#  And ReplaceSchema task basically ignores this.
        #
        #  Normally this 'except' means no getting meta data for excepted tables.
        #  (so the tables are not existing in SchemaHTML and HistoryHTML and so on).
        #  But you can specify the '@gen' suffix that means generate-only except.
        #  A table with the mark can be treated as documents but no generating classes.
        #

module.  An independent module is a module which is not derived from or
based on this library.  If you modify this library, you may extend this
exception to your version of the library, but you are not obligated to
do so.  If you do not wish to do so, delete this exception statement

Es war eines der ersten extrem schnellen Python-Frameworks, welches auf `asyncio` basierte. Es wurde so gestaltet, dass es Flask sehr ähnlich ist.

!!! note "Technische Details"
    Es verwendete <a href="https://github.com/MagicStack/uvloop" class="external-link" target="_blank">`uvloop`</a> anstelle der standardmäßigen Python-`asyncio`-Schleife. Das hat es so schnell gemacht.

      echo "JAVA_HOME is set to \"$JAVA_HOME\", but \"\$JAVA_HOME/bin/java\" does not exist." >&2
      exit 1
    fi
  fi
else
  JAVACMD="`\\unset -f command; \\command -v java`"

  if [ ! -x "$JAVACMD" ] ; then
    echo "The java(1) command does not exist in PATH nor is JAVA_HOME set, so Apache Maven cannot be started." >&2
    exit 1
  fi

    ```Python hl_lines="10"
    {!> ../../../docs_src/security/tutorial001.py!}
    ```

Aber das ist immer noch nicht so nützlich.

Lassen wir es uns den aktuellen Benutzer überreichen.

## Ein Benutzermodell erstellen

Erstellen wir zunächst ein Pydantic-Benutzermodell.

So wie wir Pydantic zum Deklarieren von Bodys verwenden, können wir es auch überall sonst verwenden:

=== "Python 3.10+"

        be available. However, if that file:// url references a
        file-share, as in the case of an NFS or SMB mount, that will
        be unavailable.

  So, offline mode has several implications, some of which may not be
  altogether obvious:

  * Localhost may be unavailable. Therefore, even locally installed
    server processes which work by conversing over a port may fail.

So, what we will do next is add the code to document how that *external API* should look like to receive the callback from *your API*.

          exchange.responseHeadersStart()
          invokeStartEvent = false
        }
        if (responseBuilder == null) {
          if (requestBody.isDuplex()) {
            // Prepare a duplex body so that the application can send a request body later.
            exchange.flushRequest()
            val bufferedRequestBody = exchange.createRequestBody(request, true).buffer()
            requestBody.writeTo(bufferedRequestBody)

**FastAPI** is fully compatible with (and based on) <a href="https://www.starlette.io/" class="external-link" target="_blank"><strong>Starlette</strong></a>. So, any additional Starlette code you have, will also work.

`FastAPI` is actually a sub-class of `Starlette`. So, if you already know or use Starlette, most of the functionality will work the same way.

import jetbrains.buildServer.configs.kotlin.AbsoluteId
import jetbrains.buildServer.configs.kotlin.DslContext

fun DslContext.initForTest() {
    // Set the project id here, so we can use methods on the DslContext
    parentProjectId = AbsoluteId("Gradle")
    projectId = AbsoluteId("Gradle_Master")
    settingsRootId = AbsoluteId("GradleMaster")
    settingsRoot.name = "GradleMaster"
    addParameters("Branch" to "master")