And it shows their true commitment to FastAPI and its **community** (you), as they not only want to provide you a **good service** but also want to make sure you have a **good and healthy framework**, FastAPI. 🙇

For example, you might want to try <a href="https://speakeasyapi.dev/?utm_source=fastapi+repo&utm_medium=github+sponsorship" class="external-link" target="_blank">Speakeasy</a>.

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

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"_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

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"_Мы использовали библиотеку **FastAPI** для создания сервера **REST**, к которому можно делать запросы для получения **прогнозов**. [для Ludwig]_"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

"_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>微软</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

「_我们选择了 **FastAPI** 来创建用于获取**预测结果**的 **REST** 服务。[用于 Ludwig]_」

# Behind a Proxy

In some situations, you might need to use a **proxy** server like Traefik or Nginx with a configuration that adds an extra path prefix that is not seen by your application.

In these cases you can use `root_path` to configure your application.

The `root_path` is a mechanism provided by the ASGI specification (that FastAPI is built on, through Starlette).

The `root_path` is used to handle these specific cases.

It uses the information from Webargs and Marshmallow to automatically generate OpenAPI schemas, using APISpec.

It's a great tool, very underrated. It should be way more popular than many Flask plug-ins out there. It might be due to its documentation being too concise and abstract.

This solved having to write YAML (another syntax) inside of Python docstrings.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

This schema definition includes your API paths, the possible parameters they take, etc.

#### Data "schema"

The term "schema" might also refer to the shape of some data, like a JSON content.

In that case, it would mean the JSON attributes, and data types they have, etc.

#### OpenAPI and JSON Schema

If something seems interesting and useful to your project, go ahead and check it, but otherwise, you might probably just skip them.

!!! tip