# This file was auto-generated by Fern from our API Definition.

"""
jsonable_encoder converts a Python object to a JSON-friendly dict
(e.g. datetimes to strings, Pydantic models to dicts).

Taken from FastAPI, and made a bit simpler
https://github.com/tiangolo/fastapi/blob/master/fastapi/encoders.py
"""

import dataclasses
import datetime as dt
from collections import defaultdict
from enum import Enum
from pathlib import PurePath
from types import GeneratorType
from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union

from .datetime_utils import serialize_datetime
from .pydantic_utilities import pydantic_v1

SetIntStr = Set[Union[int, str]]
DictIntStrAny = Dict[Union[int, str], Any]


def generate_encoders_by_class_tuples(
    type_encoder_map: Dict[Any, Callable[[Any], Any]],
) -> Dict[Callable[[Any], Any], Tuple[Any, ...]]:
    encoders_by_class_tuples: Dict[Callable[[Any], Any], Tuple[Any, ...]] = defaultdict(
        tuple
    )
    for type_, encoder in type_encoder_map.items():
        encoders_by_class_tuples[encoder] += (type_,)
    return encoders_by_class_tuples


encoders_by_class_tuples = generate_encoders_by_class_tuples(
    pydantic_v1.json.ENCODERS_BY_TYPE
)


def jsonable_encoder(
    obj: Any, custom_encoder: Optional[Dict[Any, Callable[[Any], Any]]] = None
) -> Any:
    custom_encoder = custom_encoder or {}
    if custom_encoder:
        if type(obj) in custom_encoder:
            return custom_encoder[type(obj)](obj)
        else:
            for encoder_type, encoder_instance in custom_encoder.items():
                if isinstance(obj, encoder_type):
                    return encoder_instance(obj)
    if isinstance(obj, pydantic_v1.BaseModel):
        encoder = getattr(obj.__config__, "json_encoders", {})
        if custom_encoder:
            encoder.update(custom_encoder)
        obj_dict = obj.dict(by_alias=True)
        if "__root__" in obj_dict:
            obj_dict = obj_dict["__root__"]
        return jsonable_encoder(obj_dict, custom_encoder=encoder)
    if dataclasses.is_dataclass(obj):
        obj_dict = dataclasses.asdict(obj)
        return jsonable_encoder(obj_dict, custom_encoder=custom_encoder)
    if isinstance(obj, Enum):
        return obj.value
    if isinstance(obj, PurePath):
        return str(obj)
    if isinstance(obj, (str, int, float, type(None))):
        return obj
    if isinstance(obj, dt.datetime):
        return serialize_datetime(obj)
    if isinstance(obj, dt.date):
        return str(obj)
    if isinstance(obj, dict):
        encoded_dict = {}
        allowed_keys = set(obj.keys())
        for key, value in obj.items():
            if key in allowed_keys:
                encoded_key = jsonable_encoder(key, custom_encoder=custom_encoder)
                encoded_value = jsonable_encoder(value, custom_encoder=custom_encoder)
                encoded_dict[encoded_key] = encoded_value
        return encoded_dict
    if isinstance(obj, (list, set, frozenset, GeneratorType, tuple)):
        encoded_list = []
        for item in obj:
            encoded_list.append(jsonable_encoder(item, custom_encoder=custom_encoder))
        return encoded_list

    if type(obj) in pydantic_v1.json.ENCODERS_BY_TYPE:
        return pydantic_v1.json.ENCODERS_BY_TYPE[type(obj)](obj)
    for encoder, classes_tuple in encoders_by_class_tuples.items():
        if isinstance(obj, classes_tuple):
            return encoder(obj)

    try:
        data = dict(obj)
    except Exception as e:
        errors: List[Exception] = []
        errors.append(e)
        try:
            data = vars(obj)
        except Exception as e:
            errors.append(e)
            raise ValueError(errors) from e
    return jsonable_encoder(data, custom_encoder=custom_encoder)
