from datetime import datetime, timezone

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel


def test_pydanticv2():
    from pydantic import field_serializer

    class ModelWithDatetimeField(BaseModel):
        dt_field: datetime

        @field_serializer("dt_field")
        def serialize_datetime(self, dt_field: datetime):

import warnings
from collections import deque
from dataclasses import dataclass
from datetime import datetime, timezone
from decimal import Decimal
from enum import Enum
from math import isinf, isnan
from pathlib import PurePath, PurePosixPath, PureWindowsPath
from typing import Optional, TypedDict

import pytest
from fastapi._compat import Undefined
from fastapi.encoders import jsonable_encoder

    else:
        return float(dec_value)


ENCODERS_BY_TYPE: dict[type[Any], Callable[[Any], Any]] = {
    bytes: lambda o: o.decode(),
    Color: str,
    datetime.date: isoformat,
    datetime.datetime: isoformat,
    datetime.time: isoformat,
    datetime.timedelta: lambda td: td.total_seconds(),
    Decimal: decimal_encoder,
    Enum: lambda o: o.value,
    frozenset: list,
    deque: list,
    GeneratorType: list,

    assert mock_print.call_count == 2
    call_args = [str(arg.args[0]) for arg in mock_print.call_args_list]
    assert call_args == [
        "id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3]",
        "123",

                            "start_datetime": {
                                "title": "Start Datetime",
                                "type": "string",
                                "format": "date-time",
                            },
                            "end_datetime": {
                                "title": "End Datetime",
                                "type": "string",

Sie können den `jsonable_encoder` verwenden, um die empfangenen Daten in etwas zu konvertieren, das als JSON gespeichert werden kann (z. B. in einer NoSQL-Datenbank). Zum Beispiel, um ein `datetime` in einen `str` zu konvertieren.

{* ../../docs_src/body_updates/tutorial001_py310.py hl[28:33] *}

`PUT` wird verwendet, um Daten zu empfangen, die die existierenden Daten ersetzen sollen.

        },
    )
    assert response.status_code == 422
    assert response.json() == {
        "detail": [
            {
                "loc": ["body", "timestamp"],
                "msg": "Input should be a valid datetime or date, invalid character in year",
                "type": "datetime_from_date_parsing",
                "input": "not a date",
                "ctx": {"error": "invalid character in year"},
            }
        ]

    # TODO: remove after upgrading SQLAlchemy to a version that includes the following changes
    # https://github.com/sqlalchemy/sqlalchemy/commit/59521abcc0676e936b31a523bd968fc157fef0c2
    'ignore:datetime\.datetime\.utcfromtimestamp\(\) is deprecated and scheduled for removal in a future version\..*:DeprecationWarning:sqlalchemy',
    # Trio 24.1.0 raises a warning from attrs
    # Ref: https://github.com/python-trio/trio/pull/3054

    * Konvertieren von Python-Typen (`str`, `int`, `float`, `bool`, `list`, usw.).
    * `datetime`-Objekte.
    * `UUID`-Objekte.
    * Datenbankmodelle.
    * ... und viele mehr.
* Automatische interaktive API-Dokumentation, einschließlich zwei alternativer Benutzeroberflächen:
    * Swagger UI.
    * ReDoc.

    * Convert Python types (`str`, `int`, `float`, `bool`, `list`, etc).
    * `datetime` objects.
    * `UUID` objects.
    * Database models.
    * ...and many more.
* Automatic interactive API documentation, including 2 alternative user interfaces:
    * Swagger UI.
    * ReDoc.

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