Current File : //proc/self/root/opt/alt/python37/share/doc/alt-python37-alembic/docs/build/batch.rst
.. _batch_migrations:
Running "Batch" Migrations for SQLite and Other Databases
=========================================================
.. note:: "Batch mode" for SQLite and other databases is a new and intricate
feature within the 0.7.0 series of Alembic, and should be
considered as "beta" for the next several releases.
.. versionadded:: 0.7.0
The SQLite database presents a challenge to migration tools
in that it has almost no support for the ALTER statement upon which
relational schema migrations rely upon. The rationale for this stems from
philosophical and architectural concerns within SQLite, and they are unlikely
to be changed.
Migration tools are instead expected to produce copies of SQLite tables that
correspond to the new structure, transfer the data from the existing
table to the new one, then drop the old table. For our purposes here
we'll call this **"move and copy"** workflow, and in order to accommodate it
in a way that is reasonably predictable, while also remaining compatible
with other databases, Alembic provides the **batch** operations context.
Within this context, a relational table is named, and then a series of
mutation operations to that table alone are specified within
the block. When the context is complete, a process begins whereby the
"move and copy" procedure begins; the existing table structure is reflected
from the database, a new version of this table is created with the given
changes, data is copied from the
old table to the new table using "INSERT from SELECT", and finally the old
table is dropped and the new one renamed to the original name.
The :meth:`.Operations.batch_alter_table` method provides the gateway to this
process::
with op.batch_alter_table("some_table") as batch_op:
batch_op.add_column(Column('foo', Integer))
batch_op.drop_column('bar')
When the above directives are invoked within a migration script, on a
SQLite backend we would see SQL like:
.. sourcecode:: sql
CREATE TABLE _alembic_batch_temp (
id INTEGER NOT NULL,
foo INTEGER,
PRIMARY KEY (id)
);
INSERT INTO _alembic_batch_temp (id) SELECT some_table.id FROM some_table;
DROP TABLE some_table;
ALTER TABLE _alembic_batch_temp RENAME TO some_table;
On other backends, we'd see the usual ``ALTER`` statements done as though
there were no batch directive - the batch context by default only does
the "move and copy" process if SQLite is in use, and if there are
migration directives other than :meth:`.Operations.add_column` present,
which is the one kind of column-level ALTER statement that SQLite supports.
:meth:`.Operations.batch_alter_table` can be configured
to run "move and copy" unconditionally in all cases, including on databases
other than SQLite; more on this is below.
.. _batch_controlling_table_reflection:
Controlling Table Reflection
----------------------------
The :class:`~sqlalchemy.schema.Table` object that is reflected when
"move and copy" proceeds is performed using the standard ``autoload=True``
approach. This call can be affected using the
:paramref:`~.Operations.batch_alter_table.reflect_args` and
:paramref:`~.Operations.batch_alter_table.reflect_kwargs` arguments.
For example, to override a :class:`~sqlalchemy.schema.Column` within
the reflection process such that a :class:`~sqlalchemy.types.Boolean`
object is reflected with the ``create_constraint`` flag set to ``False``::
with self.op.batch_alter_table(
"bar",
reflect_args=[Column('flag', Boolean(create_constraint=False))]
) as batch_op:
batch_op.alter_column(
'flag', new_column_name='bflag', existing_type=Boolean)
Another use case, add a listener to the :class:`~sqlalchemy.schema.Table`
as it is reflected so that special logic can be applied to columns or
types, using the :meth:`~sqlalchemy.events.DDLEvents.column_reflect` event::
def listen_for_reflect(inspector, table, column_info):
"correct an ENUM type"
if column_info['name'] == 'my_enum':
column_info['type'] = Enum('a', 'b', 'c')
with self.op.batch_alter_table(
"bar",
reflect_kwargs=dict(
listeners=[
('column_reflect', listen_for_reflect)
]
)
) as batch_op:
batch_op.alter_column(
'flag', new_column_name='bflag', existing_type=Boolean)
The reflection process may also be bypassed entirely by sending a
pre-fabricated :class:`~sqlalchemy.schema.Table` object; see
:ref:`batch_offline_mode` for an example.
