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 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 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 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 Now, the purpose of the migration scripts is relegated just to movement between versions on out-of-date databases, not new databases.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 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:
"""${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 EnvironmentContext.get_x_argument()
is an easy way to support
new commandline options within environment and migration scripts.
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.
See also
The Replaceable Object concept has been integrated by the 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 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,
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 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 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 Operations.implementation_for()
that run straight into 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 Operations.register_operation()
and
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 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
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. 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.
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 }
The
EnvironmentContext.configure.include_schemas
flag must also be False or not included.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 ofEnvironmentContext.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.
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
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.
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 EnvironmentContext.configure.process_revision_directives
hook, this is straightforward; place a process_revision_directives
hook in MigrationContext.configure()
which removes the
single 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()
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 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
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 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
MetaData
, and finally that compare_to
is None
, indicating
autogenerate is not comparing this Table
to any Table
in
the local 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
)
Apply Custom Sorting to Table Columns within CREATE TABLE¶
This example illustrates use of the Rewriter
object introduced
at Fine-Grained Autogenerate Generation with Rewriters. While the rewriter grants access to the
individual 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 ops.CreateTableOp
directive. This directive, when
generated by autogenerate, actually holds onto the original Table
object as the source of its information, so attempting to reorder the
ops.CreateTableOp.columns
collection will usually have no effect.
Instead, a new ops.CreateTableOp
object may be constructed with the
new ordering. However, a second issue is that the Column
objects
inside will already be associated with the Table
that is from the
model being autogenerated, meaning they can’t be reassigned directly to a new
Table
. To get around this, we can copy all the columns and constraints
using methods like Column.copy()
.
Below we use Rewriter
to create a new ops.CreateTableOp
directive and to copy the 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 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
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 EnvironmentContext.configure()
.
Run Multiple Alembic Environments from one .ini file¶
Long before Alembic had the “multiple bases” feature described in Working with 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 ops.UpgradeOps
, ops.CreateTableOp
, and
ops.CreateIndexOp
, we create a migration file structure,
using Table
objects that we get from SQLAlchemy reflection.
The structure is passed to 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 Operations
object has a method known as
Operations.invoke()
that will generically invoke a particular operation
object. We can therefore use the autogenerate.produce_migrations()
function to run an autogenerate comparison, get back a
ops.MigrationScript
structure representing the changes, and with a
little bit of insider information we can invoke them directly.
The traversal through the 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 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 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
MigrationContext.get_current_heads()
as well as
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))
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.
Programmatic API use (connection sharing) With Asyncio¶
Combining the examples of Sharing a Connection across one or more programmatic migration commands with Using Asyncio with Alembic
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())