1. Ben Trofatter
  2. sqlalchemy-1753


sqlalchemy-1753 / doc / build / changelog / migration_08.rst

What's New in SQLAlchemy 0.8?

About this Document

This document describes changes between SQLAlchemy version 0.7, undergoing maintenance releases as of October, 2012, and SQLAlchemy version 0.8, which is expected for release in late 2012.

Document date: October 25, 2012


This guide introduces what's new in SQLAlchemy version 0.8, and also documents changes which affect users migrating their applications from the 0.7 series of SQLAlchemy to 0.8.

SQLAlchemy releases are closing in on 1.0, and each new version since 0.5 features fewer major usage changes. Most applications that are settled into modern 0.7 patterns should be movable to 0.8 with no changes. Applications that use 0.6 and even 0.5 patterns should be directly migratable to 0.8 as well, though larger applications may want to test with each interim version.

Platform Support

Targeting Python 2.5 and Up Now

SQLAlchemy 0.8 will target Python 2.5 and forward; compatibility for Python 2.4 is being dropped.

The internals will be able to make usage of Python ternaries (that is, x if y else z) which will improve things versus the usage of y and x or z, which naturally has been the source of some bugs, as well as context managers (that is, with:) and perhaps in some cases try:/except:/else: blocks which will help with code readability.

SQLAlchemy will eventually drop 2.5 support as well - when 2.6 is reached as the baseline, SQLAlchemy will move to use 2.6/3.3 in-place compatibility, removing the usage of the 2to3 tool and maintaining a source base that works with Python 2 and 3 at the same time.

New ORM Features

Rewritten :func:`.relationship` mechanics

0.8 features a much improved and capable system regarding how :func:`.relationship` determines how to join between two entities. The new system includes these features:

  • The primaryjoin argument is no longer needed when constructing a :func:`.relationship` against a class that has multiple foreign key paths to the target. Only the foreign_keys argument is needed to specify those columns which should be included:

    class Parent(Base):
        __tablename__ = 'parent'
        id = Column(Integer, primary_key=True)
        child_id_one = Column(Integer, ForeignKey('child.id'))
        child_id_two = Column(Integer, ForeignKey('child.id'))
        child_one = relationship("Child", foreign_keys=child_id_one)
        child_two = relationship("Child", foreign_keys=child_id_two)
    class Child(Base):
        __tablename__ = 'child'
        id = Column(Integer, primary_key=True)
  • relationships against self-referential, composite foreign keys where a column points to itself are now supported. The canonical case is as follows:

    class Folder(Base):
        __tablename__ = 'folder'
        __table_args__ = (
              ['account_id', 'parent_id'],
              ['folder.account_id', 'folder.folder_id']),
        account_id = Column(Integer, primary_key=True)
        folder_id = Column(Integer, primary_key=True)
        parent_id = Column(Integer)
        name = Column(String)
        parent_folder = relationship("Folder",
                            remote_side=[account_id, folder_id]

    Above, the Folder refers to its parent Folder joining from account_id to itself, and parent_id to folder_id. When SQLAlchemy constructs an auto- join, no longer can it assume all columns on the "remote" side are aliased, and all columns on the "local" side are not - the account_id column is on both sides. So the internal relationship mechanics were totally rewritten to support an entirely different system whereby two copies of account_id are generated, each containing different annotations to determine their role within the statement. Note the join condition within a basic eager load:

        folder.account_id AS folder_account_id,
        folder.folder_id AS folder_folder_id,
        folder.parent_id AS folder_parent_id,
        folder.name AS folder_name,
        folder_1.account_id AS folder_1_account_id,
        folder_1.folder_id AS folder_1_folder_id,
        folder_1.parent_id AS folder_1_parent_id,
        folder_1.name AS folder_1_name
    FROM folder
        LEFT OUTER JOIN folder AS folder_1
            folder_1.account_id = folder.account_id
            AND folder.folder_id = folder_1.parent_id
    WHERE folder.folder_id = ? AND folder.account_id = ?
  • Thanks to the new relationship mechanics, new annotation functions :func:`.foreign` and :func:`.remote` are provided which can be used to create primaryjoin conditions involving any kind of SQL function, CAST, or other construct that wraps the target column. Previously, a semi-public argument _local_remote_pairs would be used to tell :func:`.relationship` unambiguously what columns should be considered as corresponding to the mapping - the annotations make the point more directly, such as below where Parent joins to Child by matching the Parent.name column converted to lower case to that of the Child.name_upper column:

