WIP - Pydantic v2 support (#1238)
* WIP * WIP - make test_model_definition tests pass * WIP - make test_model_methods pass * WIP - make whole test suit at least run - failing 49/443 tests * WIP fix part of the getting pydantic tests as types of fields are now kept in core schema and not on fieldsinfo * WIP fix validation in update by creating individual fields validators, failing 36/443 * WIP fix __pydantic_extra__ in intializing model, fix test related to pydantic config checks, failing 32/442 * WIP - fix enum schema in model_json_schema, failing 31/442 * WIP - fix copying through model, fix setting pydantic fields on through, fix default config and inheriting from it, failing 26/442 * WIP fix tests checking pydantic schema, fix excluding parent fields, failing 21/442 * WIP some missed files * WIP - fix validators inheritance and fix validators in generated pydantic, failing 17/442 * WIP - fix through models setting - only on reverse side of relation, but always on reverse side, failing 15/442 * WIP - fix through models setting - only on reverse side of relation, but always on reverse side, failing 15/442 * WIP - working on proper populating __dict__ for relations for new schema dumping, some work on openapi docs, failing 13/442 * WIP - remove property fields as pydantic has now computed_field on its own, failing 9/442 * WIP - fixes in docs, failing 8/442 * WIP - fix tests for largebinary schema, wrapped bytes fields fail in pydantic, will be fixed in pydantic-core, remaining is circural schema for related models, failing 6/442 * WIP - fix to pk only models in schemas * Getting test suites to pass (#1249) * wip, fixing tests * iteration, fixing some more tests * iteration, fixing some more tests * adhere to comments * adhere to comments * remove unnecessary dict call, re-add getattribute for testing * todo for reverse relationship * adhere to comments, remove prints * solve circular refs * all tests pass 🎉 * remove 3.7 from tests * add lint and type check jobs * reforat with ruff, fix jobs * rename jobs * fix imports * fix evaluate in py3.8 * partially fix coverage * fix coverage, add more tests * fix test ids * fix test ids * fix lint, fix docs, make docs fully working scripts, add test docs job * fix pyproject * pin py ver in test docs * change dir in test docs * fix pydantic warning hack * rm poetry call in test_docs * switch to pathlib in test docs * remove coverage req test docs * fix type check tests, fix part of types * fix/skip next part of types * fix next part of types * fix next part of types * fix coverage * fix coverage * fix type (bit dirty 🤷) * fix some code smells * change pre-commit * tweak workflows * remove no root from tests * switch to full python path by passing sys.executable * some small refactor in new base model, one sample test, change makefile * small refactors to reduce complexity of methods * temp add tests for prs against pydantic_v2 * remove all references to __fields__ * remove all references to construct, deprecate the method and update model_construct to be in line with pydantic * deprecate dict and add model_dump, todo switch to model_dict in calls * fix tests * change to union * change to union * change to model_dump and model_dump_json from dict and json deprecated methods, deprecate them in ormar too * finish switching dict() -> model_dump() * finish switching json() -> model_dump_json() * remove fully pydantic_only * switch to extra for payment card, change missed json calls * fix coverage - no more warnings internal * fix coverage - no more warnings internal - part 2 * split model_construct into own and pydantic parts * split determine pydantic field type * change to new field validators * fix benchmarks, add codspeed instead of pytest-benchmark, add action and gh workflow * restore pytest-benchmark * remove codspeed * pin pydantic version, restore codspeed * change on push to pydantic_v2 to trigger first one * Use lifespan function instead of event (#1259) * check return types * fix imports order, set warnings=False on json that passes the dict, fix unnecessary loop in one of the test * remove references to model's meta as it's now ormar config, rename related methods too * filter out pydantic serializer warnings * remove choices leftovers * remove leftovers after property_fields, keep only enough to exclude them in initialization * add migration guide * fix meta references * downgrade databases for now * Change line numbers in documentation (#1265) * proofread and fix the docs, part 1 * proofread and fix the docs for models * proofread and fix the docs for fields * proofread and fix the docs for relations * proofread and fix rest of the docs, add release notes for 0.20 * create tables in new docs src * cleanup old deps, uncomment docs publish on tag * fix import reorder --------- Co-authored-by: TouwaStar <30479449+TouwaStar@users.noreply.github.com> Co-authored-by: Goran Mekić <meka@tilda.center>
This commit is contained in:
collerek
@ -21,7 +21,7 @@
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### Overview
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The `ormar` package is an async mini ORM for Python, with support for **Postgres,
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The `ormar` package is an async ORM for Python, with support for **Postgres,
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MySQL**, and **SQLite**.
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The main benefits of using `ormar` are:
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@ -53,13 +53,7 @@ Yet remember that those are - well - tests and not all solutions are suitable to
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### Part of the `fastapi` ecosystem
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As part of the fastapi ecosystem `ormar` is supported in libraries that somehow work with databases.
