* 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>
222 lines
6.2 KiB
Markdown
222 lines
6.2 KiB
Markdown
# Fastapi
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The use of ormar with fastapi is quite simple.
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Apart from connecting to databases at startup everything else
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you need to do is substitute pydantic models with ormar models.
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Here you can find a very simple sample application code.
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!!!warning
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This example assumes that you already have a database created. If that is not the case please visit [database initialization][database initialization] section.
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!!!tip
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The following example (all sections) should be put in one file.
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It's divided into subsections for clarity.
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!!!note
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If you want to read more on how you can use ormar models in fastapi requests and
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responses check the [responses](response.md) and [requests](requests.md) documentation.
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## Quick Start
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!!!note
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Note that you can find the full quick start script in the [github](https://github.com/collerek/ormar) repo under examples.
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### Imports and initialization
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Define startup and shutdown procedures using FastAPI lifespan and use is in the
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application.
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```python
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from typing import List, Optional
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import databases
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import sqlalchemy
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from fastapi import FastAPI
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import ormar
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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@asynccontextmanager
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async def lifespan(_: FastAPI) -> AsyncIterator[None]:
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if not config.database.is_connected:
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await config.database.connect()
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yield
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if config.database.is_connected:
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await config.database.disconnect()
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base_ormar_config = ormar.OrmarConfig(
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metadata=sqlalchemy.MetaData(),
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database=databases.Database("sqlite:///test.db"),
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)
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app = FastAPI(lifespan=lifespan(base_ormar_config))
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```
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!!!info
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You can read more on connecting to databases in [fastapi][fastapi] documentation
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### Models definition
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Define ormar models with appropriate fields.
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Those models will be used instead of pydantic ones.
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```python
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base_ormar_config = OrmarConfig(
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metadata = metadata
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database = database
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)
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class Category(ormar.Model):
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ormar_config = base_ormar_config.copy(tablename="categories")
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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 Item(ormar.Model):
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ormar_config = base_ormar_config.copy()
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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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category: Optional[Category] = ormar.ForeignKey(Category, nullable=True)
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```
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!!!tip
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You can read more on defining `Models` in [models][models] section.
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### Fastapi endpoints definition
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Define your desired endpoints, note how `ormar` models are used both
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as `response_model` and as a requests parameters.
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```python
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@app.get("/items/", response_model=List[Item])
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async def get_items():
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items = await Item.objects.select_related("category").all()
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return items
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@app.post("/items/", response_model=Item)
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async def create_item(item: Item):
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await item.save()
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return item
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@app.post("/categories/", response_model=Category)
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async def create_category(category: Category):
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await category.save()
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return category
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@app.put("/items/{item_id}")
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async def get_item(item_id: int, item: Item):
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item_db = await Item.objects.get(pk=item_id)
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return await item_db.update(**item.model_dump())
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@app.delete("/items/{item_id}")
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async def delete_item(item_id: int, item: Item = None):
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if item:
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return {"deleted_rows": await item.delete()}
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item_db = await Item.objects.get(pk=item_id)
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return {"deleted_rows": await item_db.delete()}
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```
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!!!note
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Note how ormar `Model` methods like save() are available straight out of the box after fastapi initializes it for you.
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!!!note
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Note that you can return a `Model` (or list of `Models`) directly - fastapi will jsonize it for you
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### Test the application
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#### Run fastapi
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If you want to run this script and play with fastapi swagger install uvicorn first
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`pip install uvicorn`
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And launch the fastapi.
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`uvicorn <filename_without_extension>:app --reload`
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Now you can navigate to your browser (by default fastapi address is `127.0.0.1:8000/docs`) and play with the api.
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!!!info
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You can read more about running fastapi in [fastapi][fastapi] docs.
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#### Test with pytest
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Here you have a sample test that will prove that everything works as intended.
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Be sure to create the tables first. If you are using pytest you can use a fixture.
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```python
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@pytest.fixture(autouse=True, scope="module")
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def create_test_database():
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engine = sqlalchemy.create_engine(DATABASE_URL)
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metadata.create_all(engine)
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yield
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metadata.drop_all(engine)
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```
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```python
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# here is a sample test to check the working of the ormar with fastapi
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from starlette.testclient import TestClient
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def test_all_endpoints():
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# note that TestClient is only sync, don't use asyns here
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client = TestClient(app)
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# note that you need to connect to database manually
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# or use client as contextmanager during tests
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with client as client:
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response = client.post("/categories/", json={"name": "test cat"})
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category = response.json()
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response = client.post(
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"/items/", json={"name": "test", "id": 1, "category": category}
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)
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item = Item(**response.json())
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assert item.pk is not None
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response = client.get("/items/")
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items = [Item(**item) for item in response.json()]
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assert items[0] == item
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item.name = "New name"
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response = client.put(f"/items/{item.pk}", json=item.model_dump())
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assert response.json() == item.model_dump()
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response = client.get("/items/")
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items = [Item(**item) for item in response.json()]
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assert items[0].name == "New name"
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response = client.delete(f"/items/{item.pk}", json=item.model_dump())
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assert response.json().get("deleted_rows", "__UNDEFINED__") != "__UNDEFINED__"
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response = client.get("/items/")
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items = response.json()
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assert len(items) == 0
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```
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!!!tip
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If you want to see more test cases and how to test ormar/fastapi see [tests][tests] directory in the github repo
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!!!info
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You can read more on testing fastapi in [fastapi][fastapi] docs.
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[fastapi]: https://fastapi.tiangolo.com/
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[models]: ../models/index.md
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[database initialization]: ../models/migrations.md
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[tests]: https://github.com/collerek/ormar/tree/master/tests
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