from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: int = Path(title="The ID of the item to get"),
    q: str | None = Query(default=None, alias="item-query"),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

}

// getHealSequence - Retrieve a heal sequence by path. The second
// argument returns if a heal sequence actually exists.
func (ahs *allHealState) getHealSequence(path string) (h *healSequence, exists bool) {
	ahs.RLock()
	defer ahs.RUnlock()
	h, exists = ahs.healSeqMap[path]
	return h, exists
}

func (ahs *allHealState) stopHealSequence(path string) ([]byte, APIError) {
	var hsp madmin.HealStopSuccess

from typing import Any


def get_body_model_name(openapi: dict[str, Any], path: str) -> str:
    body = openapi["paths"][path]["post"]["requestBody"]
    body_schema = body["content"]["application/json"]["schema"]

Accessing to contents inside an archive can be done using regular S3 API with a modified request path. You just need to append the path of the content inside the archive to the path of the archive itself.

e.g.:
To download `2021/taxes.csv` archived in `financial.zip` and stored under a bucket named `company-data`, you can issue a GET request using the following path 'company-data/financial.zip/2021/taxes.csv`

## Contents properties

Si tienes bastante conocimiento técnico (coroutines, hilos, bloqueo, etc.) y tienes curiosidad sobre cómo FastAPI maneja `async def` vs `def` normal, adelante.

///

### Funciones de *path operation* { #path-operation-functions }

Cuando declaras una *path operation function* con `def` normal en lugar de `async def`, se ejecuta en un threadpool externo que luego es esperado, en lugar de ser llamado directamente (ya que bloquearía el servidor).

import json
from pathlib import Path

file_path = Path("./openapi.json")
openapi_content = json.loads(file_path.read_text())

for path_data in openapi_content["paths"].values():
    for operation in path_data.values():
        tag = operation["tags"][0]
        operation_id = operation["operationId"]
        to_remove = f"{tag}-"
        new_operation_id = operation_id[len(to_remove) :]
        operation["operationId"] = new_operation_id

## Combina responses predefinidos y personalizados { #combine-predefined-responses-and-custom-ones }

Es posible que desees tener algunos responses predefinidos que se apliquen a muchas *path operations*, pero que quieras combinarlos con responses personalizados necesarios por cada *path operation*.

Para esos casos, puedes usar la técnica de Python de "desempaquetar" un `dict` con `**dict_to_unpack`:

```Python
old_dict = {
    "old key": "old value",

## Combine predefined responses and custom ones { #combine-predefined-responses-and-custom-ones }

You might want to have some predefined responses that apply to many *path operations*, but you want to combine them with custom responses needed by each *path operation*.

For those cases, you can use the Python technique of "unpacking" a `dict` with `**dict_to_unpack`:

```Python
old_dict = {
    "old key": "old value",

		},
		config.HelpKV{
			Key:         KafkaClientTLSCert,
			Description: "path to client certificate for mTLS auth",
			Optional:    true,
			Type:        "path",
			Sensitive:   true,
		},
		config.HelpKV{
			Key:         KafkaClientTLSKey,
			Description: "path to client key for mTLS auth",
			Optional:    true,
			Type:        "path",
			Sensitive:   true,
		},
		config.HelpKV{

import okio.FileSystem
import okio.Path.Companion.toPath

fun main(vararg args: String) {
  val data = loadIdnaMappingTableData()
  val file = generateMappingTableFile(data)
  file.writeTo(File(args[0]))
}

fun loadIdnaMappingTableData(): IdnaMappingTableData {
  val path = "/okhttp3/internal/idna/IdnaMappingTable.txt".toPath()
  val table =
    FileSystem.RESOURCES.read(path) {
      readPlainTextIdnaMappingTable()
    }