<!-- Thank you for your contribution! -->
<!-- Unless your change is trivial, please create an issue to discuss the change before creating a PR -->

## Change Summary

I noticed similar or identical logic in several places and extracted a couple of methods to reduce duplication.

The two commits are fairly independent and it may be easier to view their diffs separately to understand the changes. The first is probably a bit more compelling.

Note that the original code replaced by `clean_schema` wasn't always exactly the same, but the differences didn't really strike me as intentional, and either way it seemed good to draw attention to those differences and consider discussing them or adding comments to clarify.

## Related issue number

There's no issue because this isn't fixing/adding anything notable, it's just refactoring. I thought it made more sense to discuss the changes here rather than in a separate issue.

## Checklist

* [x] The pull request title is a good summary of the changes - it will be used in the changelog
* [x] Unit tests for the changes exist
* [x] Tests pass on CI
* [x] Documentation reflects the changes where applicable
* [x] My PR is ready to review, **please add a comment including the phrase "please review" to assign reviewers**


Selected Reviewer: @adriangb
Refactoring schema-related code. <!-- Thank you for your contribution! -->
<!-- Unless your change is trivial, please create an issue to discuss the change before creating a PR -->

## Change Summary

I noticed similar or identical logic in several places and extracted a couple of methods to reduce duplication.

The two commits are fairly independent and it may be easier to view their diffs separately to understand the changes. The first is probably a bit more compelling.

Note that the original code replaced by `clean_schema` wasn't always exactly the same, but the differences didn't really strike me as intentional, and either way it seemed good to draw attention to those differences and consider discussing them or adding comments to clarify.

## Related issue number

There's no issue because this isn't fixing/adding anything notable, it's just refactoring. I thought it made more sense to discuss the changes here rather than in a separate issue.

## Checklist

* [x] The pull request title is a good summary of the changes - it will be used in the changelog
* [x] Unit tests for the changes exist
* [x] Tests pass on CI
* [x] Documentation reflects the changes where applicable
* [x] My PR is ready to review, **please add a comment including the phrase "please review" to assign reviewers**


Selected Reviewer: @adriangb
import datetime
import warnings
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 TYPE_CHECKING, Any, Callable, Dict, Type, Union
from uuid import UUID

from typing_extensions import deprecated

from ..color import Color
from ..networks import NameEmail
from ..types import SecretBytes, SecretStr
from ..warnings import PydanticDeprecatedSince20

if not TYPE_CHECKING:
    # See PyCharm issues https://youtrack.jetbrains.com/issue/PY-21915
    # and https://youtrack.jetbrains.com/issue/PY-51428
    DeprecationWarning = PydanticDeprecatedSince20

__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
    """
    exponent = dec_value.as_tuple().exponent
    if isinstance(exponent, int) and 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,
}


@deprecated(
    'pydantic_encoder is deprecated, use pydantic_core.to_jsonable_python instead.', category=PydanticDeprecatedSince20
)
def pydantic_encoder(obj: Any) -> Any:
    from dataclasses import asdict, is_dataclass

    from ..main import BaseModel

    warnings.warn('pydantic_encoder is deprecated, use BaseModel.model_dump instead.', DeprecationWarning, stacklevel=2)
    if isinstance(obj, BaseModel):
        return obj.model_dump()
    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")


# TODO: Add a suggested migration path once there is a way to use custom encoders
@deprecated('custom_pydantic_encoder is deprecated.', category=PydanticDeprecatedSince20)
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
    warnings.warn(
        'custom_pydantic_encoder is deprecated, use BaseModel.model_dump instead.', DeprecationWarning, stacklevel=2
    )
    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)


@deprecated('timedelta_isoformat is deprecated.', category=PydanticDeprecatedSince20)
def timedelta_isoformat(td: datetime.timedelta) -> str:
    """ISO 8601 encoding for Python timedelta object."""
    warnings.warn('timedelta_isoformat is deprecated.', DeprecationWarning, stacklevel=2)
    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'

import datetime
import warnings
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 TYPE_CHECKING, Any, Callable, Dict, Type, Union
from uuid import UUID

from typing_extensions import deprecated

from ..color import Color
from ..networks import NameEmail
from ..types import SecretBytes, SecretStr
from ..warnings import PydanticDeprecatedSince20

if not TYPE_CHECKING:
    # See PyCharm issues https://youtrack.jetbrains.com/issue/PY-21915
    # and https://youtrack.jetbrains.com/issue/PY-51428
    DeprecationWarning = PydanticDeprecatedSince20

__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
    """
    exponent = dec_value.as_tuple().exponent
    if isinstance(exponent, int) and 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,
}


@deprecated(
    'pydantic_encoder is deprecated, use pydantic_core.to_jsonable_python instead.', category=PydanticDeprecatedSince20
)
def pydantic_encoder(obj: Any) -> Any:
    from dataclasses import asdict, is_dataclass

    from ..main import BaseModel

    warnings.warn('pydantic_encoder is deprecated, use BaseModel.model_dump instead.', DeprecationWarning, stacklevel=2)
    if isinstance(obj, BaseModel):
        return obj.model_dump()
    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")


# TODO: Add a suggested migration path once there is a way to use custom encoders
@deprecated('custom_pydantic_encoder is deprecated.', category=PydanticDeprecatedSince20)
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
    warnings.warn(
        'custom_pydantic_encoder is deprecated, use BaseModel.model_dump instead.', DeprecationWarning, stacklevel=2
    )
    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)


@deprecated('timedelta_isoformat is deprecated.', category=PydanticDeprecatedSince20)
def timedelta_isoformat(td: datetime.timedelta) -> str:
    """ISO 8601 encoding for Python timedelta object."""
    warnings.warn('timedelta_isoformat is deprecated.', DeprecationWarning, stacklevel=2)
    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'
