path: root/docs/build/cookbook.rst

========
Cookbook
========

A collection of "How-Tos" highlighting popular ways to extend
Alembic.

.. note::

    This is a new section where we catalogue various "how-tos"
    based on user requests.  It is often the case that users
    will request a feature only to learn it can be provided with
    a simple customization.

.. _building_uptodate:

Building an Up to Date Database from Scratch
=============================================

There's a theory of database migrations that says that the revisions in existence for a database should be
able to go from an entirely blank schema to the finished product, and back again.   Alembic can roll
this way.   Though we think it's kind of overkill, considering that SQLAlchemy itself can emit
the full CREATE statements for any given model using :meth:`~sqlalchemy.schema.MetaData.create_all`.   If you check out
a copy of an application, running this will give you the entire database in one shot, without the need
to run through all those migration files, which are instead tailored towards applying incremental
changes to an existing database.

Alembic can integrate with a :meth:`~sqlalchemy.schema.MetaData.create_all` script quite easily.  After running the
create operation, tell Alembic to create a new version table, and to stamp it with the most recent
revision (i.e. ``head``)::

    # inside of a "create the database" script, first create
    # tables:
    my_metadata.create_all(engine)

    # then, load the Alembic configuration and generate the
    # version table, "stamping" it with the most recent rev:
    from alembic.config import Config
    from alembic import command
    alembic_cfg = Config("/path/to/yourapp/alembic.ini")
    command.stamp(alembic_cfg, "head")

When this approach is used, the application can generate the database using normal SQLAlchemy
techniques instead of iterating through hundreds of migration scripts.   Now, the purpose of the
migration scripts is relegated just to movement between versions on out-of-date databases, not
*new* databases.    You can now remove old migration files that are no longer represented
on any existing environments.

To prune old migration files, simply delete the files.   Then, in the earliest, still-remaining
migration file, set ``down_revision`` to ``None``::

    # replace this:
    #down_revision = '290696571ad2'

    # with this:
    down_revision = None

That file now becomes the "base" of the migration series.

Conditional Migration Elements
==============================

This example features the basic idea of a common need, that of affecting
how a migration runs based on command line switches.

The technique to use here is simple; within a migration script, inspect
the :meth:`.EnvironmentContext.get_x_argument` collection for any additional,
user-defined parameters.  Then take action based on the presence of those
arguments.

To make it such that the logic to inspect these flags is easy to use and
modify, we modify our ``script.py.mako`` template to make this feature
available in all new revision files:

.. code-block:: mako

    """${message}

    Revision ID: ${up_revision}
    Revises: ${down_revision}
    Create Date: ${create_date}

    """

    # revision identifiers, used by Alembic.
    revision = ${repr(up_revision)}
    down_revision = ${repr(down_revision)}

    from alembic import op
    import sqlalchemy as sa
    ${imports if imports else ""}

    from alembic import context


    def upgrade():
        schema_upgrades()
        if context.get_x_argument(as_dictionary=True).get('data', None):
            data_upgrades()

    def downgrade():
        if context.get_x_argument(as_dictionary=True).get('data', None):
            data_downgrades()
        schema_downgrades()

    def schema_upgrades():
        """schema upgrade migrations go here."""
        ${upgrades if upgrades else "pass"}

    def schema_downgrades():
        """schema downgrade migrations go here."""
        ${downgrades if downgrades else "pass"}

    def data_upgrades():
        """Add any optional data upgrade migrations here!"""
        pass

    def data_downgrades():
        """Add any optional data downgrade migrations here!"""
        pass

Now, when we create a new migration file, the ``data_upgrades()`` and ``data_downgrades()``
placeholders will be available, where we can add optional data migrations::

    """rev one

    Revision ID: 3ba2b522d10d
    Revises: None
    Create Date: 2014-03-04 18:05:36.992867

    """

    # revision identifiers, used by Alembic.
    revision = '3ba2b522d10d'
    down_revision = None

    from alembic import op
    import sqlalchemy as sa
    from sqlalchemy import String, Column
    from sqlalchemy.sql import table, column

    from alembic import context

    def upgrade():
        schema_upgrades()
        if context.get_x_argument(as_dictionary=True).get('data', None):
            data_upgrades()

    def downgrade():
        if context.get_x_argument(as_dictionary=True).get('data', None):
            data_downgrades()
        schema_downgrades()

    def schema_upgrades():
        """schema upgrade migrations go here."""
        op.create_table("my_table", Column('data', String))

    def schema_downgrades():
        """schema downgrade migrations go here."""
        op.drop_table("my_table")

    def data_upgrades():
        """Add any optional data upgrade migrations here!"""

        my_table = table('my_table',
            column('data', String),
        )

        op.bulk_insert(my_table,
            [
                {'data': 'data 1'},
                {'data': 'data 2'},
                {'data': 'data 3'},
            ]
        )

    def data_downgrades():
        """Add any optional data downgrade migrations here!"""

        op.execute("delete from my_table")

To invoke our migrations with data included, we use the ``-x`` flag::

    alembic -x data=true upgrade head

The :meth:`.EnvironmentContext.get_x_argument` is an easy way to support
new commandline options within environment and migration scripts.

.. _connection_sharing:

Sharing a Connection across one or more programmatic migration commands
=========================================================================

It is often the case that an application will need to call upon a series
of commands within :ref:`alembic.command.toplevel`, where it would be advantageous
for all operations to proceed along a single transaction.   The connectivity
for a migration is typically solely determined within the ``env.py`` script
of a migration environment, which is called within the scope of a command.

The steps to take here are:

1. Produce the :class:`~sqlalchemy.engine.Connection` object to use.

2. Place it somewhere that ``env.py`` will be able to access it.  This
   can be either a. a module-level global somewhere, or b.
   an attribute which we place into the :attr:`.Config.attributes`
   dictionary (if we are on an older Alembic version, we may also attach
   an attribute directly to the :class:`.Config` object).

3. The ``env.py`` script is modified such that it looks for this
   :class:`~sqlalchemy.engine.Connection` and makes use of it, in lieu
   of building up its own :class:`~sqlalchemy.engine.Engine` instance.

