## ASGI Servers

Let's go a little deeper into the details.

FastAPI uses a standard for building Python web frameworks and servers called <abbr title="Asynchronous Server Gateway Interface">ASGI</abbr>. FastAPI is an ASGI web framework.

## Installation

<div class="termy">

```console
$ pip install fastapi

---> 100%
```

</div>

			err = x.setIdx(i, *ver)
		default:
			x.versions = append(x.versions[:i], x.versions[i+1:]...)
			// if uv has tiered content we add a
			// free-version to track it for
			// asynchronous deletion via scanner.
			if freeVersion, toFree := ver.ObjectV2.InitFreeVersion(fi); toFree {
				err = x.addVersion(freeVersion)
			}
		}

		if fi.Deleted {
			err = x.addVersion(ventry)
		}

	}

	// Empty fi.VersionID indicates that versioning is either
	// suspended or disabled on this bucket. RenameData will replace
	// the 'null' version. We add a free-version to track its tiered
	// content for asynchronous deletion.
	//
	// Note: RestoreObject and HealObject requests don't end up replacing the
	// null version and therefore don't require the free-version to track
	// anything

   * set (including {@linkplain #setFuture set asynchronously}). When a call to this method returns,
   * the {@code Future} is guaranteed to be {@linkplain #isDone done} <b>only if</b> the call was
   * accepted (in which case it returns {@code true}). If it returns {@code false}, the {@code
   * Future} may have previously been set asynchronously, in which case its result may not be known

		// whether to replicate as the target could be temporarily down
		opts.TargetArn = tgtArn
		replicate := cfg.Replicate(opts)
		var synchronous bool
		if tgt != nil {
			synchronous = tgt.replicateSync
		}
		dsc.Set(newReplicateTargetDecision(tgtArn, replicate, synchronous))
	}
	return dsc
}

// Standard headers that needs to be extracted from User metadata.
var standardHeaders = []string{

*   Updates `sqlite3` to `3.44.0` to keep in sync with master branch.

# Release 2.4.0

\## Major Features and Improvements

*   `tf.distribute` introduces experimental support for asynchronous training of
    models via the
    [`tf.distribute.experimental.ParameterServerStrategy`](https://www.tensorflow.org/api_docs/python/tf/distribute/experimental/ParameterServerStrategy)
    API. Please see the