.. versionadded:: 0.7.1
added :paramref:`.Operations.batch_alter_table.reflect_args`
and :paramref:`.Operations.batch_alter_table.reflect_kwargs` options.
.. _sqlite_batch_constraints:
Dealing with Constraints
------------------------
There are a variety of issues when using "batch" mode with constraints,
such as FOREIGN KEY, CHECK and UNIQUE constraints. This section
will attempt to detail many of these scenarios.
.. _dropping_sqlite_foreign_keys:
Dropping Unnamed or Named Foreign Key Constraints
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
SQLite, unlike any other database, allows constraints to exist in the
database that have no identifying name. On all other backends, the
target database will always generate some kind of name, if one is not
given.
The first challenge this represents is that an unnamed constraint can't
by itself be targeted by the :meth:`.BatchOperations.drop_constraint` method.
An unnamed FOREIGN KEY constraint is implicit whenever the
:class:`~sqlalchemy.schema.ForeignKey`
or :class:`~sqlalchemy.schema.ForeignKeyConstraint` objects are used without
passing them a name. Only on SQLite will these constraints remain entirely
unnamed when they are created on the target database; an automatically generated
name will be assigned in the case of all other database backends.
A second issue is that SQLAlchemy itself has inconsistent behavior in
dealing with SQLite constraints as far as names. Prior to version 1.0,
SQLAlchemy omits the name of foreign key constraints when reflecting them
against the SQLite backend. So even if the target application has gone through
the steps to apply names to the constraints as stated in the database,
they still aren't targetable within the batch reflection process prior
to SQLAlchemy 1.0.
Within the scope of batch mode, this presents the issue that the
:meth:`.BatchOperations.drop_constraint` method requires a constraint name
in order to target the correct constraint.
In order to overcome this, the :meth:`.Operations.batch_alter_table` method supports a
:paramref:`~.Operations.batch_alter_table.naming_convention` argument, so that
all reflected constraints, including foreign keys that are unnamed, or
were named but SQLAlchemy isn't loading this name, may be given a name,
as described in :ref:`autogen_naming_conventions`. Usage is as follows::
naming_convention = {
"fk":
"fk_%(table_name)s_%(column_0_name)s_%(referred_table_name)s",
}
with self.op.batch_alter_table(
"bar", naming_convention=naming_convention) as batch_op:
batch_op.drop_constraint(
"fk_bar_foo_id_foo", type_="foreignkey")
Note that the naming convention feature requires at least
**SQLAlchemy 0.9.4** for support.
.. versionadded:: 0.7.1
added :paramref:`~.Operations.batch_alter_table.naming_convention` to
:meth:`.Operations.batch_alter_table`.
Including unnamed UNIQUE constraints
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
A similar, but frustratingly slightly different, issue is that in the
case of UNIQUE constraints, we again have the issue that SQLite allows
unnamed UNIQUE constraints to exist on the database, however in this case,
SQLAlchemy prior to version 1.0 doesn't reflect these constraints at all.
It does properly reflect named unique constraints with their names, however.
So in this case, the workaround for foreign key names is still not sufficient
prior to SQLAlchemy 1.0. If our table includes unnamed unique constraints,
and we'd like them to be re-created along with the table, we need to include
them directly, which can be via the
:paramref:`~.Operations.batch_alter_table.table_args` argument::
with self.op.batch_alter_table(
"bar", table_args=(UniqueConstraint('username'),)
):
batch_op.add_column(Column('foo', Integer))
Including CHECK constraints
^^^^^^^^^^^^^^^^^^^^^^^^^^^
SQLAlchemy currently doesn't reflect CHECK constraints on any backend.
So again these must be stated explicitly if they are to be included in the
recreated table::
with op.batch_alter_table("some_table", table_args=[
CheckConstraint('x > 5')
]) as batch_op:
batch_op.add_column(Column('foo', Integer))
batch_op.drop_column('bar')
Dealing with Referencing Foreign Keys
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If the SQLite database is enforcing referential integrity with
``PRAGMA FOREIGN KEYS``, this pragma may need to be disabled when the workflow
mode proceeds, else remote constraints which refer to this table may prevent
it from being dropped; additionally, for referential integrity to be
re-enabled, it may be necessary to recreate the
foreign keys on those remote tables to refer again to the new table (this
is definitely the case on other databases, at least). SQLite is normally used
without referential integrity enabled so this won't be a problem for most
users.
