#!/usr/bin/env/python

import boto3
from botocore.client import Config

s3 = boto3.client('s3',
        endpoint_url='http://localhost:9000',
        aws_access_key_id='YOUR-ACCESSKEYID',
        aws_secret_access_key='YOUR-SECRETACCESSKEY',
        config=Config(signature_version='s3v4'),
        region_name='us-east-1')


def _add_header(request, **kwargs):
    request.headers.add_header('x-minio-extract', 'true')

These functions are there (instead of just using the classes directly) so that your editor doesn't mark errors about their types.

That way you can use your normal editor and coding tools without having to add custom configurations to disregard those errors.

Pero al revisar benchmarks y comparaciones, debes tener en cuenta lo siguiente.

## Benchmarks y velocidad

  /**
   * Returns the minimum of the two values. If the values compare as 0, the first is returned.
   *
   * <p>The recommended solution for finding the {@code minimum} of some values depends on the type
   * of your data and the number of elements you have. Read more in the Guava User Guide article on
   * <a href="https://github.com/google/guava/wiki/CollectionUtilitiesExplained#comparators">{@code
   * Comparators}</a>.
   *

You can use any template engine you want with **FastAPI**.

A common choice is Jinja2, the same one used by Flask and other tools.

There are utilities to configure it easily that you can use directly in your **FastAPI** application (provided by Starlette).

## Install dependencies { #install-dependencies }

## OpenAPI condicional desde configuraciones y variables de entorno

Puedes usar fácilmente las mismas configuraciones de Pydantic para configurar tu OpenAPI generado y las interfaces de usuario de la documentación.

Por ejemplo:

{* ../../docs_src/conditional_openapi/tutorial001.py hl[6,11] *}

    * You wouldn't write an application in Uvicorn directly. That would mean that your code would have to include more or less, at least, all the code provided by Starlette (or **FastAPI**). And if you did that, your final application would have the same overhead as having used a framework and minimizing your app code and bugs.
    * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.

Por ejemplo, podrías usarlo para añadir metadatos para una interfaz de usuario frontend, etc.

///

/// info | Información

OpenAPI 3.1.0 (usado desde FastAPI 0.99.0) añadió soporte para `examples`, que es parte del estándar de **JSON Schema**.

## Memória

Se você executar **um único processo por contêiner**, terá uma quantidade mais ou menos bem definida, estável e limitada de memória consumida por cada um desses contêineres (mais de um se eles forem replicados).

Ele foi um dos primeiros exemplos de **documentação automática de API**, e essa foi especificamente uma das primeiras idéias que inspirou "a busca por" **FastAPI**.

/// note | Nota

Django REST Framework foi criado por Tom Christie. O mesmo criador de Starlette e Uvicorn, nos quais **FastAPI** é baseado.

///

/// check | **FastAPI** inspirado para