Aber irgendwann gab es keine andere Möglichkeit, als etwas zu schaffen, das all diese Funktionen bereitstellte, die besten Ideen früherer Tools aufnahm und diese auf die bestmögliche Weise kombinierte, wobei Sprachfunktionen verwendet wurden, die vorher noch nicht einmal verfügbar waren (Python 3.6+ Typhinweise).

</blockquote>

## Investigation

= vendor/github.com/antlr4-go/antlr/v4 licensed under: =

Copyright (c) 2012-2023 The ANTLR Project. All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:

1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.

# Advanced User Guide

## Additional Features

The main [Tutorial - User Guide](../tutorial/index.md){.internal-link target=_blank} should be enough to give you a tour through all the main features of **FastAPI**.

In the next sections you will see other options, configurations, and additional features.

!!! tip
    The next sections are **not necessarily "advanced"**.

    And it's possible that for your use case, the solution is in one of them.

# Experimental filesystem C APIs for TensorFlow.
# Will be moved in proper place once all filesystems are converted to the
# modular framework.
load("//tensorflow:tensorflow.bzl", "tf_cc_test")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

# This is only for plugins
cc_library(
    name = "filesystem_interface",

Langkah pertama adalah dengan meng-install FastAPI.

Untuk tutorial, kamu mungkin hendak meng-installnya dengan semua pilihan fitur dan dependensinya:

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%
```

</div>

...yang juga termasuk `uvicorn`, yang dapat kamu gunakan sebagai server yang menjalankan kodemu.

!!! note "Catatan"
    Kamu juga dapat meng-installnya bagian demi bagian.

El primer paso es instalar FastAPI.

Para el tutorial, es posible que quieras instalarlo con todas las dependencias y características opcionales:

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%
```

</div>

...eso también incluye `uvicorn` que puedes usar como el servidor que ejecuta tu código.

!!! note "Nota"
    También puedes instalarlo parte por parte.

e.g.:
To download `2021/taxes.csv` archived in `financial.zip` and stored under a bucket named `company-data`, you can issue a GET request using the following path 'company-data/financial.zip/2021/taxes.csv`

## Contents properties

  build2 --> project3
  
  project4["project"]
  build2 --> project4

```

### Build process state

The "build process state" holds the global state of the build process and manages all the other state.

The build process state also includes state that is tied to a particular Gradle user home directory.
When that directory changes between Gradle invocations, the state is discarded and recreated.

    val testNameParameterName = "testName"
    val testTaskOptionsParameterName = "testTaskOptions"
    val daemon = true
    applyDefaultSettings(os, arch, buildJvm = BuildToolBuildJvm, timeout = 0)

    // Show all failed tests here, since that is what we are interested in
    failureConditions.supportTestRetry = false

    requirements = "//:requirements_lock_" + TF_PYTHON_VERSION.replace(".", "_") + ".txt",
)

load("@pypi//:requirements.bzl", "install_deps")

install_deps()

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.