We illustrate using :attr:`.Config.attributes` a script that will run
the :func:`.command.upgrade` command programmatically within a
transaction declared in a Python file::

    from alembic import command, config

    cfg = config.Config("/path/to/yourapp/alembic.ini")
    with engine.begin() as connection:
        cfg.attributes['connection'] = connection
        command.upgrade(cfg, "head")

Then in ``env.py`` we can update ``run_migrations_online``::

    def run_migrations_online():
        connectable = config.attributes.get('connection', None)

        if connectable is None:
            # only create Engine if we don't have a Connection
            # from the outside
            connectable = engine_from_config(
                config.get_section(config.config_ini_section),
                prefix='sqlalchemy.',
                poolclass=pool.NullPool)

            with connectable.connect() as connection:
                context.configure(
                    connection=connection, target_metadata=target_metadata
                )

                with context.begin_transaction():
                    context.run_migrations()
        else:
            context.configure(
                connection=connectable,
                target_metadata=target_metadata
            )

            with context.begin_transaction():
                context.run_migrations()


.. _replaceable_objects:

Replaceable Objects
===================

This recipe proposes a hypothetical way of dealing with
what we might call a *replaceable* schema object.  A replaceable object
is a schema object that needs to be created and dropped all at once.
Examples of such objects include views, stored procedures, and triggers.

.. seealso::

    The Replaceable Object concept has been integrated by the
    `Alembic Utils <https://github.com/olirice/alembic_utils>`_ project,
    which provides autogenerate and migration
    support for PostgreSQL functions and views.   See
    Alembic Utils at https://github.com/olirice/alembic_utils .

Replaceable objects present a problem in that in order to make incremental
changes to them, we have to refer to the whole definition at once.
If we need to add a new column to a view, for example, we have to drop
it entirely and recreate it fresh with the extra column added, referring to
the whole structure; but to make it even tougher, if we wish to support
downgrade operarations in our migration scripts,
we need to refer to the *previous* version of that
construct fully, and we'd much rather not have to type out the whole
definition in multiple places.

This recipe proposes that we may refer to the older version of a
replaceable construct by directly naming the migration version in
which it was created, and having a migration refer to that previous
file as migrations run.   We will also demonstrate how to integrate this
logic within the :ref:`operation_plugins` feature introduced in
Alembic 0.8.  It may be very helpful to review
this section first to get an overview of this API.

The Replaceable Object Structure
--------------------------------

We first need to devise a simple format that represents the "CREATE XYZ" /
"DROP XYZ" aspect of what it is we're building.  We will work with an object
that represents a textual definition; while a SQL view is an object that we can define
using a `table-metadata-like system <https://github.com/sqlalchemy/sqlalchemy/wiki/UsageRecipes/Views>`_,
this is not so much the case for things like stored procedures, where
we pretty much need to have a full string definition written down somewhere.
We'll use a simple value object called ``ReplaceableObject`` that can
represent any named set of SQL text to send to a "CREATE" statement of
some kind::

    class ReplaceableObject:
        def __init__(self, name, sqltext):
            self.name = name
            self.sqltext = sqltext

Using this object in a migration script, assuming a Postgresql-style
syntax, looks like::

    customer_view = ReplaceableObject(
        "customer_view",
        "SELECT name, order_count FROM customer WHERE order_count > 0"
    )

    add_customer_sp = ReplaceableObject(
        "add_customer_sp(name varchar, order_count integer)",
        """
        RETURNS integer AS $$
        BEGIN
            insert into customer (name, order_count)
            VALUES (in_name, in_order_count);
        END;
        $$ LANGUAGE plpgsql;
        """
    )

The ``ReplaceableObject`` class is only one very simplistic way to do this.
The structure of how we represent our schema objects
is not too important for the purposes of this example; we can just
as well put strings inside of tuples or dictionaries, as well as
that we could define any kind of series of fields and class structures we want.
The only important part is that below we will illustrate how organize the
code that can consume the structure we create here.

Create Operations for the Target Objects
----------------------------------------

We'll use the :class:`.Operations` extension API to make new operations
for create, drop, and replace of views and stored procedures.  Using this
API is also optional; we can just as well make any kind of Python
function that we would invoke from our migration scripts.
However, using this API gives us operations
built directly into the Alembic ``op.*`` namespace very nicely.

The most intricate class is below.  This is the base of our "replaceable"
operation, which includes not just a base operation for emitting
CREATE and DROP instructions on a ``ReplaceableObject``, it also assumes
a certain model of "reversibility" which makes use of references to
other migration files in order to refer to the "previous" version
of an object::

    from alembic.operations import Operations, MigrateOperation

    class ReversibleOp(MigrateOperation):
        def __init__(self, target):
            self.target = target

        @classmethod
        def invoke_for_target(cls, operations, target):
            op = cls(target)
            return operations.invoke(op)

        def reverse(self):
            raise NotImplementedError()

        @classmethod
        def _get_object_from_version(cls, operations, ident):
            version, objname = ident.split(".")

            module = operations.get_context().script.get_revision(version).module
            obj = getattr(module, objname)
            return obj

        @classmethod
        def replace(cls, operations, target, replaces=None, replace_with=None):

            if replaces:
                old_obj = cls._get_object_from_version(operations, replaces)
                drop_old = cls(old_obj).reverse()
                create_new = cls(target)
            elif replace_with:
                old_obj = cls._get_object_from_version(operations, replace_with)
                drop_old = cls(target).reverse()
                create_new = cls(old_obj)
            else:
                raise TypeError("replaces or replace_with is required")

            operations.invoke(drop_old)
            operations.invoke(create_new)

The workings of this class should become clear as we walk through the
example.   To create usable operations from this base, we will build
a series of stub classes and use :meth:`.Operations.register_operation`
to make them part of the ``op.*`` namespace::

    @Operations.register_operation("create_view", "invoke_for_target")
    @Operations.register_operation("replace_view", "replace")
    class CreateViewOp(ReversibleOp):
        def reverse(self):
            return DropViewOp(self.target)


    @Operations.register_operation("drop_view", "invoke_for_target")
    class DropViewOp(ReversibleOp):
        def reverse(self):
            return CreateViewOp(self.target)


    @Operations.register_operation("create_sp", "invoke_for_target")
    @Operations.register_operation("replace_sp", "replace")
    class CreateSPOp(ReversibleOp):
        def reverse(self):
            return DropSPOp(self.target)


    @Operations.register_operation("drop_sp", "invoke_for_target")
    class DropSPOp(ReversibleOp):
        def reverse(self):
            return CreateSPOp(self.target)

