SQLAlchemy 0.4 Documentation

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Version: 0.4.2b Last Updated: 01/07/08 15:05:25

module sqlalchemy.orm.collections

Support for collections of mapped entities.

The collections package supplies the machinery used to inform the ORM of collection membership changes. An instrumentation via decoration approach is used, allowing arbitrary types (including built-ins) to be used as entity collections without requiring inheritance from a base class.

Instrumentation decoration relays membership change events to the InstrumentedCollectionAttribute that is currently managing the collection. The decorators observe function call arguments and return values, tracking entities entering or leaving the collection. Two decorator approaches are provided. One is a bundle of generic decorators that map function arguments and return values to events:

from sqlalchemy.orm.collections import collection
class MyClass(object):
    # ...

    @collection.adds(1)
    def store(self, item):
        self.data.append(item)

    @collection.removes_return()
    def pop(self):
        return self.data.pop()

The second approach is a bundle of targeted decorators that wrap appropriate append and remove notifiers around the mutation methods present in the standard Python list, set and dict interfaces. These could be specified in terms of generic decorator recipes, but are instead hand-tooled for increased efficiency. The targeted decorators occasionally implement adapter-like behavior, such as mapping bulk-set methods (extend, update, __setslice, etc.) into the series of atomic mutation events that the ORM requires.

The targeted decorators are used internally for automatic instrumentation of entity collection classes. Every collection class goes through a transformation process roughly like so:

  1. If the class is a built-in, substitute a trivial sub-class
  2. Is this class already instrumented?
  3. Add in generic decorators
  4. Sniff out the collection interface through duck-typing
  5. Add targeted decoration to any undecorated interface method

This process modifies the class at runtime, decorating methods and adding some bookkeeping properties. This isn't possible (or desirable) for built-in classes like list, so trivial sub-classes are substituted to hold decoration:

class InstrumentedList(list):
    pass

Collection classes can be specified in relation(collection_class=) as types or a function that returns an instance. Collection classes are inspected and instrumented during the mapper compilation phase. The collection_class callable will be executed once to produce a specimen instance, and the type of that specimen will be instrumented. Functions that return built-in types like lists will be adapted to produce instrumented instances.

When extending a known type like list, additional decorations are not generally not needed. Odds are, the extension method will delegate to a method that's already instrumented. For example:

class QueueIsh(list):
   def push(self, item):
       self.append(item)
   def shift(self):
       return self.pop(0)

There's no need to decorate these methods. append and pop are already instrumented as part of the list interface. Decorating them would fire duplicate events, which should be avoided.

The targeted decoration tries not to rely on other methods in the underlying collection class, but some are unavoidable. Many depend on 'read' methods being present to properly instrument a 'write', for example, __setitem__ needs __getitem__. "Bulk" methods like update and extend may also reimplemented in terms of atomic appends and removes, so the extend decoration will actually perform many append operations and not call the underlying method at all.

Tight control over bulk operation and the firing of events is also possible by implementing the instrumentation internally in your methods. The basic instrumentation package works under the general assumption that collection mutation will not raise unusual exceptions. If you want to closely orchestrate append and remove events with exception management, internal instrumentation may be the answer. Within your method, collection_adapter(self) will retrieve an object that you can use for explicit control over triggering append and remove events.

The owning object and InstrumentedCollectionAttribute are also reachable through the adapter, allowing for some very sophisticated behavior.

Module Functions

def attribute_mapped_collection(attr_name)

A dictionary-based collection type with attribute-based keying.

Returns a MappedCollection factory with a keying based on the 'attr_name' attribute of entities in the collection.

The key value must be immutable for the lifetime of the object. You can not, for example, map on foreign key values if those key values will change during the session, i.e. from None to a database-assigned integer after a session flush.

def collection_adapter(collection)

Fetch the CollectionAdapter for a collection.

def column_mapped_collection(mapping_spec)

A dictionary-based collection type with column-based keying.

Returns a MappedCollection factory with a keying function generated from mapping_spec, which may be a Column or a sequence of Columns.

The key value must be immutable for the lifetime of the object. You can not, for example, map on foreign key values if those key values will change during the session, i.e. from None to a database-assigned integer after a session flush.

def mapped_collection(keyfunc)

A dictionary-based collection type with arbitrary keying.