    class Parent(Base):
        __tablename__ = 'parent'
        id = Column(Integer, primary_key=True)
        name = Column(String)
        children = relationship("Child",
    class Child(Base):
        __tablename__ = 'child'
        id = Column(Integer, primary_key=True)
        name_upper = Column(String)

:ticket:`1401` :ticket:`610`

New Class/Object Inspection System

Lots of SQLAlchemy users are writing systems that require the ability to inspect the attributes of a mapped class, including being able to get at the primary key columns, object relationships, plain attributes, and so forth, typically for the purpose of building data-marshalling systems, like JSON/XML conversion schemes and of course form libraries galore.

Originally, the :class:`.Table` and :class:`.Column` model were the original inspection points, which have a well-documented system. While SQLAlchemy ORM models are also fully introspectable, this has never been a fully stable and supported feature, and users tended to not have a clear idea how to get at this information.

0.8 now provides a consistent, stable and fully documented API for this purpose, including an inspection system which works on mapped classes, instances, attributes, and other Core and ORM constructs. The entrypoint to this system is the core-level :func:`.inspect` function. In most cases, the object being inspected is one already part of SQLAlchemy's system, such as :class:`.Mapper`, :class:`.InstanceState`, :class:`.Inspector`. In some cases, new objects have been added with the job of providing the inspection API in certain contexts, such as :class:`.AliasedInsp` and :class:`.AttributeState`.

A walkthrough of some key capabilities follows:

>>> class User(Base):
...     __tablename__ = 'user'
...     id = Column(Integer, primary_key=True)
...     name = Column(String)
...     name_syn = synonym(name)
...     addresses = relationship("Address")

>>> # universal entry point is inspect()
>>> b = inspect(User)

>>> # b in this case is the Mapper
>>> b
<Mapper at 0x101521950; User>

>>> # Column namespace
>>> b.columns.id
Column('id', Integer(), table=<user>, primary_key=True, nullable=False)

>>> # mapper's perspective of the primary key
>>> b.primary_key
(Column('id', Integer(), table=<user>, primary_key=True, nullable=False),)

>>> # MapperProperties available from .attrs
>>> b.attrs.keys()
['name_syn', 'addresses', 'id', 'name']

>>> # .column_attrs, .relationships, etc. filter this collection
>>> b.column_attrs.keys()
['id', 'name']

>>> list(b.relationships)
[<sqlalchemy.orm.properties.RelationshipProperty object at 0x1015212d0>]

>>> # they are also namespaces
>>> b.column_attrs.id
<sqlalchemy.orm.properties.ColumnProperty object at 0x101525090>

>>> b.relationships.addresses
<sqlalchemy.orm.properties.RelationshipProperty object at 0x1015212d0>

>>> # point inspect() at a mapped, class level attribute,
>>> # returns the attribute itself
>>> b = inspect(User.addresses)
>>> b
<sqlalchemy.orm.attributes.InstrumentedAttribute object at 0x101521fd0>

>>> # From here we can get the mapper:
>>> b.mapper
<Mapper at 0x101525810; Address>

>>> # the parent inspector, in this case a mapper
>>> b.parent
<Mapper at 0x101521950; User>

>>> # an expression
>>> print b.expression
"user".id = address.user_id

>>> # inspect works on instances
>>> u1 = User(id=3, name='x')
>>> b = inspect(u1)

>>> # it returns the InstanceState
>>> b
<sqlalchemy.orm.state.InstanceState object at 0x10152bed0>