To actually run the SQL like "CREATE VIEW" and "DROP SEQUENCE", we'll provide
implementations using :meth:`.Operations.implementation_for`
that run straight into :meth:`.Operations.execute`::

    @Operations.implementation_for(CreateViewOp)
    def create_view(operations, operation):
        operations.execute("CREATE VIEW %s AS %s" % (
            operation.target.name,
            operation.target.sqltext
        ))


    @Operations.implementation_for(DropViewOp)
    def drop_view(operations, operation):
        operations.execute("DROP VIEW %s" % operation.target.name)


    @Operations.implementation_for(CreateSPOp)
    def create_sp(operations, operation):
        operations.execute(
            "CREATE FUNCTION %s %s" % (
                operation.target.name, operation.target.sqltext
            )
        )


    @Operations.implementation_for(DropSPOp)
    def drop_sp(operations, operation):
        operations.execute("DROP FUNCTION %s" % operation.target.name)

All of the above code can be present anywhere within an application's
source tree; the only requirement is that when the ``env.py`` script is
invoked, it includes imports that ultimately call upon these classes
as well as the :meth:`.Operations.register_operation` and
:meth:`.Operations.implementation_for` sequences.

Create Initial Migrations
-------------------------

We can now illustrate how these objects look during use.  For the first step,
we'll create a new migration to create a "customer" table::

    $ alembic revision -m "create table"

We build the first revision as follows::

    """create table

    Revision ID: 3ab8b2dfb055
    Revises:
    Create Date: 2015-07-27 16:22:44.918507

    """

    # revision identifiers, used by Alembic.
    revision = '3ab8b2dfb055'
    down_revision = None
    branch_labels = None
    depends_on = None

    from alembic import op
    import sqlalchemy as sa


    def upgrade():
        op.create_table(
            "customer",
            sa.Column('id', sa.Integer, primary_key=True),
            sa.Column('name', sa.String),
            sa.Column('order_count', sa.Integer),
        )


    def downgrade():
        op.drop_table('customer')

For the second migration, we will create a view and a stored procedure
which act upon this table::

    $ alembic revision -m "create views/sp"

This migration will use the new directives::

    """create views/sp

    Revision ID: 28af9800143f
    Revises: 3ab8b2dfb055
    Create Date: 2015-07-27 16:24:03.589867

    """

    # revision identifiers, used by Alembic.
    revision = '28af9800143f'
    down_revision = '3ab8b2dfb055'
    branch_labels = None
    depends_on = None

    from alembic import op
    import sqlalchemy as sa

    from foo import ReplaceableObject

    customer_view = ReplaceableObject(
        "customer_view",
        "SELECT name, order_count FROM customer WHERE order_count > 0"
    )

    add_customer_sp = ReplaceableObject(
        "add_customer_sp(name varchar, order_count integer)",
        """
        RETURNS integer AS $$
        BEGIN
            insert into customer (name, order_count)
            VALUES (in_name, in_order_count);
        END;
        $$ LANGUAGE plpgsql;
        """
    )


    def upgrade():
        op.create_view(customer_view)
        op.create_sp(add_customer_sp)


    def downgrade():
        op.drop_view(customer_view)
        op.drop_sp(add_customer_sp)


We see the use of our new ``create_view()``, ``create_sp()``,
``drop_view()``, and ``drop_sp()`` directives.  Running these to "head"
we get the following (this includes an edited view of SQL emitted)::

    $ alembic upgrade 28af9800143
    INFO  [alembic.runtime.migration] Context impl PostgresqlImpl.
    INFO  [alembic.runtime.migration] Will assume transactional DDL.
    INFO  [sqlalchemy.engine.base.Engine] BEGIN (implicit)
    INFO  [sqlalchemy.engine.base.Engine] select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s
    INFO  [sqlalchemy.engine.base.Engine] {'name': u'alembic_version'}
    INFO  [sqlalchemy.engine.base.Engine] SELECT alembic_version.version_num
    FROM alembic_version
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s
    INFO  [sqlalchemy.engine.base.Engine] {'name': u'alembic_version'}
    INFO  [alembic.runtime.migration] Running upgrade  -> 3ab8b2dfb055, create table
    INFO  [sqlalchemy.engine.base.Engine]
    CREATE TABLE customer (
        id SERIAL NOT NULL,
        name VARCHAR,
        order_count INTEGER,
        PRIMARY KEY (id)
    )


    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] INSERT INTO alembic_version (version_num) VALUES ('3ab8b2dfb055')
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [alembic.runtime.migration] Running upgrade 3ab8b2dfb055 -> 28af9800143f, create views/sp
    INFO  [sqlalchemy.engine.base.Engine] CREATE VIEW customer_view AS SELECT name, order_count FROM customer WHERE order_count > 0
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] CREATE FUNCTION add_customer_sp(name varchar, order_count integer)
        RETURNS integer AS $$
        BEGIN
            insert into customer (name, order_count)
            VALUES (in_name, in_order_count);
        END;
        $$ LANGUAGE plpgsql;

    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] UPDATE alembic_version SET version_num='28af9800143f' WHERE alembic_version.version_num = '3ab8b2dfb055'
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] COMMIT

We see that our CREATE TABLE proceeded as well as the CREATE VIEW and CREATE
FUNCTION operations produced by our new directives.


Create Revision Migrations
--------------------------

Finally, we can illustrate how we would "revise" these objects.
Let's consider we added a new column ``email`` to our ``customer`` table::

    $ alembic revision -m "add email col"

The migration is::

    """add email col

    Revision ID: 191a2d20b025
    Revises: 28af9800143f
    Create Date: 2015-07-27 16:25:59.277326

    """

    # revision identifiers, used by Alembic.
    revision = '191a2d20b025'
    down_revision = '28af9800143f'
    branch_labels = None
    depends_on = None

    from alembic import op
    import sqlalchemy as sa


    def upgrade():
        op.add_column("customer", sa.Column("email", sa.String()))


    def downgrade():
        op.drop_column("customer", "email")


We now need to recreate the ``customer_view`` view and the
``add_customer_sp`` function.   To include downgrade capability, we will
need to refer to the **previous** version of the construct; the
``replace_view()`` and ``replace_sp()`` operations we've created make
this possible, by allowing us to refer to a specific, previous revision.
the ``replaces`` and ``replace_with`` arguments accept a dot-separated
string, which refers to a revision number and an object name, such
as ``"28af9800143f.customer_view"``.  The ``ReversibleOp`` class makes use
of the :meth:`.Operations.get_context` method to locate the version file
we refer to::

