tag-template: maven-$RESOLVED_VERSION

# Override replacers to strip backport branch prefixes and handle JIRA links
replacers:
  # Strip backport branch prefixes like [maven-4.0.x], [maven-3.x], etc.
  - search: '/^\[maven-[\d\.x-]+\]\s*-?\s*/g'
    replace: ''
  # Convert JIRA ticket references to links (but not maven branch prefixes)
  - search: '/\[([A-Z]+)-(\d+)\]\s*-?\s*/g'

For that, you can use the `WSGIMiddleware` and use it to wrap your WSGI application, for example, Flask, Django, etc.

## Using `WSGIMiddleware` { #using-wsgimiddleware }

You need to import `WSGIMiddleware`.

Then wrap the WSGI (e.g. Flask) app with the middleware.

And then mount that under a path.

#include "tensorflow/core/platform/macros.h"

namespace tensorflow {

// Convenience macros for asserting and handling exceptional conditions, for
// C structs, including `TF_OpKernelContext`, `TF_Status`, etc. This is analogus
// to the macros in tensorflow/core/framework/op_requires.h. This is provided
// for plugin OpKernel developer's convenience.

#define C_OPKERNELCONTEXT_REQUIRES_OK(CTX, C_STATUS, __VA_ARGS__) \

Usar `BackgroundTasks` también funciona con el sistema de inyección de dependencias, puedes declarar un parámetro de tipo `BackgroundTasks` en varios niveles: en una *path operation function*, en una dependencia (dependable), en una sub-dependencia, etc.

**FastAPI** sabe qué hacer en cada caso y cómo reutilizar el mismo objeto, de modo que todas las tareas en segundo plano se combinan y ejecutan en segundo plano después:

You can import it directly from `fastapi`:

```python
from fastapi import Depends
```

::: fastapi.Depends

## `Security()`

For many scenarios, you can handle security (authorization, authentication, etc.) with dependencies, using `Depends()`.

But when you want to also declare OAuth2 scopes, you can use `Security()` instead of `Depends()`.

You can import `Security()` directly from `fastapi`:

```python

Por exemplo, "**Python 3.6+**" significa que é compatível com o Python 3.6 ou superior (incluindo o 3.7, 3.8, 3.9, 3.10, etc). E "**Python 3.9+**" significa que é compatível com o Python 3.9 ou mais recente (incluindo o 3.10, etc).

Por ejemplo, "**Python 3.6+**" significa que es compatible con Python 3.6 o superior (incluyendo 3.7, 3.8, 3.9, 3.10, etc). Y "**Python 3.9+**" significa que es compatible con Python 3.9 o superior (incluyendo 3.10, etc).

Si puedes usar las **últimas versiones de Python**, utiliza los ejemplos para la última versión, esos tendrán la **mejor y más simple sintaxis**, por ejemplo, "**Python 3.10+**".

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

```sh
aws s3api put-object --bucket testbucket --key lockme --object-lock-mode GOVERNANCE --object-lock-retain-until-date "2019-11-20"  --body /etc/issue
```

See <https://docs.aws.amazon.com/AmazonS3/latest/dev/object-lock-overview.html> for AWS S3 spec on object locking and permissions required for object retention and governance bypass overrides.

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

/// tip