* Generate <a href="https://json-schema.org" class="external-link" target="_blank">JSON Schema</a> definitions for your model, you can also use them anywhere else you like if it makes sense for your project.

#### "Schema" { #schema }

A "schema" is a definition or description of something. Not the code that implements it, but just an abstract description.

#### API "schema" { #api-schema }

In this case, <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank">OpenAPI</a> is a specification that dictates how to define a schema of your API.

* Validation and documentation from these types.
* Dependency Injection system.

It doesn't use a data validation, serialization and documentation third-party library like Pydantic, it has its own. So, these data type definitions would not be reusable as easily.

### Sub-dependencies { #sub-dependencies }

You can have multiple dependencies and [sub-dependencies](tutorial/dependencies/sub-dependencies.md){.internal-link target=_blank} requiring each other (as parameters of the function definitions), some of them might be created with `async def` and some with normal `def`. It would still work, and the ones created with normal `def` would be called on an external thread (from the threadpool) instead of being "awaited".

				<configuration>
					<encoding>UTF-8</encoding>
					<properties>
						<year>2025</year>
					</properties>
					<headerDefinitions>
						<headerDefinition>https://www.codelibs.org/assets/license/header-definition-2.xml</headerDefinition>
					</headerDefinitions>
					<licenseSets>
						<licenseSet>
							<header>https://www.codelibs.org/assets/license/header.txt</header>
							<includes>

Sie können eine Pfadoperation auch nicht erneut definieren:

{* ../../docs_src/path_params/tutorial003b.py hl[6,11] *}

Die erste Definition wird immer verwendet werden, da ihr Pfad zuerst übereinstimmt.

## Vordefinierte Parameterwerte

With **FastAPI** you get all of **Pydantic**'s features (as FastAPI is based on Pydantic for all the data handling):

* **No brainfuck**:
    * No new schema definition micro-language to learn.
    * If you know Python types you know how to use Pydantic.

{* ../../docs_src/python_types/tutorial001.py hl[2] *}

### Edit it { #edit-it }

It's a very simple program.

But now imagine that you were writing it from scratch.

At some point you would have started the definition of the function, you had the parameters ready...

But then you have to call "that method that converts the first letter to upper case".

Was it `upper`? Was it `uppercase`? `first_uppercase`? `capitalize`?

### Sous-dépendances

### Sub-dependencias

Puedes tener múltiples dependencias y [sub-dependencias](tutorial/dependencies/sub-dependencies.md){.internal-link target=_blank} requiriéndose mutuamente (como parámetros de las definiciones de funciones), algunas de ellas podrían ser creadas con `async def` y algunas con `def` normal. Aun funcionará, y las que fueron creadas con `def` normal serían llamadas en un hilo externo (del threadpool) en lugar de ser "awaited".