    $ alembic revision -m "update views/sp"

The migration::

    """update views/sp

    Revision ID: 199028bf9856
    Revises: 191a2d20b025
    Create Date: 2015-07-27 16:26:31.344504

    """

    # revision identifiers, used by Alembic.
    revision = '199028bf9856'
    down_revision = '191a2d20b025'
    branch_labels = None
    depends_on = None

    from alembic import op
    import sqlalchemy as sa

    from foo import ReplaceableObject

    customer_view = ReplaceableObject(
        "customer_view",
        "SELECT name, order_count, email "
        "FROM customer WHERE order_count > 0"
    )

    add_customer_sp = ReplaceableObject(
        "add_customer_sp(name varchar, order_count integer, email varchar)",
        """
        RETURNS integer AS $$
        BEGIN
            insert into customer (name, order_count, email)
            VALUES (in_name, in_order_count, email);
        END;
        $$ LANGUAGE plpgsql;
        """
    )


    def upgrade():
        op.replace_view(customer_view, replaces="28af9800143f.customer_view")
        op.replace_sp(add_customer_sp, replaces="28af9800143f.add_customer_sp")


    def downgrade():
        op.replace_view(customer_view, replace_with="28af9800143f.customer_view")
        op.replace_sp(add_customer_sp, replace_with="28af9800143f.add_customer_sp")

Above, instead of using ``create_view()``, ``create_sp()``,
``drop_view()``, and ``drop_sp()`` methods, we now use ``replace_view()`` and
``replace_sp()``.  The replace operation we've built always runs a DROP *and*
a CREATE.  Running an upgrade to head we see::

    $ alembic upgrade head
    INFO  [alembic.runtime.migration] Context impl PostgresqlImpl.
    INFO  [alembic.runtime.migration] Will assume transactional DDL.
    INFO  [sqlalchemy.engine.base.Engine] BEGIN (implicit)
    INFO  [sqlalchemy.engine.base.Engine] select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s
    INFO  [sqlalchemy.engine.base.Engine] {'name': u'alembic_version'}
    INFO  [sqlalchemy.engine.base.Engine] SELECT alembic_version.version_num
    FROM alembic_version
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [alembic.runtime.migration] Running upgrade 28af9800143f -> 191a2d20b025, add email col
    INFO  [sqlalchemy.engine.base.Engine] ALTER TABLE customer ADD COLUMN email VARCHAR
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] UPDATE alembic_version SET version_num='191a2d20b025' WHERE alembic_version.version_num = '28af9800143f'
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [alembic.runtime.migration] Running upgrade 191a2d20b025 -> 199028bf9856, update views/sp
    INFO  [sqlalchemy.engine.base.Engine] DROP VIEW customer_view
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] CREATE VIEW customer_view AS SELECT name, order_count, email FROM customer WHERE order_count > 0
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] DROP FUNCTION add_customer_sp(name varchar, order_count integer)
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] CREATE FUNCTION add_customer_sp(name varchar, order_count integer, email varchar)
        RETURNS integer AS $$
        BEGIN
            insert into customer (name, order_count, email)
            VALUES (in_name, in_order_count, email);
        END;
        $$ LANGUAGE plpgsql;

    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] UPDATE alembic_version SET version_num='199028bf9856' WHERE alembic_version.version_num = '191a2d20b025'
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] COMMIT

After adding our new ``email`` column, we see that both ``customer_view``
and ``add_customer_sp()`` are dropped before the new version is created.
If we downgrade back to the old version, we see the old version of these
recreated again within the downgrade for this migration::

    $ alembic downgrade 28af9800143
    INFO  [alembic.runtime.migration] Context impl PostgresqlImpl.
    INFO  [alembic.runtime.migration] Will assume transactional DDL.
    INFO  [sqlalchemy.engine.base.Engine] BEGIN (implicit)
    INFO  [sqlalchemy.engine.base.Engine] select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s
    INFO  [sqlalchemy.engine.base.Engine] {'name': u'alembic_version'}
    INFO  [sqlalchemy.engine.base.Engine] SELECT alembic_version.version_num
    FROM alembic_version
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [alembic.runtime.migration] Running downgrade 199028bf9856 -> 191a2d20b025, update views/sp
    INFO  [sqlalchemy.engine.base.Engine] DROP VIEW customer_view
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] CREATE VIEW customer_view AS SELECT name, order_count FROM customer WHERE order_count > 0
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] DROP FUNCTION add_customer_sp(name varchar, order_count integer, email varchar)
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] CREATE FUNCTION add_customer_sp(name varchar, order_count integer)
        RETURNS integer AS $$
        BEGIN
            insert into customer (name, order_count)
            VALUES (in_name, in_order_count);
        END;
        $$ LANGUAGE plpgsql;

    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] UPDATE alembic_version SET version_num='191a2d20b025' WHERE alembic_version.version_num = '199028bf9856'
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [alembic.runtime.migration] Running downgrade 191a2d20b025 -> 28af9800143f, add email col
    INFO  [sqlalchemy.engine.base.Engine] ALTER TABLE customer DROP COLUMN email
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] UPDATE alembic_version SET version_num='28af9800143f' WHERE alembic_version.version_num = '191a2d20b025'
    INFO  [sqlalchemy.engine.base.Engine] {}
    INFO  [sqlalchemy.engine.base.Engine] COMMIT

.. _cookbook_postgresql_multi_tenancy:

Rudimental Schema-Level Multi Tenancy for PostgreSQL Databases
==============================================================

**Multi tenancy** refers to an application that accommodates for many
clients simultaneously.   Within the scope of a database migrations tool,
multi-tenancy typically refers to the practice of maintaining multiple,
identical databases where each database is assigned to one client.

Alembic does not currently have explicit multi-tenant support; typically,
the approach must involve running Alembic multiple times against different
database URLs.

One common approach to multi-tenancy, particularly on the PostgreSQL database,
is to install tenants within **individual PostgreSQL schemas**.  When using
PostgreSQL's schemas, a special variable ``search_path`` is offered that is
intended to assist with targeting of different schemas.