>>> # similar attrs accessor refers to the
>>> b.attrs.keys()
['id', 'name_syn', 'addresses', 'name']

>>> # attribute interface - from attrs, you get a state object
>>> b.attrs.id
<sqlalchemy.orm.state.AttributeState object at 0x10152bf90>

>>> # this object can give you, current value...
>>> b.attrs.id.value

>>> # ... current history
>>> b.attrs.id.history
History(added=[3], unchanged=(), deleted=())

>>> # InstanceState can also provide session state information
>>> # lets assume the object is persistent
>>> s = Session()
>>> s.add(u1)
>>> s.commit()

>>> # now we can get primary key identity, always
>>> # works in query.get()
>>> b.identity

>>> # the mapper level key
>>> b.identity_key
(<class '__main__.User'>, (3,))

>>> # state within the session
>>> b.persistent, b.transient, b.deleted, b.detached
(True, False, False, False)

>>> # owning session
>>> b.session
<sqlalchemy.orm.session.Session object at 0x101701150>


New with_polymorphic() feature, can be used anywhere

The :meth:`.Query.with_polymorphic` method allows the user to specify which tables should be present when querying against a joined-table entity. Unfortunately the method is awkward and only applies to the first entity in the list, and otherwise has awkward behaviors both in usage as well as within the internals. A new enhancement to the :func:`.aliased` construct has been added called :func:`.with_polymorphic` which allows any entity to be "aliased" into a "polymorphic" version of itself, freely usable anywhere:

from sqlalchemy.orm import with_polymorphic
palias = with_polymorphic(Person, [Engineer, Manager])
            join(palias, Company.employees).\
            filter(or_(Engineer.language=='java', Manager.hair=='pointy'))


of_type() works with alias(), with_polymorphic(), any(), has(), joinedload(), subqueryload(), contains_eager()

The :meth:`.PropComparator.of_type` method is used to specify a specific subtype to use when constructing SQL expressions along a :func:`.relationship` that has a :term:`polymorphic` mapping as its target. This method can now be used to target any number of target subtypes, by combining it with the new :func:`.with_polymorphic` function:

# use eager loading in conjunction with with_polymorphic targets
Job_P = with_polymorphic(Job, [SubJob, ExtraJob], aliased=True)
q = s.query(DataContainer).\

The method now works equally well in most places a regular relationship attribute is accepted, including with loader functions like :func:`.joinedload`, :func:`.subqueryload`, :func:`.contains_eager`, and comparison methods like :meth:`.PropComparator.any` and :meth:`.PropComparator.has`:

# use eager loading in conjunction with with_polymorphic targets
Job_P = with_polymorphic(Job, [SubJob, ExtraJob], aliased=True)
q = s.query(DataContainer).\

# pass subclasses to eager loads (implicitly applies with_polymorphic)
q = s.query(ParentThing).\

# control self-referential aliasing with any()/has()
Job_A = aliased(Job)
q = s.query(Job).join(DataContainer.jobs).\
                        any(and_(Job_A.id < Job.id, Job_A.type=='fred')

:ticket:`2438` :ticket:`1106`

New DeferredReflection Feature in Declarative

The "deferred reflection" example has been moved to a supported feature within Declarative. This feature allows the construction of declarative mapped classes with only placeholder Table metadata, until a prepare() step is called, given an Engine with which to reflect fully all tables and establish actual mappings. The system supports overriding of columns, single and joined inheritance, as well as distinct bases-per-engine. A full declarative configuration can now be created against an existing table that is assembled upon engine creation time in one step:

class ReflectedOne(DeferredReflection, Base):
    __abstract__ = True

class ReflectedTwo(DeferredReflection, Base):
    __abstract__ = True

class MyClass(ReflectedOne):
    __tablename__ = 'mytable'

class MyOtherClass(ReflectedOne):
    __tablename__ = 'myothertable'

class YetAnotherClass(ReflectedTwo):
    __tablename__ = 'yetanothertable'



ORM Classes Now Accepted by Core Constructs

While the SQL expressions used with :meth:`.Query.filter`, such as User.id == 5, have always been compatible for use with core constructs such as :func:`.select`, the mapped class itself would not be recognized when passed to :func:`.select`, :meth:`.Select.select_from`, or :meth:`.Select.correlate`. A new SQL registration system allows a mapped class to be accepted as a FROM clause within the core:

from sqlalchemy import select

stmt = select([User]).where(User.id == 5)

Above, the mapped User class will expand into :class:`.Table` to which :class:`.User` is mapped.


Query.update() supports UPDATE..FROM

The new UPDATE..FROM mechanics work in query.update(). Below, we emit an UPDATE against SomeEntity, adding a FROM clause (or equivalent, depending on backend) against SomeOtherEntity:


In particular, updates to joined-inheritance entities are supported, provided the target of the UPDATE is local to the table being filtered on, or if the parent and child tables are mixed, they are joined explicitly in the query. Below, given Engineer as a joined subclass of Person:


would produce:

UPDATE engineer SET engineer_data='java' FROM person
WHERE person.id=engineer.id AND person.name='dilbert'


rollback() will only roll back "dirty" objects from a begin_nested()

A behavioral change that should improve efficiency for those users using SAVEPOINT via Session.begin_nested() - upon rollback(), only those objects that were made dirty since the last flush will be expired, the rest of the Session remains intact. This because a ROLLBACK to a SAVEPOINT does not terminate the containing transaction's isolation, so no expiry is needed except for those changes that were not flushed in the current transaction.


Caching Example now uses dogpile.cache

The caching example now uses dogpile.cache. Dogpile.cache is a rewrite of the caching portion of Beaker, featuring vastly simpler and faster operation, as well as support for distributed locking.


New Core Features

Fully extensible, type-level operator support in Core

The Core has to date never had any system of adding support for new SQL operators to Column and other expression constructs, other than the :meth:`.ColumnOperators.op` method which is "just enough" to make things work. There has also never been any system in place for Core which allows the behavior of existing operators to be overridden. Up until now, the only way operators could be flexibly redefined was in the ORM layer, using :func:`.column_property` given a comparator_factory argument. Third party libraries like GeoAlchemy therefore were forced to be ORM-centric and rely upon an array of hacks to apply new opertions as well as to get them to propagate correctly.

The new operator system in Core adds the one hook that's been missing all along, which is to associate new and overridden operators with types. Since after all, it's not really a column, CAST operator, or SQL function that really drives what kinds of operations are present, it's the type of the expression. The implementation details are minimal - only a few extra methods are added to the core :class:`.ColumnElement` type so that it consults it's :class:`.TypeEngine` object for an optional set of operators. New or revised operations can be associated with any type, either via subclassing of an existing type, by using :class:`.TypeDecorator`, or "globally across-the-board" by attaching a new :class:`.TypeEngine.Comparator` object to an existing type class.

For example, to add logarithm support to :class:`.Numeric` types:

from sqlalchemy.types import Numeric
from sqlalchemy.sql import func

class CustomNumeric(Numeric):
    class comparator_factory(Numeric.Comparator):
        def log(self, other):
            return func.log(self.expr, other)

The new type is usable like any other type:

data = Table('data', metadata,
          Column('id', Integer, primary_key=True),
          Column('x', CustomNumeric(10, 5)),
          Column('y', CustomNumeric(10, 5))

stmt = select([data.c.x.log(data.c.y)]).where(data.c.x.log(2) < value)
print conn.execute(stmt).fetchall()

New features which should come from this immediately are support for Postgresql's HSTORE type, which is ready to go in a separate library which may be merged, as well as all the special operations associated with Postgresql's ARRAY type. It also paves the way for existing types to acquire lots more operators that are specific to those types, such as more string, integer and date operators.


