You can combine normal FastAPI *path operations* with GraphQL on the same application.

/// tip

**GraphQL** solves some very specific use cases.

It has **advantages** and **disadvantages** when compared to common **web APIs**.

Make sure you evaluate if the **benefits** for your use case compensate the **drawbacks**. 🤓

///

## GraphQL Libraries { #graphql-libraries }

```Python
q: Annotated[str, Query()] = "rick"
```

...or in older code bases you will find:

```Python
q: str = Query(default="rick")
```

### Advantages of `Annotated` { #advantages-of-annotated }

**Using `Annotated` is recommended** instead of the default value in function parameters, it is **better** for multiple reasons. 🤓

import java.util.stream.LongStream;
import org.jspecify.annotations.Nullable;

/**
 * An immutable array of {@code long} values, with an API resembling {@link List}.
 *
 * <p>Advantages compared to {@code long[]}:
 *
 * <ul>
 *   <li>All the many well-known advantages of immutability (read <i>Effective Java</i>, third
 *       edition, Item 17).
 *   <li>Has the value-based (not identity-based) {@link #equals}, {@link #hashCode}, and {@link

import org.jspecify.annotations.Nullable;

/**
 * An immutable array of {@code double} values, with an API resembling {@link List}.
 *
 * <p>Advantages compared to {@code double[]}:
 *
 * <ul>
 *   <li>All the many well-known advantages of immutability (read <i>Effective Java</i>, third
 *       edition, Item 17).
 *   <li>Has the value-based (not identity-based) {@link #equals}, {@link #hashCode}, and {@link

import java.util.stream.IntStream;
import org.jspecify.annotations.Nullable;

/**
 * An immutable array of {@code int} values, with an API resembling {@link List}.
 *
 * <p>Advantages compared to {@code int[]}:
 *
 * <ul>
 *   <li>All the many well-known advantages of immutability (read <i>Effective Java</i>, third
 *       edition, Item 17).
 *   <li>Has the value-based (not identity-based) {@link #equals}, {@link #hashCode}, and {@link

## Requirements { #requirements }

After testing several alternatives, I decided that I was going to use [**Pydantic**](https://docs.pydantic.dev/) for its advantages.

Then I contributed to it, to make it fully compliant with JSON Schema, to support different ways to define constraint declarations, and to improve editor support (type checks, autocompletion) based on the tests in several editors.

Define a file parameter with a type of `UploadFile`:

{* ../../docs_src/request_files/tutorial001_an_py310.py hl[14] *}

Using `UploadFile` has several advantages over `bytes`:

* You don't have to use `File()` in the default value of the parameter.
* It uses a "spooled" file:

This is just a **quick tutorial / refresher** about Python type hints. It covers only the minimum necessary to use them with **FastAPI**... which is actually very little.

**FastAPI** is all based on these type hints, they give it many advantages and benefits.

But even if you never use **FastAPI**, you would benefit from learning a bit about them.

/// note

If you are a Python expert, and you already know everything about type hints, skip to the next chapter.

따라서 (가능하면) 다음과 같이 사용합니다:

```Python
q: Annotated[str, Query()] = "rick"
```

...또는 오래된 코드베이스에서는 다음과 같은 코드를 찾게 될 것입니다:

```Python
q: str = Query(default="rick")
```

### `Annotated`의 장점 { #advantages-of-annotated }

함수 매개변수의 기본값 방식 대신 **`Annotated`를 사용하는 것을 권장**합니다. 여러 이유로 **더 좋기** 때문입니다. 🤓

**함수 매개변수**의 **기본값**이 **실제 기본값**이 되므로, 전반적으로 Python에 더 직관적입니다. 😌

Using Linux containers has several advantages including **security**, **replicability**, **simplicity**, and others.

/// tip

In a hurry and already know this stuff? Jump to the [`Dockerfile` below 👇](#build-a-docker-image-for-fastapi).

///

<details>