.. note::  SQLAlchemy includes a system of directing a common set of
   ``Table`` metadata to many schemas called `schema_translate_map <https://docs.sqlalchemy.org/core/connections.html#translation-of-schema-names>`_.   Alembic at the time
   of this writing lacks adequate support for this feature.  The recipe below
   should be considered **interim** until Alembic has more first-class support
   for schema-level multi-tenancy.

The recipe below can be altered for flexibility.  The primary purpose of this
recipe is to illustrate how to point the Alembic process towards one PostgreSQL
schema or another.

1. The model metadata used as the target for autogenerate must not include any
   schema name for tables; the schema must be non-present or set to ``None``.
   Otherwise, Alembic autogenerate will still attempt
   to compare and render tables in terms of this schema::


        class A(Base):
            __tablename__ = 'a'

            id = Column(Integer, primary_key=True)
            data = Column(UnicodeText())
            foo = Column(Integer)

            __table_args__ = {
                "schema": None
            }

   ..

2. The :paramref:`.EnvironmentContext.configure.include_schemas` flag must
   also be False or not included.

3. The "tenant" will be a schema name passed to Alembic using the "-x" flag.
   In ``env.py`` an approach like the following allows ``-xtenant=some_schema``
   to be supported by making use of :meth:`.EnvironmentContext.get_x_argument`::

        from sqlalchemy import text

        def run_migrations_online():
            connectable = engine_from_config(
                config.get_section(config.config_ini_section),
                prefix="sqlalchemy.",
                poolclass=pool.NullPool,
            )

            current_tenant = context.get_x_argument(as_dictionary=True).get("tenant")
            with connectable.connect() as connection:

                # set search path on the connection, which ensures that
                # PostgreSQL will emit all CREATE / ALTER / DROP statements
                # in terms of this schema by default
                connection.execute(text('set search_path to "%s"' % current_tenant))
                # in SQLAlchemy v2+ the search path change needs to be committed
                connection.commit()

                # make use of non-supported SQLAlchemy attribute to ensure
                # the dialect reflects tables in terms of the current tenant name
                connection.dialect.default_schema_name = current_tenant

                context.configure(
                    connection=connection,
                    target_metadata=target_metadata,
                )

                with context.begin_transaction():
                    context.run_migrations()

   The current tenant is set using the PostgreSQL ``search_path`` variable on
   the connection.  Note above we must employ a **non-supported SQLAlchemy
   workaround** at the moment which is to hardcode the SQLAlchemy dialect's
   default schema name to our target schema.

   It is also important to note that the above changes **remain on the connection
   permanently unless reversed explicitly**.  If the alembic application simply
   exits above, there is no issue.  However if the application attempts to
   continue using the above connection for other purposes, it may be necessary
   to reset these variables back to the default, which for PostgreSQL is usually
   the name "public" however may be different based on configuration.


4. Alembic operations will now proceed in terms of whichever schema we pass
   on the command line.   All logged SQL will show no schema, except for
   reflection operations which will make use of the ``default_schema_name``
   attribute::

       []$ alembic -x tenant=some_schema revision -m "rev1" --autogenerate

   ..

5. Since all schemas are to be maintained in sync, autogenerate should be run
   against only **one** schema, generating new Alembic migration files.
   Autogenerated migration operations are then run against **all** schemas.


.. _cookbook_no_empty_migrations:

Don't Generate Empty Migrations with Autogenerate
=================================================

A common request is to have the ``alembic revision --autogenerate`` command not
actually generate a revision file if no changes to the schema is detected.  Using
the :paramref:`.EnvironmentContext.configure.process_revision_directives`
hook, this is straightforward; place a ``process_revision_directives``
hook in :meth:`.MigrationContext.configure` which removes the
single :class:`.MigrationScript` directive if it is empty of
any operations::


    def run_migrations_online():

        # ...

        def process_revision_directives(context, revision, directives):
            if config.cmd_opts.autogenerate:
                script = directives[0]
                if script.upgrade_ops.is_empty():
                    directives[:] = []


        # connectable = ...

        with connectable.connect() as connection:
            context.configure(
                connection=connection,
                target_metadata=target_metadata,
                process_revision_directives=process_revision_directives
            )

            with context.begin_transaction():
                context.run_migrations()

.. _cookbook_dont_emit_drop_index:

Don't emit DROP INDEX when the table is to be dropped as well
=============================================================

MySQL may complain when dropping an index that is against a column
that also has a foreign key constraint on it.   If the table is to be dropped
in any case, the DROP INDEX isn't necessary.  This recipe will process the set
of autogenerate directives such that all :class:`.DropIndexOp` directives
are removed against tables that themselves are to be dropped::

    def run_migrations_online():

        # ...

        from alembic.operations import ops

        def process_revision_directives(context, revision, directives):
            script = directives[0]

            # process both "def upgrade()", "def downgrade()"
            for directive in (script.upgrade_ops, script.downgrade_ops):

                # make a set of tables that are being dropped within
                # the migration function
                tables_dropped = set()
                for op in directive.ops:
                    if isinstance(op, ops.DropTableOp):
                        tables_dropped.add((op.table_name, op.schema))

                # now rewrite the list of "ops" such that DropIndexOp
                # is removed for those tables.   Needs a recursive function.
                directive.ops = list(
                    _filter_drop_indexes(directive.ops, tables_dropped)
                )

        def _filter_drop_indexes(directives, tables_dropped):
            # given a set of (tablename, schemaname) to be dropped, filter
            # out DropIndexOp from the list of directives and yield the result.

            for directive in directives:
                # ModifyTableOps is a container of ALTER TABLE types of
                # commands.  process those in place recursively.
                if isinstance(directive, ops.ModifyTableOps) and \
                        (directive.table_name, directive.schema) in tables_dropped:
                    directive.ops = list(
                        _filter_drop_indexes(directive.ops, tables_dropped)
                    )

                    # if we emptied out the directives, then skip the
                    # container altogether.
                    if not directive.ops:
                        continue
                elif isinstance(directive, ops.DropIndexOp) and \
                        (directive.table_name, directive.schema) in tables_dropped:
                    # we found a target DropIndexOp.   keep looping
                    continue

                # otherwise if not filtered, yield out the directive
                yield directive

        # connectable = ...

        with connectable.connect() as connection:
            context.configure(
                connection=connection,
                target_metadata=target_metadata,
                process_revision_directives=process_revision_directives
            )

            with context.begin_transaction():
                context.run_migrations()


Whereas autogenerate, when dropping two tables with a foreign key and
an index, would previously generate something like::

    def downgrade():
        # ### commands auto generated by Alembic - please adjust! ###
        op.drop_index(op.f('ix_b_aid'), table_name='b')
        op.drop_table('b')
        op.drop_table('a')
        # ### end Alembic commands ###

With the above rewriter, it generates as::

    def downgrade():
        # ### commands auto generated by Alembic - please adjust! ###
        op.drop_table('b')
        op.drop_table('a')
        # ### end Alembic commands ###


Don't generate any DROP TABLE directives with autogenerate
==========================================================

When running autogenerate against a database that has existing tables outside
of the application's autogenerated metadata, it may be desirable to prevent
autogenerate from considering any of those existing tables to be dropped.
This will prevent autogenerate from detecting tables removed from the
local metadata as well however this is only a small caveat.