Type Expressions

SQL expressions can now be associated with types. Historically, :class:`.TypeEngine` has always allowed Python-side functions which receive both bound parameters as well as result row values, passing them through a Python side conversion function on the way to/back from the database. The new feature allows similar functionality, except on the database side:

from sqlalchemy.types import String
from sqlalchemy import func, Table, Column, MetaData

class LowerString(String):
    def bind_expression(self, bindvalue):
        return func.lower(bindvalue)

    def column_expression(self, col):
        return func.lower(col)

metadata = MetaData()
test_table = Table(
        Column('data', LowerString)

Above, the LowerString type defines a SQL expression that will be emitted whenever the test_table.c.data column is rendered in the columns clause of a SELECT statement:

>>> print select([test_table]).where(test_table.c.data == 'HI')
SELECT lower(test_table.data) AS data
FROM test_table
WHERE test_table.data = lower(:data_1)

This feature is also used heavily by the new release of GeoAlchemy, to embed PostGIS expressions inline in SQL based on type rules.


Core Inspection System

The :func:`.inspect` function introduced in :ref:`feature_orminspection_08` also applies to the core. Applied to an :class:`.Engine` it produces an :class:`.Inspector` object:

from sqlalchemy import inspect
from sqlalchemy import create_engine

engine = create_engine("postgresql://scott:tiger@localhost/test")
insp = inspect(engine)
print insp.get_table_names()

It can also be applied to any :class:`.ClauseElement`, which returns the :class:`.ClauseElement` itself, such as :class:`.Table`, :class:`.Column`, :class:`.Select`, etc. This allows it to work fluently between Core and ORM constructs.

New, configurable DATE, TIME types for SQLite

SQLite has no built-in DATE, TIME, or DATETIME types, and instead provides some support for storage of date and time values either as strings or integers. The date and time types for SQLite are enhanced in 0.8 to be much more configurable as to the specific format, including that the "microseconds" portion is optional, as well as pretty much everything else.

Column('sometimestamp', sqlite.DATETIME(truncate_microseconds=True))
Column('sometimestamp', sqlite.DATETIME(
Column('somedate', sqlite.DATE(

Huge thanks to Nate Dub for the sprinting on this at Pycon 2012.


New Method :meth:`.Select.correlate_except`

:func:`.select` now has a method :meth:`.Select.correlate_except` which specifies "correlate on all FROM clauses except those specified". It can be used for mapping scenarios where a related subquery should correlate normally, except against a particular target selectable:

class SnortEvent(Base):
    __tablename__ = "event"

    id = Column(Integer, primary_key=True)
    signature = Column(Integer, ForeignKey("signature.id"))

    signatures = relationship("Signature", lazy=False)

class Signature(Base):
    __tablename__ = "signature"

    id = Column(Integer, primary_key=True)

    sig_count = column_property(
                        where(SnortEvent.signature == id).

Enhanced Postgresql ARRAY type

The postgresql.ARRAY type will accept an optional "dimension" argument, pinning it to a fixed number of dimensions and greatly improving efficiency when retrieving results:

# old way, still works since PG supports N-dimensions per row:
Column("my_array", postgresql.ARRAY(Integer))

# new way, will render ARRAY with correct number of [] in DDL,
# will process binds and results more efficiently as we don't need
# to guess how many levels deep to go
Column("my_array", postgresql.ARRAY(Integer, dimensions=2))


"COLLATE" supported across all dialects; in particular MySQL, Postgresql, SQLite

The "collate" keyword, long accepted by the MySQL dialect, is now established on all :class:`.String` types and will render on any backend, including when features such as :meth:`.MetaData.create_all` and :func:`.cast` is used:

>>> stmt = select([cast(sometable.c.somechar, String(20, collation='utf8'))])
>>> print stmt
SELECT CAST(sometable.somechar AS VARCHAR(20) COLLATE "utf8") AS anon_1
FROM sometable


"Prefixes" now supported for :func:`.update`, :func:`.delete`

Geared towards MySQL, a "prefix" can be rendered within any of these constructs. E.g.:

stmt = table.delete().prefix_with("LOW_PRIORITY", dialect="mysql")

stmt = table.update().prefix_with("LOW_PRIORITY", dialect="mysql")

The method is new in addition to those which already existed on :func:`.insert`, :func:`.select` and :class:`.Query`.