.. _batch_offline_mode:
Working in Offline Mode
-----------------------
In the preceding sections, we've seen how much of an emphasis the
"move and copy" process has on using reflection in order to know the
structure of the table that is to be copied. This means that in the typical
case, "online" mode, where a live database connection is present so that
:meth:`.Operations.batch_alter_table` can reflect the table from the
database, is required; the ``--sql`` flag **cannot** be used without extra
steps.
To support offline mode, the system must work without table reflection
present, which means the full table as it intends to be created must be
passed to :meth:`.Operations.batch_alter_table` using
:paramref:`~.Operations.batch_alter_table.copy_from`::
meta = MetaData()
some_table = Table(
'some_table', meta,
Column('id', Integer, primary_key=True),
Column('bar', String(50))
)
with op.batch_alter_table("some_table", copy_from=some_table) as batch_op:
batch_op.add_column(Column('foo', Integer))
batch_op.drop_column('bar')
The above use pattern is pretty tedious and quite far off from Alembic's
preferred style of working; however, if one needs to do SQLite-compatible
"move and copy" migrations and need them to generate flat SQL files in
"offline" mode, there's not much alternative.
.. versionadded:: 0.7.6 Fully implemented the
:paramref:`~.Operations.batch_alter_table.copy_from`
parameter.
Batch mode with Autogenerate
----------------------------
The syntax of batch mode is essentially that :meth:`.Operations.batch_alter_table`
is used to enter a batch block, and the returned :class:`.BatchOperations` context
works just like the regular :class:`.Operations` context, except that
the "table name" and "schema name" arguments are omitted.
To support rendering of migration commands in batch mode for autogenerate,
configure the :paramref:`.EnvironmentContext.configure.render_as_batch`
flag in ``env.py``::
context.configure(
connection=connection,
target_metadata=target_metadata,
render_as_batch=True
)
Autogenerate will now generate along the lines of::
def upgrade():
### commands auto generated by Alembic - please adjust! ###
with op.batch_alter_table('address', schema=None) as batch_op:
batch_op.add_column(sa.Column('street', sa.String(length=50), nullable=True))
This mode is safe to use in all cases, as the :meth:`.Operations.batch_alter_table`
directive by default only takes place for SQLite; other backends will
behave just as they normally do in the absense of the batch directives.
Note that autogenerate support does not include "offline" mode, where
the :paramref:`.Operations.batch_alter_table.copy_from` parameter is used.
The table definition here would need to be entered into migration files
manually if this is needed.
Batch mode with databases other than SQLite
--------------------------------------------
There's an odd use case some shops have, where the "move and copy" style
of migration is useful in some cases for databases that do already support
ALTER. There's some cases where an ALTER operation may block access to the
table for a long time, which might not be acceptable. "move and copy" can
be made to work on other backends, though with a few extra caveats.
The batch mode directive will run the "recreate" system regardless of
backend if the flag ``recreate='always'`` is passed::
with op.batch_alter_table("some_table", recreate='always') as batch_op:
batch_op.add_column(Column('foo', Integer))
The issues that arise in this mode are mostly to do with constraints.
Databases such as Postgresql and MySQL with InnoDB will enforce referential
integrity (e.g. via foreign keys) in all cases. Unlike SQLite, it's not
as simple to turn off referential integrity across the board (nor would it
be desirable). Since a new table is replacing the old one, existing
foreign key constraints which refer to the target table will need to be
unconditionally dropped before the batch operation, and re-created to refer
to the new table afterwards. Batch mode currently does not provide any
automation for this.
The Postgresql database and possibly others also have the behavior such
that when the new table is created, a naming conflict occurs with the
named constraints of the new table, in that they match those of the old
table, and on Postgresql, these names need to be unique across all tables.
The Postgresql dialect will therefore emit a "DROP CONSTRAINT" directive
for all constraints on the old table before the new one is created; this is
"safe" in case of a failed operation because Postgresql also supports
transactional DDL.
Note that also as is the case with SQLite, CHECK constraints need to be
moved over between old and new table manually using the
:paramref:`.Operations.batch_alter_table.table_args` parameter.
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