# Module okhttp

, 👆 💪 🏤-⚙️ 😐 🔗 (👈 📨 💲) 👆 ⏪ ⚙️ 👱 🙆, & ✋️ 💲 🏆 🚫 ⚙️, 🔗 🔜 🛠️:

{* ../../docs_src/dependencies/tutorial006.py hl[9,14] *}

## 🔗 👪 *➡ 🛠️*

⏪, 🕐❔ 👂 🔃 ❔ 📊 🦏 🈸 ([🦏 🈸 - 💗 📁](../../tutorial/bigger-applications.md){.internal-link target=_blank}), 🎲 ⏮️ 💗 📁, 👆 🔜 💡 ❔ 📣 👁 `dependencies` 🔢 👪 *➡ 🛠️*.

## 🌐 🔗

# ==============================================================================


"""Converts MSYS Linux-like paths stored in env variables to Windows paths.

This is necessary on Windows, because some applications do not understand/handle
Linux-like paths MSYS uses, for example, Docker.
"""

import argparse
import os


def should_convert(var_name: str,
                   blacklist: list[str] | None,

## Usa `CORSMiddleware`

Puedes configurarlo en tu aplicación **FastAPI** usando el `CORSMiddleware`.

* Importa `CORSMiddleware`.
* Crea una lista de orígenes permitidos (como strings).
* Agrégalo como un "middleware" a tu aplicación **FastAPI**.

También puedes especificar si tu backend permite:

* Credenciales (headers de autorización, cookies, etc).

# WSGI inkludieren – Flask, Django und andere

Sie können WSGI-Anwendungen mounten, wie Sie es in [Unteranwendungen – Mounts](sub-applications.md){.internal-link target=_blank}, [Hinter einem Proxy](behind-a-proxy.md){.internal-link target=_blank} gesehen haben.

Dazu können Sie die `WSGIMiddleware` verwenden und damit Ihre WSGI-Anwendung wrappen, zum Beispiel Flask, Django usw.

## `WSGIMiddleware` verwenden

Sie müssen `WSGIMiddleware` importieren.

# Middleware Avanzado

En el tutorial principal leíste cómo agregar [Middleware Personalizado](../tutorial/middleware.md){.internal-link target=_blank} a tu aplicación.

Y luego también leíste cómo manejar [CORS con el `CORSMiddleware`](../tutorial/cors.md){.internal-link target=_blank}.

En esta sección veremos cómo usar otros middlewares.

## Agregando middlewares ASGI

		Bucket:    bucket,
		Quota:     data,
		UpdatedAt: updatedAt,
	}
	if quotaConfig.Size == 0 && quotaConfig.Quota == 0 {
		bucketMeta.Quota = nil
	}

	// Call site replication hook.
	replLogIf(ctx, globalSiteReplicationSys.BucketMetaHook(ctx, bucketMeta))

	// Write success response.
	writeSuccessResponseHeadersOnly(w)
}

			if evt.Action.Delete() {
				globalExpiryState.enqueueByDays(objInfo, evt, lcEventSrc_s3ListObjects)
				if !evt.Action.DeleteRestored() {
					continue
				} // queue version for replication upon expired restored copies if needed.
			}
		}

		queueReplicationHeal(ctx, o.Bucket, objInfo, o.Replication, 0)
	}
	return
}

# Description:
# TensorFlow is a computational framework, primarily for use in machine
# learning applications.

load("@rules_cc//cc:cc_import.bzl", "cc_import")
load("@bazel_skylib//lib:selects.bzl", "selects")
load("@bazel_skylib//rules:common_settings.bzl", "bool_flag", "bool_setting")
load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda")
load(
    "//tensorflow:tensorflow.bzl",
    "VERSION",
    "VERSION_MAJOR",
    "check_deps",

			globalBucketMetadataSys.Init(GlobalContext, buckets, newObject)
		})

		// initialize replication resync state.
		bootstrapTrace("initResync", func() {
			globalReplicationPool.Get().initResync(GlobalContext, buckets, newObject)
		})

		// Initialize site replication manager after bucket metadata
		bootstrapTrace("globalSiteReplicationSys.Init", func() {