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docs/en/docs/deployment/manually.md
* Restarts * Replication (the number of processes running) * Memory * Previous steps before starting
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docs/en/docs/advanced/behind-a-proxy.md
In these cases you can use `root_path` to configure your application. The `root_path` is a mechanism provided by the ASGI specification (that FastAPI is built on, through Starlette). The `root_path` is used to handle these specific cases. And it's also used internally when mounting sub-applications. ## Proxy with a stripped path prefix
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docs/en/docs/deployment/concepts.md
In most cases, the same tool that is used to **run the program on startup** is also used to handle automatic **restarts**. For example, this could be handled by: * Docker * Kubernetes * Docker Compose * Docker in Swarm Mode * Systemd * Supervisor * Handled internally by a cloud provider as part of their services * Others... ## Replication - Processes and Memory
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docs/en/docs/release-notes.md
* [Override the default exception handlers](https://fastapi.tiangolo.com/tutorial/handling-errors/#override-the-default-exception-handlers). * [Re-use **FastAPI's** exception handlers](https://fastapi.tiangolo.com/tutorial/handling-errors/#re-use-fastapis-exception-handlers). * PR [#273](https://github.com/tiangolo/fastapi/pull/273).
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pyproject.toml
"W", # pycodestyle warnings "F", # pyflakes "I", # isort "B", # flake8-bugbear "C4", # flake8-comprehensions "UP", # pyupgrade ] ignore = [ "E501", # line too long, handled by black "B008", # do not perform function calls in argument defaults "C901", # too complex "W191", # indentation contains tabs ] [tool.ruff.lint.per-file-ignores] "__init__.py" = ["F401"]
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docs/en/docs/advanced/websockets.md
Notice that the query `token` will be handled by a dependency. With that you can connect the WebSocket and then send and receive messages: <img src="/img/tutorial/websockets/image05.png"> ## Handling disconnections and multiple clients When a WebSocket connection is closed, the `await websocket.receive_text()` will raise a `WebSocketDisconnect` exception, which you can then catch and handle like in this example.
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docs/en/docs/features.md
* Numbers (`int`, `float`) with min and max values, etc. * Validation for more exotic types, like: * URL. * Email. * UUID. * ...and others. All the validation is handled by the well-established and robust **Pydantic**. ### Security and authentication Security and authentication integrated. Without any compromise with databases or data models.
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docs/en/mkdocs.yml
advanced/conditional-openapi.md: how-to/conditional-openapi.md advanced/extending-openapi.md: how-to/extending-openapi.md mkdocstrings: handlers: python: options: extensions: - griffe_typingdoc show_root_heading: true show_if_no_docstring: true preload_modules: - httpx
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docs/en/docs/advanced/wsgi.md
And then mount that under a path. ```Python hl_lines="2-3 23" {!../../../docs_src/wsgi/tutorial001.py!} ``` ## Check it Now, every request under the path `/v1/` will be handled by the Flask application. And the rest will be handled by **FastAPI**. If you run it and go to <a href="http://localhost:8000/v1/" class="external-link" target="_blank">http://localhost:8000/v1/</a> you will see the response from Flask: ```txt
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docs/en/docs/deployment/docker.md
the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So, each request could be handled by one of the multiple **replicated containers** running your app. And normally this **load balancer** would be able to handle requests that go to *other* apps in your cluster (e.g. to a different domain, or under a different URL path prefix), and would transmit that communication to the right containers...
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