Si vous souhaitez un rappel de 2 minutes sur l'utilisation des types en Python (même si vous ne comptez pas utiliser FastAPI), jetez un oeil au tutoriel suivant: [Python Types](python-types.md){.internal-link target=_blank}.

Vous écrivez du python standard avec des annotations de types:

```Python
from datetime import date

from pydantic import BaseModel

name: Issue Manager

on:
  schedule:
    - cron: "13 22 * * *"
  issue_comment:
    types:
      - created
  issues:
    types:
      - labeled
  pull_request_target:
    types:
      - labeled
  workflow_dispatch:

permissions:
  issues: write
  pull-requests: write

jobs:
  issue-manager:
    if: github.repository_owner == 'fastapi'
    runs-on: ubuntu-latest
    steps:

     * @param ctype2
     *            The array of character types.
     * @param val
     *            The character code.
     */
    protected static void wordChar(final byte[] ctype2, final int val) {
        ctype2[val] |= CT_ALPHA;
    }

    /**
     * Sets characters as whitespace.
     *
     * @param ctype2
     *            The array of character types.
     * @param low

  /**
   * The Photoshop File Format ({@code psd} files) as defined by <a
   * href="http://www.iana.org/assignments/media-types/image/vnd.adobe.photoshop">IANA</a>, and
   * found in {@code /etc/mime.types}, e.g. <a
   * href="http://svn.apache.org/repos/asf/httpd/httpd/branches/1.3.x/conf/mime.types"></a> of the
   * Apache <a href="http://httpd.apache.org/">HTTPD project</a>; for the specification, see <a

Primero, necesitas importar `BaseModel` de `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Crea tu modelo de datos

Luego, declaras tu modelo de datos como una clase que hereda de `BaseModel`.

Usa tipos estándar de Python para todos los atributos:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

pkg go/ast, type Scope //deprecated #52463
pkg go/types, func NewAlias(*TypeName, Type) *Alias #63223
pkg go/types, func Unalias(Type) Type #63223
pkg go/types, method (*Alias) Obj() *TypeName #63223
pkg go/types, method (*Alias) String() string #63223
pkg go/types, method (*Alias) Underlying() Type #63223
pkg go/types, method (*Info) PkgNameOf(*ast.ImportSpec) *PkgName #62037
pkg go/types, method (Checker) PkgNameOf(*ast.ImportSpec) *PkgName #62037

     */
    private final String methodName;

    /**
     * The argument types.
     */
    private final Class<?>[] argTypes;

    /**
     * Creates a {@link NoSuchMethodRuntimeException}.
     *
     * @param targetClass the target class
     * @param methodName the method name
     * @param argTypes the argument types
     * @param cause the underlying exception
     */

        patterns:
          - "*"

  - package-ecosystem: docker
    directory: /ci/devinfra/docker_windows
    schedule:
      interval: monthly
    ignore:
      - dependency-name: "*"
        update-types: ["version-update:semver-major", "version-update:semver-minor"]

  - package-ecosystem: docker
    directory: /tensorflow/tools/gcs_test
    schedule:
      interval: monthly

  - package-ecosystem: docker

import org.codelibs.fess.util.ComponentUtil;

import jakarta.annotation.PostConstruct;

/**
 * Helper class for managing file type mappings based on MIME types.
 * This class provides functionality to map MIME types to file types and
 * retrieve appropriate file type classifications for documents during indexing.
 *
 * The mappings are loaded from configuration and can be dynamically modified

		loadDriveMetrics)
}

func newCPUMetricsCache() *cachevalue.Cache[madmin.CPUMetrics] {
	loadCPUMetrics := func(ctx context.Context) (v madmin.CPUMetrics, err error) {
		types := madmin.MetricsCPU

		m := collectLocalMetrics(types, collectMetricsOpts{
			hosts: map[string]struct{}{
				globalLocalNodeName: {},
			},
		})

		for _, hm := range m.ByHost {
			if hm.CPU != nil {
				v = *hm.CPU