The most direct way to achieve this using the
:paramref:`.EnvironmentContext.configure.include_object` hook.   There is no
need to hardcode a fixed "whitelist" of table names; the hook gives enough
information in the given arguments to determine if a particular table name is
not part of the local :class:`.MetaData` being autogenerated, by checking first
that the type of object is ``"table"``, then that ``reflected`` is ``True``,
indicating this table name is from the local database connection, not the
:class:`.MetaData`, and finally that ``compare_to`` is ``None``, indicating
autogenerate is not comparing this :class:`.Table` to any :class:`.Table` in
the local :class:`.MetaData` collection::

    # in env.py

    def include_object(object, name, type_, reflected, compare_to):
        if type_ == "table" and reflected and compare_to is None:
            return False
        else:
            return True


    context.configure(
        # ...
        include_object = include_object
    )

.. _cookbook_custom_sorting_create_table:

Apply Custom Sorting to Table Columns within CREATE TABLE
==========================================================

This example illustrates use of the :class:`.Rewriter` object introduced
at :ref:`autogen_rewriter`.   While the rewriter grants access to the
individual :class:`.ops.MigrateOperation` objects, there are sometimes some
special techniques required to get around some structural limitations that
are present.

One is when trying to reorganize the order of columns in a
table within a :class:`.ops.CreateTableOp` directive.  This directive, when
generated by autogenerate, actually holds onto the original :class:`.Table`
object as the source of its information, so attempting to reorder the
:attr:`.ops.CreateTableOp.columns` collection will usually have no effect.
Instead, a new :class:`.ops.CreateTableOp` object may be constructed with the
new ordering.   However, a second issue is that the :class:`.Column` objects
inside will already be associated with the :class:`.Table` that is from the
model being autogenerated, meaning they can't be reassigned directly to a new
:class:`.Table`.  To get around this, we can copy all the columns and constraints
using methods like :meth:`.Column.copy`.

Below we use :class:`.Rewriter` to create a new :class:`.ops.CreateTableOp`
directive and to copy the :class:`.Column` objects from one into another,
copying each column or constraint object and applying a new sorting scheme::

    # in env.py

    from alembic.operations import ops
    from alembic.autogenerate import rewriter

    writer = rewriter.Rewriter()

    @writer.rewrites(ops.CreateTableOp)
    def order_columns(context, revision, op):

        special_names = {"id": -100, "created_at": 1001, "updated_at": 1002}

        cols_by_key = [
            (
                special_names.get(col.key, index)
                if isinstance(col, Column)
                else 2000,
                col.copy(),
            )
            for index, col in enumerate(op.columns)
        ]

        columns = [
            col for idx, col in sorted(cols_by_key, key=lambda entry: entry[0])
        ]
        return ops.CreateTableOp(
            op.table_name, columns, schema=op.schema, **op.kw)


    # ...

    context.configure(
        # ...
        process_revision_directives=writer
    )


Above, when we apply the ``writer`` to a table such as::

    Table(
        "my_table",
        m,
        Column("data", String(50)),
        Column("created_at", DateTime),
        Column("id", Integer, primary_key=True),
        Column("updated_at", DateTime),
        UniqueConstraint("data", name="uq_data")
    )


This will render in the autogenerated file as::

    def upgrade():
        # ### commands auto generated by Alembic - please adjust! ###
        op.create_table(
            "my_table",
            sa.Column("id", sa.Integer(), nullable=False),
            sa.Column("data", sa.String(length=50), nullable=True),
            sa.Column("created_at", sa.DateTime(), nullable=True),
            sa.Column("updated_at", sa.DateTime(), nullable=True),
            sa.PrimaryKeyConstraint("id"),
            sa.UniqueConstraint("data", name="uq_data"),
        )
        # ### end Alembic commands ###

Don't emit CREATE TABLE statements for Views
============================================

It is sometimes convenient to create :class:`~sqlalchemy.schema.Table` instances for views
so that they can be queried using normal SQLAlchemy techniques. Unfortunately this
causes Alembic to treat them as tables in need of creation and to generate spurious
``create_table()`` operations. This is easily fixable by flagging such Tables and using the
:paramref:`~.EnvironmentContext.configure.include_object` hook to exclude them::

    my_view = Table('my_view', metadata, autoload=True, info=dict(is_view=True))    # Flag this as a view

Or, if you use declarative tables::

    class MyView(Base):
        __tablename__ = 'my_view'
        __table_args__ = {'info': {'is_view': True}} # Flag this as a view

Then define ``include_object`` as::

    def include_object(object, name, type_, reflected, compare_to):
        """
        Exclude views from Alembic's consideration.
        """

        return not object.info.get('is_view', False)

Finally, in ``env.py`` pass your ``include_object`` as a keyword argument to :meth:`.EnvironmentContext.configure`.

.. _multiple_environments:

Run Multiple Alembic Environments from one .ini file
====================================================

Long before Alembic had the "multiple bases" feature described in :ref:`multiple_bases`,
projects had a need to maintain more than one Alembic version history in a single
project, where these version histories are completely independent of each other
and each refer to their own alembic_version table, either across multiple databases,
schemas, or namespaces.  A simple approach was added to support this, the
``--name`` flag on the commandline.

