For instructions or titles in imperative, keep them in imperative, for example "Edit it" to "Edítalo".

---

For the next terms, use the following translations:

* framework: framework (do not translate to "marco")
* performance: rendimiento
* program (verb): programar
* code (verb): programar
* type hints: anotaciones de tipos
* type annotations: anotaciones de tipos
* autocomplete: autocompletado

pkg debug/macho, type LoadCmd uint32
pkg debug/macho, type Nlist32 struct
pkg debug/macho, type Nlist32 struct, Desc uint16
pkg debug/macho, type Nlist32 struct, Name uint32
pkg debug/macho, type Nlist32 struct, Sect uint8
pkg debug/macho, type Nlist32 struct, Type uint8
pkg debug/macho, type Nlist32 struct, Value uint32
pkg debug/macho, type Nlist64 struct
pkg debug/macho, type Nlist64 struct, Desc uint16

Dentro de la función, puedes acceder a todos los atributos del objeto modelo directamente:

{* ../../docs_src/body/tutorial002_py310.py *}

/// info | Información

En Pydantic v1 el método se llamaba `.dict()`, se marcó como obsoleto (pero sigue soportado) en Pydantic v2, y se renombró a `.model_dump()`.

Los ejemplos aquí usan `.dict()` por compatibilidad con Pydantic v1, pero deberías usar `.model_dump()` si puedes usar Pydantic v2.

///

          "interval": "",
          "legendFormat": "[{{drive}}:{{api}}]",
          "refId": "B"
        }
      ],
      "title": "Drive Latency (micro sec)",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "description": "",
      "fieldConfig": {

Kullanıcılar için otomatik API dökümantasyonu sunan bir web arayüzüne sahip olmalı.

///

### <a href="https://flask.palletsprojects.com" class="external-link" target="_blank">Flask</a>

Flask bir <abbr title="Mikro Framework: Micro Framework">mikro framework</abbr> olduğundan Django gibi framework'lerin aksine veritabanı entegrasyonu gibi Django ile gelen pek çok özelliği direkt barındırmaz.

		return nil, nil, errInvalidArgument
	}

	// prepare getElapsedTime() to calculate elapsed time since we started trying formatting disks.
	// All times are rounded to avoid showing milli, micro and nano seconds
	formatStartTime := time.Now().Round(time.Second)
	getElapsedTime := func() string {
		return time.Now().Round(time.Second).Sub(formatStartTime).String()
	}

	var (
		tries   int

  language: en
repo_name: fastapi/fastapi
repo_url: https://github.com/fastapi/fastapi
plugins:
  social:
    cards_layout_options:
      logo: ../en/docs/img/icon-white.svg
  typeset: null
  search: null
  macros:
    include_yaml:
    - github_sponsors: ../en/data/github_sponsors.yml
    - people: ../en/data/people.yml
    - contributors: ../en/data/contributors.yml
    - translators: ../en/data/translators.yml

Asia/Hovd Asia/Irkutsk Asia/Istanbul Asia/Jakarta Asia/Jayapura Asia/Jerusalem Asia/Kabul Asia/Kamchatka Asia/Karachi Asia/Kashgar Asia/Kathmandu Asia/Katmandu Asia/Khandyga Asia/Kolkata Asia/Krasnoyarsk Asia/Kuala_Lumpur Asia/Kuching Asia/Kuwait Asia/Macao Asia/Macau Asia/Magadan Asia/Makassar Asia/Manila Asia/Muscat Asia/Nicosia Asia/Novokuznetsk Asia/Novosibirsk Asia/Omsk Asia/Oral Asia/Phnom_Penh Asia/Pontianak Asia/Pyongyang Asia/Qatar Asia/Qostanay Asia/Qyzylorda Asia/Rangoon Asia/Riyadh Asia/Saigon...

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.

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.