!!! tip
        Prefer to use the `Annotated` version if possible.

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

This dependency will provide a `str` that is assigned to the parameter `token` of the *path operation function*.

**FastAPI** will know that it can use this dependency to define a "security scheme" in the OpenAPI schema (and the automatic API docs).

## Description from docstring

As descriptions tend to be long and cover multiple lines, you can declare the *path operation* description in the function <abbr title="a multi-line string as the first expression inside a function (not assigned to any variable) used for documentation">docstring</abbr> and **FastAPI** will read it from there.

### <a href="https://falconframework.org/" class="external-link" target="_blank">Falcon</a>

Falcon is another high performance Python framework, it is designed to be minimal, and work as the foundation of other frameworks like Hug.

It is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, which in turn is designed based on Requests, so it's very familiar and intuitive.

With it, you can use <a href="https://docs.pytest.org/" class="external-link" target="_blank">pytest</a> directly with **FastAPI**.

## Using `TestClient`

!!! info

!!! tip
    You might remember that request bodies are also declared with Pydantic models.

    Here **FastAPI** won't get confused because you are using `Depends`.

!!! check
    The way this dependency system is designed allows us to have different dependencies (different "dependables") that all return a `User` model.

    We are not restricted to having only one dependency that can return that type of data.

## Other models

    ```

## 📛 ⚪️➡️ #️⃣

📛 😑 📏 &amp; 📔 💗 ⏸, 👆 💪 📣 *➡ 🛠️* 📛 🔢 <abbr title="a multi-line string as the first expression inside a function (not assigned to any variable) used for documentation"> #️⃣ </abbr> &amp; **FastAPI** 🔜 ✍ ⚫️ ⚪️➡️ 📤.

👆 💪 ✍ <a href="https://en.wikipedia.org/wiki/Markdown" class="external-link" target="_blank">✍</a> #️⃣ , ⚫️ 🔜 🔬 &amp; 🖥 ☑ (✊ 🔘 🏧 #️⃣ 📐).

---

"_If anyone is looking to build a production Python API, I would highly recommend **FastAPI**. It is **beautifully designed**, **simple to use** and **highly scalable**, it has become a **key component** in our API first development strategy and is driving many automations and services such as our Virtual TAC Engineer._"

This was designed this way mainly to allow using the same objects "yielded" by dependencies inside of background tasks, because the exit code would be executed after the background tasks were finished.

Now create Pydantic *models* (schemas) that will be used when reading data, when returning it from the API.

For example, before creating an item, we don't know what will be the ID assigned to it, but when reading it (when returning it from the API) we will already know its ID.

The same way, when reading a user, we can now declare that `items` will contain the items that belong to this user.

# Dependencies

**FastAPI** has a very powerful but intuitive **<abbr title="also known as components, resources, providers, services, injectables">Dependency Injection</abbr>** system.

It is designed to be very simple to use, and to make it very easy for any developer to integrate other components with **FastAPI**.

## What is "Dependency Injection"