# `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

## Documenting webhooks with **FastAPI** and OpenAPI { #documenting-webhooks-with-fastapi-and-openapi }

With **FastAPI**, using OpenAPI, you can define the names of these webhooks, the types of HTTP operations that your app can send (e.g. `POST`, `PUT`, etc.) and the request **bodies** that your app would send.

/*
 * © 2025 CodeLibs, Inc.
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of

     *
     * @return minimum size in bytes for compression to be beneficial
     */
    int getMinCompressionSize();

    /**
     * Gets the maximum data size that can be compressed in a single operation.
     *
     * @return maximum size in bytes that can be compressed
     */
    int getMaxCompressionSize();

    /**
     * Gets a human-readable name for the compression algorithm.
     *

# Form Models { #form-models }

You can use **Pydantic models** to declare **form fields** in FastAPI.

/// info

To use forms, first install <a href="https://github.com/Kludex/python-multipart" class="external-link" target="_blank">`python-multipart`</a>.

Make sure you create a [virtual environment](../virtual-environments.md){.internal-link target=_blank}, activate it, and then install it, for example:

```console
$ pip install python-multipart
```

## Why distributed MinIO?

MinIO in distributed mode can help you setup a highly-available storage system with a single object storage deployment. With distributed MinIO, you can optimally use storage devices, irrespective of their location in a network.

### Data protection

### 提供 `root_path`

为此，要以如下方式使用命令行选项 `--root-path`：

<div class="termy">

```console
$ uvicorn main:app --root-path /api/v1

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

Hypercorn 也支持 `--root-path `选项。

/// note | 技术细节

ASGI 规范定义的 `root_path` 就是为了这种用例。

Um dies zu erreichen, können Sie die Kommandozeilenoption `--root-path` wie folgt verwenden:

<div class="termy">

```console
$ uvicorn main:app --root-path /api/v1

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

Falls Sie Hypercorn verwenden, das hat auch die Option `--root-path`.

/// note | Technische Details

plugins: forked-1.1.3, xdist-1.31.0, cov-2.8.1
collected 6 items

---> 100%

test_main.py <span style="color: green; white-space: pre;">......                            [100%]</span>

<span style="color: green;">================= 1 passed in 0.03s =================</span>
```

### Concurrency + Parallelism: Web + Machine Learning { #concurrency-parallelism-web-machine-learning }

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.