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As of now `ormar` is supported by:
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* [`fastapi-users`](https://github.com/frankie567/fastapi-users)
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* [`fastapi-crudrouter`](https://github.com/awtkns/fastapi-crudrouter)
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* [`fastapi-pagination`](https://github.com/uriyyo/fastapi-pagination)
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As part of the fastapi ecosystem `ormar` is supported in selected libraries that somehow work with databases.
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Ormar remains sql dialect agnostic - so only columns working in all supported backends are implemented.
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@ -76,7 +70,6 @@ Ormar is built with:
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* [`sqlalchemy core`][sqlalchemy-core] for query building.
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* [`databases`][databases] for cross-database async support.
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* [`pydantic`][pydantic] for data validation.
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* `typing_extensions` for python 3.6 - 3.7
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### License
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@ -128,17 +121,20 @@ For tests and basic applications the `sqlalchemy` is more than enough:
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# 1. Imports
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import sqlalchemy
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import databases
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import ormar
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# 2. Initialization
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DATABASE_URL = "sqlite:///db.sqlite"
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database = databases.Database(DATABASE_URL)
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metadata = sqlalchemy.MetaData()
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base_ormar_config = ormar.OrmarConfig(
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metadata=sqlalchemy.MetaData(),
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database=databases.Database(DATABASE_URL),
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engine=sqlalchemy.create_engine(DATABASE_URL),
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)
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# Define models here
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# 3. Database creation and tables creation
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engine = sqlalchemy.create_engine(DATABASE_URL)
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metadata.create_all(engine)
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base_ormar_config.metadata.create_all(engine)
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```
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For a sample configuration of alembic and more information regarding migrations and
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@ -175,45 +171,39 @@ Note that you can find the same script in examples folder on github.
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from typing import Optional
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import databases
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import pydantic
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import ormar
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import sqlalchemy
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DATABASE_URL = "sqlite:///db.sqlite"
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database = databases.Database(DATABASE_URL)
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metadata = sqlalchemy.MetaData()
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# note that this step is optional -> all ormar cares is a internal
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# class with name Meta and proper parameters, but this way you do not
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# have to repeat the same parameters if you use only one database
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class BaseMeta(ormar.ModelMeta):
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metadata = metadata
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database = database
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base_ormar_config = ormar.OrmarConfig(
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metadata=sqlalchemy.MetaData(),
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database=databases.Database(DATABASE_URL),
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engine = sqlalchemy.create_engine(DATABASE_URL),
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)
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# note that this step is optional -> all ormar cares is a field with name
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# ormar_config # and proper parameters, but this way you do not have to repeat
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# the same parameters if you use only one database
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#
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# Note that all type hints are optional
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# below is a perfectly valid model declaration
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# class Author(ormar.Model):
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# class Meta(BaseMeta):
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# tablename = "authors"
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# ormar_config = base_ormar_config.copy(tablename="authors")
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#
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# id = ormar.Integer(primary_key=True) # <= notice no field types
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# name = ormar.String(max_length=100)
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class Author(ormar.Model):
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class Meta(BaseMeta):
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tablename = "authors"
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ormar_config = base_ormar_config.copy(tablename="authors")
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=100)
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class Book(ormar.Model):
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class Meta(BaseMeta):
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tablename = "books"
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ormar_config = base_ormar_config.copy(tablename="books")
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id: int = ormar.Integer(primary_key=True)
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author: Optional[Author] = ormar.ForeignKey(Author)
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@ -224,10 +214,9 @@ class Book(ormar.Model):
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# create the database
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# note that in production you should use migrations
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# note that this is not required if you connect to existing database
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engine = sqlalchemy.create_engine(DATABASE_URL)
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# just to be sure we clear the db before
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metadata.drop_all(engine)
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metadata.create_all(engine)
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base_ormar_config.metadata.drop_all(engine)
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base_ormar_config.metadata.create_all(engine)
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# all functions below are divided into functionality categories
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@ -662,9 +651,7 @@ The following keyword arguments are supported on all field types.
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* `server_default: Any`
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* `index: bool`
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* `unique: bool`
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* `choices: typing.Sequence`
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* `name: str`
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* `pydantic_only: bool`
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All fields are required unless one of the following is set:
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@ -674,7 +661,6 @@ All fields are required unless one of the following is set:
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* `server_default` - Set a default value for the field on server side (like sqlalchemy's `func.now()`). **Not available for relation fields**
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* `primary key` with `autoincrement` - When a column is set to primary key and autoincrement is set on this column.
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Autoincrement is set by default on int primary keys.
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* `pydantic_only` - Field is available only as normal pydantic field, not stored in the database.
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### Available signals
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