Com **FastAPI** você terá todos os recursos do **Pydantic** (já que FastAPI utiliza o Pydantic para todo o controle dos dados):

* **Sem pegadinhas**:
    * Sem novas definições de esquema de micro-linguagem para aprender.
    * Se você conhece os tipos do Python, você sabe como usar o Pydantic.

Con **FastAPI** obtienes todas las características de **Pydantic** (dado que FastAPI está basado en Pydantic para todo el manejo de datos):

* **Sin dificultades para entender**:
    * No necesitas aprender un nuevo micro-lenguaje de definición de schemas.
    * Si sabes tipos de Python, sabes cómo usar Pydantic.

Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

/// check | "Inspired **FastAPI** to"

Be a micro-framework. Making it easy to mix and match the tools and parts needed.

Have a simple and easy to use routing system.

///

### <a href="https://requests.readthedocs.io" class="external-link" target="_blank">Requests</a>

这也意味着在很多情况下，你可以将从请求中获得的相同对象**直接传到数据库**，因为所有的验证都是自动的。

反之亦然，在很多情况下，你也可以将从数据库中获取的对象**直接传到客户端**。

通过 **FastAPI** 你可以获得所有 **Pydantic**  (FastAPI 基于 Pydantic 做了所有的数据处理)：

* **更简单**：
    * 没有新的模式定义 micro-language 需要学习。
    * 如果你知道 Python types，你就知道如何使用 Pydantic。
* 和你 **<abbr title="集成开发环境，和代码编辑器类似">IDE</abbr>/<abbr title="一个检查代码错误的程序">linter</abbr>/brain** 适配:

pkg debug/elf, const R_RISCV_TPREL_S R_RISCV
pkg debug/elf, method (R_RISCV) GoString() string
pkg debug/elf, method (R_RISCV) String() string
pkg debug/elf, type R_RISCV int
pkg debug/macho, const CpuArm64 = 16777228
pkg debug/macho, const CpuArm64 Cpu
pkg debug/pe, const IMAGE_DIRECTORY_ENTRY_ARCHITECTURE = 7
pkg debug/pe, const IMAGE_DIRECTORY_ENTRY_ARCHITECTURE ideal-int
pkg debug/pe, const IMAGE_DIRECTORY_ENTRY_BASERELOC = 5

    try {
      // We get the result, even if collectOneValue is a no-op, so that we can fail fast.
      // We use getUninterruptibly over getDone as a micro-optimization, we know the future is done.
      collectOneValue(index, getUninterruptibly(future));
    } catch (ExecutionException e) {
      handleException(e.getCause());

MpV,GAAK,EACvB,GAAIkV,EAAKlV,KAAOmV,EAAKnV,GACjB,OAAOA,EAGf,OAAOoV,EA8BKC,CAAalI,EAAO6H,IAASD,EAAI,EAGjC,MAEJA,IAEJ/U,IAEJ,OAAO4S,GAGX,SAASqC,GAAW9P,GAChB,IAAImQ,EAGJ,QACsB/S,IAAlBmS,GAAQvP,IACU,oBAAXtH,QACPA,QACAA,OAAOD,QAEP,IACI0X,EAAY1C,GAAa2C,MACRC,QACF,YAAcrQ,GAC7BsQ,GAAmBH,GACrB,MAAOI,GAGLhB,GAAQvP,GAAQ,KAGxB,OAAOuP,GAAQvP,GAMnB,SAASsQ,GAAmB/Q,EAAKiR,GAC7B,IAAIC,EAqBJ,OApBIlR,KAEIkR,EADApW,EAAYmW,GACLE,GAAUnR,GAEVoR,GAAapR,EAAKiR,IAKzB/C,GAAegD,EAEQ,oBAAZvR,SAA2BA,QAAQH,MAE1CG,QAAQH,KACJ,U...

 * thus paying for the cost of the expensive task.
 *
 * @author Dimitris Andreou
 * @since 13.0
 */
// TODO(user): switch to nano precision. A natural unit of cost is "bytes", and a micro precision
// would mean a maximum rate of "1MB/s", which might be small in some cases.
@Beta
@J2ktIncompatible
@GwtIncompatible
@ElementTypesAreNonnullByDefault
public abstract class RateLimiter {
  /**

 * thus paying for the cost of the expensive task.
 *
 * @author Dimitris Andreou
 * @since 13.0
 */
// TODO(user): switch to nano precision. A natural unit of cost is "bytes", and a micro precision
// would mean a maximum rate of "1MB/s", which might be small in some cases.
@Beta
@J2ktIncompatible
@GwtIncompatible
@ElementTypesAreNonnullByDefault
public abstract class RateLimiter {
  /**

E ele gera _schemas_ OpenAPI.

É assim como funciona no Flask, Starlette, Responder etc.

Mas então, nós temos novamente o problema de ter uma micro-sintaxe, dentro de uma string Python (um grande YAML).