See the full documentation here.
Adds extensions to SQLAlchemy (and/or Alembic) which allows declaratively stating the existence of additional kinds of objects about your database not natively supported by SQLAlchemy/Alembic.
This includes:
The primary function(s) of this library include:
metadata.create_all
creates these objects.alembic revision --autogenerate
automatically creates/updates/deletes
declared objects.from sqlalchemy import Column, types, select
from sqlalchemy.orm import as_declarative
from sqlalchemy_declarative_extensions import (
declarative_database, Schemas, Roles, Row, View, view,
)
from sqlalchemy_declarative_extensions.dialects.postgresql import (
DefaultGrant, Function, Trigger, Role
)
from sqlalchemy_declarative_extensions.audit import audit
@declarative_database
@as_declarative
class Base:
# Note: each object type also has a plural version (i.e. Schemas/Roles/etc) where you can specify
# collection-level options like `ignore_unspecified`).
#
# If you dont set any collection-level options, you can instead use raw list/iterable as the collection.
schemas = Schemas().are("example")
roles = Roles(ignore_unspecified=True).are(
Role("read", login=False),
Role(
"app",
in_roles=['read']
),
)
grants = [
DefaultGrant.on_tables_in_schema("public", 'example').grant("select", to="read"),
DefaultGrant.on_sequences_in_schema("public").grant("usage", to="read"),
Grant.new("usage", to="read").on_schemas("example")
]
rows = [
Row('foo', id=1),
]
views = [
View("low_foo", "select * from foo where i < 10"),
]
functions = [
Function(
"fancy_function",
"""
BEGIN
INSERT INTO foo (id) select NEW.id + 1;
RETURN NULL;
END
""",
language="plpgsql",
returns="trigger",
),
]
triggers = [
Trigger.after("insert", on="foo", execute="fancy_function")
.named("on_insert_foo")
.when("pg_trigger_depth() < 1")
.for_each_row(),
]
@audit()
class Foo(Base):
__tablename__ = 'foo'
id = Column(types.Integer(), primary_key=True)
audit_table = Foo.__audit_table__
@view(Base)
class HighFoo:
__tablename__ = "high_foo"
__view__ = select(Foo.__table__).where(Foo.__table__.c.id >= 10)
Note, there is also support for declaring objects directly through the
MetaData
for users not using sqlalchemy's declarative API.
By default, the above example does not automatically do anything. Depending on
the context, you can use one of two registration hooks:
register_sqlalchemy_events
or register_alembic_events
.
register_sqlalchemy_events
This registers events in SQLAlchemy's event system such that a
metadata.create_all(...)
call will create the declared database objects.
from sqlalchemy_declarative_extensions import register_sqlalchemy_events
metadata = Base.metadata # Given the example above.
register_sqlalchemy_events(metadata)
# Which is equivalent to...
register_sqlalchemy_events(metadata, schemas=False, roles=False, grants=False, rows=False)
All object types are opt in, and should be explicitly included in order to get registered.
Practically, this is to avoid issues with testing. In most cases the
metadata.create_all
call will be run in tests, a context where it's more
likely that you dont need grants or grants, and where parallel test
execution could lead to issues with role or schema creation, depending on your
setup.
register_alembic_events
This registers comparators in Alembic's registration system such that an
alembic revision --autogenerate
command will diff the existing database state
against the declared database objects, and issue statements to
create/update/delete objects in order to match the declared state.
# alembic's `env.py`
from sqlalchemy_declarative_extensions import register_alembic_events
register_alembic_events()
# Which is equivalent to...
register_sqlalchemy_events(schemas=True, roles=True, grants=True, rows=True)
All object types are opt out but can be excluded.
In contrast to register_sqlalchemy_events
, it's much more likely that you're
declaring most of these object types in order to have alembic track them
In principle, this library can absolutely support any database supported by SQLAlchemy, and capable of being introspected enough to support detection of different kinds of objects.
