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docs/en/docs/advanced/behind-a-proxy.md
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docs/en/docs/deployment/concepts.md
This Manager Process would probably be the one listening on the **port** in the IP. And it would transmit all the communication to the worker processes. Those worker processes would be the ones running your application, they would perform the main computations to receive a **request** and return a **response**, and they would load anything you put in variables in RAM.
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docs/en/docs/deployment/docker.md
This is what you would want to do in **most cases**, for example: * Using **Kubernetes** or similar tools * When running on a **Raspberry Pi** * Using a cloud service that would run a container image for you, etc. ### Package Requirements You would normally have the **package requirements** for your application in some file.
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docs/en/docs/benchmarks.md
* **Uvicorn**: * Will have the best performance, as it doesn't have much extra code apart from the server itself. * You wouldn't write an application in Uvicorn directly. That would mean that your code would have to include more or less, at least, all the code provided by Starlette (or **FastAPI**). And if you did that, your final application would have the same overhead as having used a framework and minimizing your app code and bugs.
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docs/en/docs/advanced/generate-clients.md
</div> #### Generate Client Code To generate the client code you can use the command line application `openapi-ts` that would now be installed. Because it is installed in the local project, you probably wouldn't be able to call that command directly, but you would put it on your `package.json` file. It could look like this: ```JSON hl_lines="7" { "name": "frontend-app", "version": "1.0.0", "description": "",
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docs/en/docs/deployment/server-workers.md
And **Uvicorn** has a **Gunicorn-compatible worker class**. Using that combination, Gunicorn would act as a **process manager**, listening on the **port** and the **IP**. And it would **transmit** the communication to the worker processes running the **Uvicorn class**.
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fastapi/security/oauth2.py
) class OAuth2(SecurityBase): """ This is the base class for OAuth2 authentication, an instance of it would be used as a dependency. All other OAuth2 classes inherit from it and customize it for each OAuth2 flow. You normally would not create a new class inheriting from it but use one of the existing subclasses, and maybe compose them if you want to support multiple flows.
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docs/en/docs/advanced/settings.md
But every time we do: ```Python Settings() ``` a new `Settings` object would be created, and at creation it would read the `.env` file again. If the dependency function was just like: ```Python def get_settings(): return Settings() ``` we would create that object for each request, and we would be reading the `.env` file for each request. ⚠️
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docs/en/docs/advanced/openapi-webhooks.md
```Python hl_lines="9-13 36-53" {!../../../docs_src/openapi_webhooks/tutorial001.py!} ``` The webhooks that you define will end up in the **OpenAPI** schema and the automatic **docs UI**. !!! info The `app.webhooks` object is actually just an `APIRouter`, the same type you would use when structuring your app with multiple files.
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docs/en/docs/tutorial/extra-models.md
If it was in a type annotation we could have used the vertical bar, as: ```Python some_variable: PlaneItem | CarItem ``` But if we put that in `response_model=PlaneItem | CarItem` we would get an error, because Python would try to perform an **invalid operation** between `PlaneItem` and `CarItem` instead of interpreting that as a type annotation.
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