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📄 __init__.py (2,771 bytes)	2.71 KB	0644	✍️ ⬇️ 🗑️
📄 _hypothesis_plugin.py (14,844 bytes)	14.5 KB	0644	✍️ ⬇️ 🗑️
📄 annotated_types.py (3,124 bytes)	3.05 KB	0644	✍️ ⬇️ 🗑️
📄 class_validators.py (14,595 bytes)	14.25 KB	0644	✍️ ⬇️ 🗑️
📄 color.py (16,811 bytes)	16.42 KB	0644	✍️ ⬇️ 🗑️
📄 config.py (6,477 bytes)	6.33 KB	0644	✍️ ⬇️ 🗑️
📄 dataclasses.py (17,515 bytes)	17.1 KB	0644	✍️ ⬇️ 🗑️
📄 datetime_parse.py (7,714 bytes)	7.53 KB	0644	✍️ ⬇️ 🗑️
📄 decorator.py (10,263 bytes)	10.02 KB	0644	✍️ ⬇️ 🗑️
📄 env_settings.py (14,039 bytes)	13.71 KB	0644	✍️ ⬇️ 🗑️
📄 error_wrappers.py (5,142 bytes)	5.02 KB	0644	✍️ ⬇️ 🗑️
📄 errors.py (17,693 bytes)	17.28 KB	0644	✍️ ⬇️ 🗑️
📄 fields.py (50,488 bytes)	49.3 KB	0644	✍️ ⬇️ 🗑️
📄 generics.py (17,805 bytes)	17.39 KB	0644	✍️ ⬇️ 🗑️
📄 json.py (3,346 bytes)	3.27 KB	0644	✍️ ⬇️ 🗑️
📄 main.py (44,378 bytes)	43.34 KB	0644	✍️ ⬇️ 🗑️
📄 mypy.py (38,745 bytes)	37.84 KB	0644	✍️ ⬇️ 🗑️
📄 networks.py (22,059 bytes)	21.54 KB	0644	✍️ ⬇️ 🗑️
📄 parse.py (1,810 bytes)	1.77 KB	0644	✍️ ⬇️ 🗑️
📄 py.typed (0 bytes)	0 B	0644	✍️ ⬇️ 🗑️
📄 schema.py (47,615 bytes)	46.5 KB	0644	✍️ ⬇️ 🗑️
📄 tools.py (2,826 bytes)	2.76 KB	0644	✍️ ⬇️ 🗑️
📄 types.py (35,380 bytes)	34.55 KB	0644	✍️ ⬇️ 🗑️
📄 typing.py (18,996 bytes)	18.55 KB	0644	✍️ ⬇️ 🗑️
📄 utils.py (25,809 bytes)	25.2 KB	0644	✍️ ⬇️ 🗑️
📄 validators.py (21,887 bytes)	21.37 KB	0644	✍️ ⬇️ 🗑️
📄 version.py (1,039 bytes)	1.01 KB	0644	✍️ ⬇️ 🗑️

✍️ Editing: json.py

            File: /opt/cloudlinux/venv/lib/python3.11/site-packages/pydantic/v1/json.py

            Size: 3.27 KB | 
            Last Modified: 2024-04-17 20:36:23        

import datetime
from collections import deque
from decimal import Decimal
from enum import Enum
from ipaddress import IPv4Address, IPv4Interface, IPv4Network, IPv6Address, IPv6Interface, IPv6Network
from pathlib import Path
from re import Pattern
from types import GeneratorType
from typing import Any, Callable, Dict, Type, Union
from uuid import UUID

from .color import Color
from .networks import NameEmail
from .types import SecretBytes, SecretStr

__all__ = 'pydantic_encoder', 'custom_pydantic_encoder', 'timedelta_isoformat'

def isoformat(o: Union[datetime.date, datetime.time]) -> str:
    return o.isoformat()

def decimal_encoder(dec_value: Decimal) -> Union[int, float]:
    """
    Encodes a Decimal as int of there's no exponent, otherwise float

This is useful when we use ConstrainedDecimal to represent Numeric(x,0)
    where a integer (but not int typed) is used. Encoding this as a float
    results in failed round-tripping between encode and parse.
    Our Id type is a prime example of this.

>>> decimal_encoder(Decimal("1.0"))
    1.0

>>> decimal_encoder(Decimal("1"))
    1
    """
    if dec_value.as_tuple().exponent >= 0:
        return int(dec_value)
    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,
    IPv4Address: str,
    IPv4Interface: str,
    IPv4Network: str,
    IPv6Address: str,
    IPv6Interface: str,
    IPv6Network: str,
    NameEmail: str,
    Path: str,
    Pattern: lambda o: o.pattern,
    SecretBytes: str,
    SecretStr: str,
    set: list,
    UUID: str,
}

def pydantic_encoder(obj: Any) -> Any:
    from dataclasses import asdict, is_dataclass

from .main import BaseModel

if isinstance(obj, BaseModel):
        return obj.dict()
    elif is_dataclass(obj):
        return asdict(obj)

# Check the class type and its superclasses for a matching encoder
    for base in obj.__class__.__mro__[:-1]:
        try:
            encoder = ENCODERS_BY_TYPE[base]
        except KeyError:
            continue
        return encoder(obj)
    else:  # We have exited the for loop without finding a suitable encoder
        raise TypeError(f"Object of type '{obj.__class__.__name__}' is not JSON serializable")

def custom_pydantic_encoder(type_encoders: Dict[Any, Callable[[Type[Any]], Any]], obj: Any) -> Any:
    # Check the class type and its superclasses for a matching encoder
    for base in obj.__class__.__mro__[:-1]:
        try:
            encoder = type_encoders[base]
        except KeyError:
            continue

return encoder(obj)
    else:  # We have exited the for loop without finding a suitable encoder
        return pydantic_encoder(obj)

def timedelta_isoformat(td: datetime.timedelta) -> str:
    """
    ISO 8601 encoding for Python timedelta object.
    """
    minutes, seconds = divmod(td.seconds, 60)
    hours, minutes = divmod(minutes, 60)
    return f'{"-" if td.days < 0 else ""}P{abs(td.days)}DT{hours:d}H{minutes:d}M{seconds:d}.{td.microseconds:06d}S'

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✍️ Editing: json.py

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