Returns a MappedCollection factory with a keying function generated from keyfunc, a callable that takes an entity and returns a key value.

The key value must be immutable for the lifetime of the object. You can not, for example, map on foreign key values if those key values will change during the session, i.e. from None to a database-assigned integer after a session flush.

class collection(object)

Decorators for entity collection classes.

The decorators fall into two groups: annotations and interception recipes.

The annotating decorators (appender, remover, iterator, internally_instrumented, on_link) indicate the method's purpose and take no arguments. They are not written with parens:

@collection.appender
def append(self, append): ...

The recipe decorators all require parens, even those that take no arguments:

@collection.adds('entity'):
def insert(self, position, entity): ...

@collection.removes_return()
def popitem(self): ...

Decorators can be specified in long-hand for Python 2.3, or with the class-level dict attribute '__instrumentation__'- see the source for details.

def adds(cls, arg)

Mark the method as adding an entity to the collection.

Adds "add to collection" handling to the method. The decorator argument indicates which method argument holds the SQLAlchemy-relevant value. Arguments can be specified positionally (i.e. integer) or by name:

@collection.adds(1)
def push(self, item): ...

@collection.adds('entity')
def do_stuff(self, thing, entity=None): ...
def appender(cls, fn)

Tag the method as the collection appender.

The appender method is called with one positional argument: the value to append. The method will be automatically decorated with 'adds(1)' if not already decorated:

@collection.appender
def add(self, append): ...

# or, equivalently
@collection.appender
@collection.adds(1)
def add(self, append): ...

# for mapping type, an 'append' may kick out a previous value
# that occupies that slot.  consider d['a'] = 'foo'- any previous
# value in d['a'] is discarded.
@collection.appender
@collection.replaces(1)
def add(self, entity):
    key = some_key_func(entity)
    previous = None
    if key in self:
        previous = self[key]
    self[key] = entity
    return previous

If the value to append is not allowed in the collection, you may raise an exception. Something to remember is that the appender will be called for each object mapped by a database query. If the database contains rows that violate your collection semantics, you will need to get creative to fix the problem, as access via the collection will not work.

If the appender method is internally instrumented, you must also receive the keyword argument '_sa_initiator' and ensure its promulgation to collection events.

def converter(cls, fn)

Tag the method as the collection converter.

This optional method will be called when a collection is being replaced entirely, as in:

myobj.acollection = [newvalue1, newvalue2]

The converter method will receive the object being assigned and should return an iterable of values suitable for use by the appender method. A converter must not assign values or mutate the collection, it's sole job is to adapt the value the user provides into an iterable of values for the ORM's use.

The default converter implementation will use duck-typing to do the conversion. A dict-like collection will be convert into an iterable of dictionary values, and other types will simply be iterated.

@collection.converter def convert(self, other): ...

If the duck-typing of the object does not match the type of this collection, a TypeError is raised.

Supply an implementation of this method if you want to expand the range of possible types that can be assigned in bulk or perform validation on the values about to be assigned.

def internally_instrumented(cls, fn)

Tag the method as instrumented.

This tag will prevent any decoration from being applied to the method. Use this if you are orchestrating your own calls to collection_adapter in one of the basic SQLAlchemy interface methods, or to prevent an automatic ABC method decoration from wrapping your implementation:

# normally an 'extend' method on a list-like class would be
# automatically intercepted and re-implemented in terms of
# SQLAlchemy events and append().  your implementation will
# never be called, unless:
@collection.internally_instrumented
def extend(self, items): ...
def iterator(cls, fn)

Tag the method as the collection remover.

The iterator method is called with no arguments. It is expected to return an iterator over all collection members:

@collection.iterator
def __iter__(self): ...
def on_link(cls, fn)

Tag the method as a the "linked to attribute" event handler.

This optional event handler will be called when the collection class is linked to or unlinked from the InstrumentedAttribute. It is invoked immediately after the '_sa_adapter' property is set on the instance. A single argument is passed: the collection adapter that has been linked, or None if unlinking.

def remover(cls, fn)

Tag the method as the collection remover.

The remover method is called with one positional argument: the value to remove. The method will be automatically decorated with 'removes_return()' if not already decorated:

@collection.remover
def zap(self, entity): ...

# or, equivalently
@collection.remover
@collection.removes_return()
def zap(self, ): ...

If the value to remove is not present in the collection, you may raise an exception or return None to ignore the error.