First, one would create an alembic.ini file of this form::

    [DEFAULT]
    # all defaults shared between environments go here

    sqlalchemy.url = postgresql://scott:tiger@hostname/mydatabase


    [schema1]
    # path to env.py and migration scripts for schema1
    script_location = myproject/revisions/schema1

    [schema2]
    # path to env.py and migration scripts for schema2
    script_location = myproject/revisions/schema2

    [schema3]
    # path to env.py and migration scripts for schema3
    script_location = myproject/revisions/db2

    # this schema uses a different database URL as well
    sqlalchemy.url = postgresql://scott:tiger@hostname/myotherdatabase


Above, in the ``[DEFAULT]`` section we set up a default database URL.
Then we create three sections corresponding to different revision lineages
in our project.   Each of these directories would have its own ``env.py``
and set of versioning files.   Then when we run the ``alembic`` command,
we simply give it the name of the configuration we want to use::

    alembic --name schema2 revision -m "new rev for schema 2" --autogenerate

Above, the ``alembic`` command makes use of the configuration in ``[schema2]``,
populated with defaults from the ``[DEFAULT]`` section.

The above approach can be automated by creating a custom front-end to the
Alembic commandline as well.

Print Python Code to Generate Particular Database Tables
========================================================

Suppose you have a database already, and want to generate some
``op.create_table()`` and other directives that you'd have in a migration file.
How can we automate generating that code?
Suppose the database schema looks like (assume MySQL)::

    CREATE TABLE IF NOT EXISTS `users` (
        `id` int(11) NOT NULL,
        KEY `id` (`id`)
    );

    CREATE TABLE IF NOT EXISTS `user_properties` (
      `users_id` int(11) NOT NULL,
      `property_name` varchar(255) NOT NULL,
      `property_value` mediumtext NOT NULL,
      UNIQUE KEY `property_name_users_id` (`property_name`,`users_id`),
      KEY `users_id` (`users_id`),
      CONSTRAINT `user_properties_ibfk_1` FOREIGN KEY (`users_id`)
      REFERENCES `users` (`id`) ON DELETE CASCADE
    ) ENGINE=InnoDB DEFAULT CHARSET=utf8;

Using :class:`.ops.UpgradeOps`, :class:`.ops.CreateTableOp`, and
:class:`.ops.CreateIndexOp`, we create a migration file structure,
using :class:`.Table` objects that we get from SQLAlchemy reflection.
The structure is passed to :func:`.autogenerate.render_python_code` to
produce the Python code for a migration file::

    from sqlalchemy import create_engine
    from sqlalchemy import MetaData, Table
    from alembic import autogenerate
    from alembic.operations import ops

    e = create_engine("mysql://scott:tiger@localhost/test")

    with e.connect() as conn:
        m = MetaData()
        user_table = Table('users', m, autoload_with=conn)
        user_property_table = Table('user_properties', m, autoload_with=conn)

    print(autogenerate.render_python_code(
        ops.UpgradeOps(
            ops=[
                ops.CreateTableOp.from_table(table) for table in m.tables.values()
            ] + [
                ops.CreateIndexOp.from_index(idx) for table in m.tables.values()
                for idx in table.indexes
            ]
        ))
    )

Output::

    # ### commands auto generated by Alembic - please adjust! ###
    op.create_table('users',
    sa.Column('id', mysql.INTEGER(display_width=11), autoincrement=False, nullable=False),
    mysql_default_charset='latin1',
    mysql_engine='InnoDB'
    )
    op.create_table('user_properties',
    sa.Column('users_id', mysql.INTEGER(display_width=11), autoincrement=False, nullable=False),
    sa.Column('property_name', mysql.VARCHAR(length=255), nullable=False),
    sa.Column('property_value', mysql.MEDIUMTEXT(), nullable=False),
    sa.ForeignKeyConstraint(['users_id'], ['users.id'], name='user_properties_ibfk_1', ondelete='CASCADE'),
    mysql_comment='user properties',
    mysql_default_charset='utf8',
    mysql_engine='InnoDB'
    )
    op.create_index('id', 'users', ['id'], unique=False)
    op.create_index('users_id', 'user_properties', ['users_id'], unique=False)
    op.create_index('property_name_users_id', 'user_properties', ['property_name', 'users_id'], unique=True)
    # ### end Alembic commands ###

Run Alembic Operation Objects Directly (as in from autogenerate)
================================================================

The :class:`.Operations` object has a method known as
:meth:`.Operations.invoke` that will generically invoke a particular operation
object.  We can therefore use the :func:`.autogenerate.produce_migrations`
function to run an autogenerate comparison, get back a
:class:`.ops.MigrationScript` structure representing the changes, and with a
little bit of insider information we can invoke them directly.

The traversal through the :class:`.ops.MigrationScript` structure is as
follows::

    use_batch = engine.name == "sqlite"

    stack = [migrations.upgrade_ops]
    while stack:
        elem = stack.pop(0)

        if use_batch and isinstance(elem, ModifyTableOps):
            with operations.batch_alter_table(
                elem.table_name, schema=elem.schema
            ) as batch_ops:
                for table_elem in elem.ops:
                    # work around Alembic issue #753 (fixed in 1.5.0)
                    if hasattr(table_elem, "column"):
                        table_elem.column = table_elem.column.copy()
                    batch_ops.invoke(table_elem)

        elif hasattr(elem, "ops"):
            stack.extend(elem.ops)
        else:
            # work around Alembic issue #753 (fixed in 1.5.0)
            if hasattr(elem, "column"):
                elem.column = elem.column.copy()
            operations.invoke(elem)

Above, we detect elements that have a collection of operations by looking
for the ``.ops`` attribute.   A check for :class:`.ModifyTableOps` allows
us to use a batch context if we are supporting that.   Finally there's a
workaround for an Alembic issue that exists for SQLAlchemy 1.3.20 and greater
combined with Alembic older than 1.5.

