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docs/en/docs/how-to/conditional-openapi.md
* Configure any required permissions and roles using dependencies. * Never store plaintext passwords, only password hashes. * Implement and use well-known cryptographic tools, like Passlib and JWT tokens, etc. * Add more granular permission controls with OAuth2 scopes where needed. * ...etc.
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docs/en/docs/python-types.md
This is just a **quick tutorial / refresher** about Python type hints. It covers only the minimum necessary to use them with **FastAPI**... which is actually very little. **FastAPI** is all based on these type hints, they give it many advantages and benefits. But even if you never use **FastAPI**, you would benefit from learning a bit about them. !!! note
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docs/pt/docs/tutorial/background-tasks.md
seja executado pelo mesmo processo (por exemplo, você não precisa compartilhar memória, variáveis, etc), você pode se beneficiar do uso de outras ferramentas maiores, como <a href="http://www.celeryproject.org/" class="external-link" target="_blank"> Celery </a>. Eles tendem a exigir configurações mais complexas, um gerenciador de fila de mensagens/tarefas, como RabbitMQ ou Redis, mas permitem que você execute tarefas em segundo plano em vários processos e, especialmente, em vários servidores....
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docs/de/docs/tutorial/background-tasks.md
unbedingt vom selben Prozess ausgeführt werden müssen (z. B. müssen Sie Speicher, Variablen, usw. nicht gemeinsam nutzen), könnte die Verwendung anderer größerer Tools wie z. B. <a href="https://docs.celeryq.dev" class="external-link" target="_blank">Celery</a> von Vorteil sein. Sie erfordern in der Regel komplexere Konfigurationen und einen Nachrichten-/Job-Queue-Manager wie RabbitMQ oder Redis, ermöglichen Ihnen jedoch die Ausführung von Hintergrundtasks in mehreren Prozessen und insbesondere...
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tests/test_tutorial/test_query_params/test_tutorial005.py
from fastapi.testclient import TestClient from docs_src.query_params.tutorial005 import app client = TestClient(app) def test_foo_needy_very(): response = client.get("/items/foo?needy=very") assert response.status_code == 200 assert response.json() == {"item_id": "foo", "needy": "very"} def test_foo_no_needy(): response = client.get("/items/foo") assert response.status_code == 422
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docs/en/docs/deployment/concepts.md
If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly). ### Examples of Replication Tools and Strategies
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docs/pt/docs/contributing.md
Mas uma vez que você tenha concluído, você poderá testar tudo como se parecesse _online_. Para fazer isso, primeiro construa toda a documentação: <div class="termy"> ```console // Use o comando "build-all", isso leverá um tempinho $ python ./scripts/docs.py build-all Updating es Updating en Building docs for: en Building docs for: es Successfully built docs for: es Copying en index.md to README.md ```
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tests/test_tutorial/test_schema_extra_example/test_tutorial001_py310.py
@needs_py310 @needs_pydanticv2 def test_post_body_example(client: TestClient): response = client.put( "/items/5", json={ "name": "Foo", "description": "A very nice Item", "price": 35.4, "tax": 3.2, }, ) assert response.status_code == 200 @needs_py310 @needs_pydanticv2 def test_openapi_schema(client: TestClient):
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docs_src/schema_extra_example/tutorial001_pv1.py
price: float tax: Union[float, None] = None class Config: schema_extra = { "examples": [ { "name": "Foo", "description": "A very nice Item", "price": 35.4, "tax": 3.2, } ] } @app.put("/items/{item_id}") async def update_item(item_id: int, item: Item):
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docs_src/schema_extra_example/tutorial001_py310.py
price: float tax: float | None = None model_config = { "json_schema_extra": { "examples": [ { "name": "Foo", "description": "A very nice Item", "price": 35.4, "tax": 3.2, } ] } } @app.put("/items/{item_id}") async def update_item(item_id: int, item: Item):
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