for_type)
return sqltype
class _MutableCompositeMeta(type):
def __init__(cls, classname, bases, dict_):
cls._setup_listeners()
return type.__init__(cls, classname, bases, dict_)
class MutableComposite(MutableBase):
"""Mixin that defines transparent propagation of change
events on a SQLAlchemy "composite" object to its
owning parent or parents.
See the example in :ref:`mutable_composites` for usage information.
.. warning::
The listeners established by the :class:`.MutableComposite`
class are *global* to all mappers, and are *not* garbage collected. Only use
:class:`.MutableComposite` for types that are permanent to an application,
not with ad-hoc types else this will cause unbounded growth
in memory usage.
"""
__metaclass__ = _MutableCompositeMeta
def changed(self):
"""Subclasses should call this method whenever change events occur."""
for parent, key in self._parents.items():
prop = object_mapper(parent).get_property(key)
for value, attr_name in zip(
self.__composite_values__(),
prop._attribute_keys):
setattr(parent, attr_name, value)
@classmethod
def _setup_listeners(cls):
"""Associate this wrapper with all future mapped composites
of the given type.
This is a convenience method that calls ``associate_with_attribute`` automatically.
"""
def listen_for_type(mapper, class_):
for prop in mapper.iterate_properties:
if hasattr(prop, 'composite_class') and issubclass(prop.composite_class, cls):
cls._listen_on_attribute(getattr(class_, prop.key), False, class_)
event.listen(mapper, 'mapper_configured', listen_for_type)
libs/sqlalchemy/ext/orderinglist.py
+4 -2
View File
@@ -1,5 +1,5 @@
# ext/orderinglist.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
@@ -73,7 +73,9 @@ Use the ``ordering_list`` function to set up the ``collection_class`` on relatio
(as in the mapper example above). This implementation depends on the list
starting in the proper order, so be SURE to put an order_by on your relationship.
.. warning:: ``ordering_list`` only provides limited functionality when a primary
.. warning::
``ordering_list`` only provides limited functionality when a primary
key column or unique column is the target of the sort. Since changing the order of
entries often means that two rows must trade values, this is not possible when
the value is constrained by a primary key or unique constraint, since one of the rows
libs/sqlalchemy/ext/serializer.py
+1 -1
View File
@@ -1,5 +1,5 @@
# ext/serializer.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
libs/sqlalchemy/ext/sqlsoup.py
+25 -8
View File
@@ -1,10 +1,24 @@
# ext/sqlsoup.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""
.. note::
SQLSoup is now its own project. Documentation
and project status are available at:
http://pypi.python.org/pypi/sqlsoup
http://readthedocs.org/docs/sqlsoup
SQLSoup will no longer be included with SQLAlchemy as of
version 0.8.
Introduction
============
@@ -152,7 +166,7 @@ construction rules apply here as to the select methods::
You can similarly update multiple rows at once. This will change the
book_id to 1 in all loans whose book_id is 2::
>>> db.loans.update(db.loans.book_id==2, book_id=1)
>>> db.loans.filter_by(db.loans.book_id==2).update({'book_id':1})
>>> db.loans.filter_by(book_id=1).all()
[MappedLoans(book_id=1,user_name=u'Joe Student',
loan_date=datetime.datetime(2006, 7, 12, 0, 0))]
@@ -245,8 +259,10 @@ Advanced Use
Sessions, Transations and Application Integration
-------------------------------------------------
**Note:** please read and understand this section thoroughly
before using SqlSoup in any web application.
.. note::
Please read and understand this section thoroughly
before using SqlSoup in any web application.
SqlSoup uses a ScopedSession to provide thread-local sessions.
You can get a reference to the current one like this::
@@ -365,9 +381,9 @@ from sqlalchemy import schema, sql, util
from sqlalchemy.engine.base import Engine
from sqlalchemy.orm import scoped_session, sessionmaker, mapper, \
class_mapper, relationship, session,\
object_session
object_session, attributes
from sqlalchemy.orm.interfaces import MapperExtension, EXT_CONTINUE
from sqlalchemy.exceptions import SQLAlchemyError, InvalidRequestError, ArgumentError
from sqlalchemy.exc import SQLAlchemyError, InvalidRequestError, ArgumentError
from sqlalchemy.sql import expression
@@ -390,7 +406,8 @@ class AutoAdd(MapperExtension):
def init_instance(self, mapper, class_, oldinit, instance, args, kwargs):
session = self.scoped_session()
session._save_without_cascade(instance)
state = attributes.instance_state(instance)
session._save_impl(state)
return EXT_CONTINUE
def init_failed(self, mapper, class_, oldinit, instance, args, kwargs):
@@ -619,7 +636,7 @@ class SqlSoup(object):
self.session.expunge_all()
def map_to(self, attrname, tablename=None, selectable=None,
schema=None, base=None, mapper_args=util.frozendict()):
schema=None, base=None, mapper_args=util.immutabledict()):
"""Configure a mapping to the given attrname.
This is the "master" method that can be used to create any