---
name: Spelling
on: [pull_request]

jobs:
  run:
    name: Spell Check with Typos
    runs-on: ubuntu-latest
    steps:
    - name: Checkout Actions Repository
      uses: actions/checkout@v4

    - name: Check spelling of repo

Krishnan Parthasarathi <******@****.***> 1743662706 -0700

https://github.com/google/guava/wiki/HowToContribute#code-contributions
and
https://github.com/google/guava/blob/master/CONTRIBUTING.md
before sending a pull request.

We generally welcome PRs for fixing trivial bugs or typos, but please refrain
from sending a PR with significant changes unless explicitly requested.

        this.plugin = plugin;
    }

    public PluginNotFoundException(Plugin plugin, List<ArtifactRepository> remoteRepositories) {
        super(
                "Plugin could not be found, please check its coordinates for typos and ensure the required"
                        + " plugin repositories are defined in the POM",
                plugin.getGroupId(),
                plugin.getArtifactId(),
                plugin.getVersion(),

2. **Commits**:
   - Write clear messages: what changed and why (e.g., “Refactor S3 API handler to reduce latency so that requests process 20% faster”).
   - Rebase to tidy commits before submitting (e.g., `git rebase -i main` to squash typos or reword messages), unless multiple contributors worked on the branch.
   - Keep PRs focused—one feature or fix. Split large changes into multiple PRs.

3. **Testing**:
   - Include unit tests for new functionality or bug fixes.

* Você pode checar todos os tipos de dados válidos do Pydantic aqui: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Tipos de dados do Pydantic</a>.

## Exemplo { #example }

Aqui está um exemplo de *operação de rota* com parâmetros utilizando-se de alguns dos tipos acima.

{* ../../docs_src/extra_data_types/tutorial001_an_py310.py hl[1,3,12:16] *}

    * En requests y responses, manejado igual que un `float`.
* Puedes revisar todos los tipos de datos válidos de Pydantic aquí: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Tipos de datos de Pydantic</a>.

## Ejemplo { #example }

Aquí tienes un ejemplo de una *path operation* con parámetros usando algunos de los tipos anteriores.

{* ../../docs_src/extra_data_types/tutorial001_an_py310.py hl[1,3,12:16] *}

import types
from enum import Enum
from typing import Any, Callable, Optional, TypeVar, Union

from pydantic import BaseModel

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = dict[Union[type[BaseModel], type[Enum]], str]
IncEx = Union[set[int], set[str], dict[int, Any], dict[str, Any]]

package loggertypes

// TargetType indicates type of the target e.g. console, http, kafka
type TargetType uint8

//go:generate stringer -type=TargetType -trimprefix=Target $GOFILE

// Constants for target types
const (
	_ TargetType = iota
	TargetConsole
	TargetHTTP
	TargetKafka
)

// TargetStats contains statistics for a target.
type TargetStats struct {

* `Decimal`:
    * Standard-Python-`Decimal`.
    * In Requests und Responses wird es wie ein `float` behandelt.
* Sie können alle gültigen Pydantic-Datentypen hier überprüfen: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic-Datentypen</a>.

## Beispiel { #example }

Hier ist ein Beispiel für eine *Pfadoperation* mit Parametern, die einige der oben genannten Typen verwenden.