Behavioral Changes

The after_attach event fires after the item is associated with the Session instead of before; before_attach added

Event handlers which use after_attach can now assume the given instance is associated with the given session:

@event.listens_for(Session, "after_attach")
def after_attach(session, instance):
    assert instance in session

Some use cases require that it work this way. However, other use cases require that the item is not yet part of the session, such as when a query, intended to load some state required for an instance, emits autoflush first and would otherwise prematurely flush the target object. Those use cases should use the new "before_attach" event:

@event.listens_for(Session, "before_attach")
def before_attach(session, instance):
    instance.some_necessary_attribute = session.query(Widget).\


Query now auto-correlates like a select() does

Previously it was necessary to call :meth:`.Query.correlate` in order to have a column- or WHERE-subquery correlate to the parent:

subq = session.query(Entity.value).\
session.query(Parent).filter(subq=="some value")

This was the opposite behavior of a plain select() construct which would assume auto-correlation by default. The above statement in 0.8 will correlate automatically:

subq = session.query(Entity.value).\
session.query(Parent).filter(subq=="some value")

like in select(), correlation can be disabled by calling query.correlate(None) or manually set by passing an entity, query.correlate(someentity).


No more magic coercion of "=" to IN when comparing to subquery in MS-SQL

We found a very old behavior in the MSSQL dialect which would attempt to rescue the user from his or herself when doing something like this:

scalar_subq = select([someothertable.c.id]).where(someothertable.c.data=='foo')

SQL Server doesn't allow an equality comparison to a scalar SELECT, that is, "x = (SELECT something)". The MSSQL dialect would convert this to an IN. The same thing would happen however upon a comparison like "(SELECT something) = x", and overall this level of guessing is outside of SQLAlchemy's usual scope so the behavior is removed.


Fixed the behavior of :meth:`.Session.is_modified`

The :meth:`.Session.is_modified` method accepts an argument passive which basically should not be necessary, the argument in all cases should be the value True - when left at its default of False it would have the effect of hitting the database, and often triggering autoflush which would itself change the results. In 0.8 the passive argument will have no effect, and unloaded attributes will never be checked for history since by definition there can be no pending state change on an unloaded attribute.


:attr:`.Column.key` is honored in the :attr:`.Select.c` attribute of :func:`.select` with :meth:`.Select.apply_labels`

Users of the expression system know that :meth:`.Select.apply_labels` prepends the table name to each column name, affecting the names that are available from :attr:`.Select.c`:

s = select([table1]).apply_labels()

Before 0.8, if the :class:`.Column` had a different :attr:`.Column.key`, this key would be ignored, inconsistently versus when :meth:`.Select.apply_labels` were not used:

# before 0.8
table1 = Table('t1', metadata,
    Column('col1', Integer, key='column_one')
s = select([table1])
s.c.column_one # would be accessible like this
s.c.col1 # would raise AttributeError

s = select([table1]).apply_labels()
s.c.table1_column_one # would raise AttributeError
s.c.table1_col1 # would be accessible like this

In 0.8, :attr:`.Column.key` is honored in both cases:

# with 0.8
table1 = Table('t1', metadata,
    Column('col1', Integer, key='column_one')
s = select([table1])
s.c.column_one # works
s.c.col1 # AttributeError

s = select([table1]).apply_labels()
s.c.table1_column_one # works
s.c.table1_col1 # AttributeError

All other behavior regarding "name" and "key" are the same, including that the rendered SQL will still use the form <tablename>_<colname> - the emphasis here was on preventing the :attr:`.Column.key` contents from being rendered into the SELECT statement so that there are no issues with special/ non-ascii characters used in the :attr:`.Column.key`.


single_parent warning is now an error

A :func:`.relationship` that is many-to-one or many-to-many and specifies "cascade='all, delete-orphan'", which is an awkward but nonetheless supported use case (with restrictions) will now raise an error if the relationship does not specify the single_parent=True option. Previously it would only emit a warning, but a failure would follow almost immediately within the attribute system in any case.