If the remove method is internally instrumented, you must also receive the keyword argument '_sa_initiator' and ensure its promulgation to collection events.

def removes(cls, arg)

Mark the method as removing an entity in the collection.

Adds "remove from collection" handling to the method. The decorator argument indicates which method argument holds the SQLAlchemy-relevant value to be removed. Arguments can be specified positionally (i.e. integer) or by name:

@collection.removes(1)
def zap(self, item): ...

For methods where the value to remove is not known at call-time, use collection.removes_return.

def removes_return(cls)

Mark the method as removing an entity in the collection.

Adds "remove from collection" handling to the method. The return value of the method, if any, is considered the value to remove. The method arguments are not inspected:

@collection.removes_return()
def pop(self): ...

For methods where the value to remove is known at call-time, use collection.remove.

def replaces(cls, arg)

Mark the method as replacing an entity in the collection.

Adds "add to collection" and "remove from collection" handling to the method. The decorator argument indicates which method argument holds the SQLAlchemy-relevant value to be added, and return value, if any will be considered the value to remove.

Arguments can be specified positionally (i.e. integer) or by name:

@collection.replaces(2)
def __setitem__(self, index, item): ...
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class MappedCollection(dict)

A basic dictionary-based collection class.

Extends dict with the minimal bag semantics that collection classes require. set and remove are implemented in terms of a keying function: any callable that takes an object and returns an object for use as a dictionary key.

def __init__(self, keyfunc)

Create a new collection with keying provided by keyfunc.

keyfunc may be any callable any callable that takes an object and returns an object for use as a dictionary key.

The keyfunc will be called every time the ORM needs to add a member by value-only (such as when loading instances from the database) or remove a member. The usual cautions about dictionary keying apply- keyfunc(object) should return the same output for the life of the collection. Keying based on mutable properties can result in unreachable instances "lost" in the collection.

def remove(self, value, _sa_initiator=None)

Remove an item from the collection by value, consulting this instance's keyfunc for the key.

def set(self, value, _sa_initiator=None)

Add an item to the collection, with a key provided by this instance's keyfunc.

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class CollectionAdapter(object)

Bridges between the ORM and arbitrary Python collections.

Proxies base-level collection operations (append, remove, iterate) to the underlying Python collection, and emits add/remove events for entities entering or leaving the collection.

The ORM uses an CollectionAdapter exclusively for interaction with entity collections.

def __init__(self, attr, owner_state, data)

Construct a new CollectionAdapter.

def adapt_like_to_iterable(self, obj)

Converts collection-compatible objects to an iterable of values.

Can be passed any type of object, and if the underlying collection determines that it can be adapted into a stream of values it can use, returns an iterable of values suitable for append()ing.

This method may raise TypeError or any other suitable exception if adaptation fails.

If a converter implementation is not supplied on the collection, a default duck-typing-based implementation is used.

def append_with_event(self, item, initiator=None)

Add an entity to the collection, firing mutation events.

def append_without_event(self, item)

Add or restore an entity to the collection, firing no events.

def clear_with_event(self, initiator=None)

Empty the collection, firing a mutation event for each entity.

def clear_without_event(self)

Empty the collection, firing no events.

data = property()

The entity collection being adapted.

def fire_append_event(self, item, initiator=None)

Notify that a entity has entered the collection.

Initiator is the InstrumentedAttribute that initiated the membership mutation, and should be left as None unless you are passing along an initiator value from a chained operation.

def fire_pre_remove_event(self, initiator=None)

Notify that an entity is about to be removed from the collection.

Only called if the entity cannot be removed after calling fire_remove_event().

def fire_remove_event(self, item, initiator=None)

Notify that a entity has been removed from the collection.

Initiator is the InstrumentedAttribute that initiated the membership mutation, and should be left as None unless you are passing along an initiator value from a chained operation.

def link_to_self(self, data)

Link a collection to this adapter, and fire a link event.

def remove_with_event(self, item, initiator=None)

Remove an entity from the collection, firing mutation events.

def remove_without_event(self, item)

Remove an entity from the collection, firing no events.

def unlink(self, data)

Unlink a collection from any adapter, and fire a link event.

def __iter__(self)

Iterate over entities in the collection.

def __len__(self)

Count entities in the collection.

def __nonzero__(self)
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