As you can see below, in reality the existence of implementations are going to be purely driven by actual usage. The current maintainer(s) primarily use PostgreSQL and as such individual features for other databases will either suffer or lack implementation.
Postgres | MySQL | SQLite | Snowflake | |
---|---|---|---|---|
Schema | ✓ | N/A | ✓ | ✓ |
View | ✓ | ✓ | ✓ | ✓ |
Role | ✓ | N/A | ✓ | |
Grant | ✓ | N/A | ||
Default Grant | ✓ | N/A | ||
Function | ✓ | * | ||
Trigger | ✓ | * | ||
Database | ✓ | ✓ | ||
Row (data) | ✓ | ✓ | ✓ | ✓ |
"Audit Table" | ✓ |
note "Row" is implemented with pure SQLAlchemy concepts, so should work for any dialect that you can use SQLAlchemy to connect to.
The asterisks above note pending or provisional support through basic test cases. The level of expertise in each dialects' particular behaviors is not uniform, and deciding on the correct behavior for those dialects will require users to submit issues/fixes!
Supporting a new dialect can be as simple as providing the dialect-dispatched implementations for detecting existing objects of the given type. Very much the intent is that once a given object type is supported at all, the comparison infrastructure for that type should make it straightforward to support other dialects. At the end of the day, this library is primarily producing SQL statements, so in theory any dialect supporting a given object type should be able to be supported.
In such cases (like Grants/Roles) that different dialects support wildly different options/syntax, there are also patterns for defining dialect-specific objects, to mediate any additional differences.
Alembic Utils is the primary library against which this library can be compared. At time of writing, most (but not all) object types supported by alembic-utils are supported by this library. One might begin to question when to use which library.
Below is a list of points on which the two libraries diverge. But note that you can certainly use both in tandem! It doesn't need to be one or the other, and certainly for any object types which do not overlap, you might need to use both.
Database Support
Alembic Utils seems to explicitly only support PostgreSQL.
This library is designed to support any dialect (in theory). Certainly PostgreSQL is best supported, but there does exist support for specific kinds of objects to varying levels of support for SQLite and MySQL, so far.
Architecture
Alembic Utils is directly tied to Alembic and does not support SQLAlchemy's
MetaData.create_all
. It's also the responsibility of the user to
discover/register objects in alembic.
This library depends only on SQLAlchemy, although it also supports
alembic. Support for MetaData.create_all
can be important for creating all
object types in tests. It also is designed such that objects are registered
on the MetaData
itself, so there is no need for any specific discovery
phase.
Scope
Alembic Utils declares specific, individual objects. I.e. you instantiate
one specific PGGrantTable
or PGView
instance and Alembic know knows you
want that object to be created. It cannot drop objects it is not already
aware of.
This library declares ths objects the system as a whole expects to exist. Similar to Alembic's behavior on tables, it will (by default) detect any undeclared objects that should not exist and drop them. That means, you can rely on this object to ensure the state of your migrations matches the state of your database exactly.
Migration history
(In fact, this can be a sticking point, trying to convert away from
alembic_utils
, because it will attempt to drop all the (e.g PGView
)
instances previously created when we replaced it with this library.)
--autogenerate
-time only.Abstraction Level
Alembic Utils appears to define a very "literal" interface (for example,
PGView
accepts the whole view definition as a raw literal string).
This library tries to, as much as possible, provide a more abstracted
interface that enables more compatibility with SQLAlchemy (For example
View
accepts SQLAlchemy objects which can be coerced into a SELECT
). It
also tends towards "builder" interfaces which progressively produce a object
(Take a look at the DefaultGrant
above, for an example of where that's
helpful).
A separate note on conversion/compatibility. Where possible, this library tries
to support alembic-utils native objects as stand-ins for the objects defined in
this library. For example, alembic_utils.pg_view.PGView
can be declared
instead of a sqlalchemy_declarative_extensions.View
, and we will internally
coerce it into the appropriate type. Hopefully this eases any transitional
costs, or issues using one or the other library.