A full example follows.  The overall setup here is copied from the example
at :func:`.autogenerate.compare_metadata`::

    from sqlalchemy import Column
    from sqlalchemy import create_engine
    from sqlalchemy import Integer
    from sqlalchemy import MetaData
    from sqlalchemy import String
    from sqlalchemy import Table

    from alembic.autogenerate import produce_migrations
    from alembic.migration import MigrationContext
    from alembic.operations import Operations
    from alembic.operations.ops import ModifyTableOps


    engine = create_engine("sqlite://", echo=True)

    with engine.connect() as conn:
        conn.execute(
            """
            create table foo (
                id integer not null primary key,
                old_data varchar(50),
                x integer
            )"""
        )

        conn.execute(
            """
            create table bar (
                data varchar(50)
            )"""
        )

    metadata = MetaData()
    Table(
        "foo",
        metadata,
        Column("id", Integer, primary_key=True),
        Column("data", Integer),
        Column("x", Integer, nullable=False),
    )
    Table("bat", metadata, Column("info", String(100)))

    mc = MigrationContext.configure(engine.connect())

    migrations = produce_migrations(mc, metadata)

    operations = Operations(mc)

    use_batch = engine.name == "sqlite"

    stack = [migrations.upgrade_ops]
    while stack:
        elem = stack.pop(0)

        if use_batch and isinstance(elem, ModifyTableOps):
            with operations.batch_alter_table(
                elem.table_name, schema=elem.schema
            ) as batch_ops:
                for table_elem in elem.ops:
                    # work around Alembic issue #753 (fixed in 1.5.0)
                    if hasattr(table_elem, "column"):
                        table_elem.column = table_elem.column.copy()
                    batch_ops.invoke(table_elem)

        elif hasattr(elem, "ops"):
            stack.extend(elem.ops)
        else:
            # work around Alembic issue #753 (fixed in 1.5.0)
            if hasattr(elem, "column"):
                elem.column = elem.column.copy()
            operations.invoke(elem)




Test current database revision is at head(s)
============================================

A recipe to determine if a database schema is up to date in terms of applying
Alembic migrations.   May be useful for test or installation suites to
determine if the target database is up to date.   Makes use of the
:meth:`.MigrationContext.get_current_heads` as well as
:meth:`.ScriptDirectory.get_heads` methods so that it accommodates for a
branched revision tree::


    from alembic import config, script
    from alembic.runtime import migration
    from sqlalchemy import engine


    def check_current_head(alembic_cfg, connectable):
        # type: (config.Config, engine.Engine) -> bool
        directory = script.ScriptDirectory.from_config(alembic_cfg)
        with connectable.begin() as connection:
            context = migration.MigrationContext.configure(connection)
            return set(context.get_current_heads()) == set(directory.get_heads())

    e = engine.create_engine("mysql://scott:tiger@localhost/test", echo=True)
    cfg = config.Config("alembic.ini")
    print(check_current_head(cfg, e))

.. seealso::

    :meth:`.MigrationContext.get_current_heads`

    :meth:`.ScriptDirectory.get_heads`


.. _asyncio_recipe:

Using Asyncio with Alembic
==========================

SQLAlchemy version 1.4 introduced experimental support for asyncio, allowing
use of most of its interface from async applications. Alembic currently does
not provide an async api directly, but it can use an use SQLAlchemy Async
engine to run the migrations and autogenerate.

New configurations can use the template "async" to bootstrap an environment which
can be used with async DBAPI like asyncpg, running the command::

    alembic init -t async <script_directory_here>

Existing configurations can be updated to use an async DBAPI by updating the ``env.py``
file that's used by Alembic to start its operations. In particular only
``run_migrations_online`` will need to be updated to be something like the example below::

    import asyncio

    from sqlalchemy.ext.asyncio import async_engine_from_config

    # ... no change required to the rest of the code


    def do_run_migrations(connection):
        context.configure(connection=connection, target_metadata=target_metadata)

        with context.begin_transaction():
            context.run_migrations()


    async def run_async_migrations():
        """In this scenario we need to create an Engine
        and associate a connection with the context.

        """

        connectable = async_engine_from_config(
            config.get_section(config.config_ini_section),
            prefix="sqlalchemy.",
            poolclass=pool.NullPool,
        )

        async with connectable.connect() as connection:
            await connection.run_sync(do_run_migrations)

        await connectable.dispose()


    def run_migrations_online():
        """Run migrations in 'online' mode."""

        asyncio.run(run_async_migrations())

An async application can also interact with the Alembic api directly by using
the SQLAlchemy ``run_sync`` method to adapt the non-async api of Alembic to
an async consumer.


.. _connection_sharing_plus_asyncio:

Programmatic API use (connection sharing) With Asyncio
------------------------------------------------------

Combining the examples of :ref:`connection_sharing` with :ref:`asyncio_recipe`
together, the  ``env.py`` listed above can be updated as follows works::


    def run_migrations_online():
        """Run migrations in 'online' mode.

        """

        connectable = config.attributes.get("connection", None)

        if connectable is None:
            asyncio.run(run_async_migrations())
        else:
            do_run_migrations(connectable)

Above, using an asyncio database URL in ``alembic.ini`` one can run
commands such as ``alembic upgrade`` from the command line.  Programmatically,
the same ``env.py`` file can be invoked using asyncio as::

    import asyncio
    from sqlalchemy.ext.asyncio import create_async_engine

    from alembic import command, config


    def run_upgrade(connection, cfg):
        cfg.attributes["connection"] = connection
        command.upgrade(cfg, "head")


    async def run_async_upgrade():
        async_engine = create_async_engine("sqlite+aiosqlite://", echo=True)
        async with async_engine.begin() as conn:
            await conn.run_sync(run_upgrade, config.Config("alembic.ini"))


    asyncio.run(run_async_upgrade())

Data Migrations - General Techniques
====================================

Alembic migrations are designed for schema migrations.
The nature of data migrations are inherently different and it's not in fact advisable
in the general case to write data migrations that integrate with Alembic's
schema versioning model.
For example downgrades are difficult to address since they might require deletion of data,
which may even not be possible to detect.

.. warning::

  The solution needs to be designed specifically for each individual application and migration.
  There are no general rules and the following text is only a recommendation based on experience.

There are three basic approaches for the data migrations.

Small data
----------

Small data migrations are easy to perform, especially in cases of initial data to a new table.
These can be handled using :meth:`.Operations.bulk_insert`.

Separate migration script
-------------------------

One possibility is a completely separate script aside of alembic migrations.
The complete migration is then processed in following steps:

1. Run the initial alembic migrations (new columns etc.)
2. Run the separate data migration script
3. Run the final alembic migrations (database constraints, delete columns etc.)

The data migration script may also need a separate ORM model to handle intermediate state of the database.

Online migration
----------------

The application maintains a version of schema with both versions.
Writes are performed on both places, while the background script move all the remaining data across.
This technique is very challenging and time demanding, since it requires custom application logic to
handle the intermediate states.