Adding the inspector argument to the column_reflect event

0.7 added a new event called column_reflect, provided so that the reflection of columns could be augmented as each one were reflected. We got this event slightly wrong in that the event gave no way to get at the current Inspector and Connection being used for the reflection, in the case that additional information from the database is needed. As this is a new event not widely used yet, we'll be adding the inspector argument into it directly:

@event.listens_for(Table, "column_reflect")
def listen_for_col(inspector, table, column_info):
    # ...


Disabling auto-detect of collations, casing for MySQL

The MySQL dialect does two calls, one very expensive, to load all possible collations from the database as well as information on casing, the first time an Engine connects. Neither of these collections are used for any SQLAlchemy functions, so these calls will be changed to no longer be emitted automatically. Applications that might have relied on these collections being present on engine.dialect will need to call upon _detect_collations() and _detect_casing() directly.


"Unconsumed column names" warning becomes an exception

Referring to a non-existent column in an insert() or update() construct will raise an error instead of a warning:

t1 = table('t1', column('x'))
t1.insert().values(x=5, z=5) # raises "Unconsumed column names: z"


Inspector.get_primary_keys() is deprecated, use Inspector.get_pk_constraint

These two methods on Inspector were redundant, where get_primary_keys() would return the same information as get_pk_constraint() minus the name of the constraint:

>>> insp.get_primary_keys()
["a", "b"]

>>> insp.get_pk_constraint()
{"name":"pk_constraint", "constrained_columns":["a", "b"]}


Case-insensitive result row names will be disabled in most cases

A very old behavior, the column names in RowProxy were always compared case-insensitively:

>>> row = result.fetchone()
>>> row['foo'] == row['FOO'] == row['Foo']

This was for the benefit of a few dialects which in the early days needed this, like Oracle and Firebird, but in modern usage we have more accurate ways of dealing with the case-insensitive behavior of these two platforms.

Going forward, this behavior will be available only optionally, by passing the flag `case_sensitive=False` to `create_engine()`, but otherwise column names requested from the row must match as far as casing.


InstrumentationManager and alternate class instrumentation is now an extension

The sqlalchemy.orm.interfaces.InstrumentationManager class is moved to sqlalchemy.ext.instrumentation.InstrumentationManager. The "alternate instrumentation" system was built for the benefit of a very small number of installations that needed to work with existing or unusual class instrumentation systems, and generally is very seldom used. The complexity of this system has been exported to an ext. module. It remains unused until once imported, typically when a third party library imports InstrumentationManager, at which point it is injected back into sqlalchemy.orm by replacing the default InstrumentationFactory with ExtendedInstrumentationRegistry.



SQLSoup is a handy package that presents an alternative interface on top of the SQLAlchemy ORM. SQLSoup is now moved into its own project and documented/released separately; see https://bitbucket.org/zzzeek/sqlsoup.

SQLSoup is a very simple tool that could also benefit from contributors who are interested in its style of usage.



The older "mutable" system within the SQLAlchemy ORM has been removed. This refers to the MutableType interface which was applied to types such as PickleType and conditionally to TypeDecorator, and since very early SQLAlchemy versions has provided a way for the ORM to detect changes in so-called "mutable" data structures such as JSON structures and pickled objects. However, the implementation was never reasonable and forced a very inefficient mode of usage on the unit-of-work which caused an expensive scan of all objects to take place during flush. In 0.7, the sqlalchemy.ext.mutable extension was introduced so that user-defined datatypes can appropriately send events to the unit of work as changes occur.

Today, usage of MutableType is expected to be low, as warnings have been in place for some years now regarding its inefficiency.


sqlalchemy.exceptions (has been sqlalchemy.exc for years)

We had left in an alias sqlalchemy.exceptions to attempt to make it slightly easier for some very old libraries that hadn't yet been upgraded to use sqlalchemy.exc. Some users are still being confused by it however so in 0.8 we're taking it out entirely to eliminate any of that confusion.