* Die Inhalte sind **verschlüsselt**, auch wenn sie mit dem **HTTP-Protokoll** gesendet werden.

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["query", "query"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "42.5",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

import * as fs from 'fs'

async function modifyOpenAPIFile(filePath) {
  try {
    const data = await fs.promises.readFile(filePath)
    const openapiContent = JSON.parse(data)

    const paths = openapiContent.paths
    for (const pathKey of Object.keys(paths)) {
      const pathData = paths[pathKey]
      for (const method of Object.keys(pathData)) {
        const operation = pathData[method]
        if (operation.tags && operation.tags.length > 0) {

                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "a",
                },
                {
                    "type": "int_parsing",
                    "loc": ["query", "limit"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "b",
                },
            ]

    new_field.pre_validators = field.pre_validators  # type: ignore[attr-defined]
    new_field.post_validators = field.post_validators  # type: ignore[attr-defined]
    new_field.parse_json = field.parse_json  # type: ignore[attr-defined]
    new_field.shape = field.shape  # type: ignore[attr-defined]
    new_field.populate_validators()  # type: ignore[attr-defined]
    return new_field

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["body", "size"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "XL",
                }
            ],
            "body": {"title": "towel", "size": "XL"},
        }
    ) | IsDict(

Aber mit all den Vorzügen:

* Editor-Unterstützung (Codevervollständigung überall)
* Datenkonvertierung (auch bekannt als Parsen, Serialisierung)
* Datenvalidierung
* Schema-Dokumentation

```JSON
{
  "detail": [
    {
      "type": "int_parsing",
      "loc": [
        "path",
        "item_id"
      ],
      "msg": "Input should be a valid integer, unable to parse string as an integer",
      "input": "foo",
      "url": "https://errors.pydantic.dev/2.1/v/int_parsing"
    }
  ]
}
```

because the path parameter `item_id` had a value of `"foo"`, which is not an `int`.

        {
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

        {
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [