# Released under the MIT License. See LICENSE for details.
#
"""Core components of dataclassio."""

import dataclasses
import typing
import warnings
import datetime
from enum import Enum
from typing import TYPE_CHECKING, get_args, override, final

from typing import _AnnotatedAlias  # type: ignore

if TYPE_CHECKING:
    from typing import Any, Callable, Literal, ClassVar, Self

# Types which we can pass through as-is.
SIMPLE_TYPES = {int, bool, str, float, type(None)}

# Attr name for dict of extra attributes included on dataclass
# instances. Note that this is only added if extra attributes are
# present.
EXTRA_ATTRS_ATTR = '_DCIOEXATTRS'

# Attr name for a bool attr for flagging data as lossy, which means it
# may have been modified in some way during load and should generally
# not be written back out.
LOSSY_ATTR = '_DCIOLOSSY'


class Codec(Enum):
    """Specifies expected data format exported to or imported from."""

    #: Use only types that will translate cleanly to/from json - lists,
    #: dicts with str keys, bools, ints, floats, and None.
    JSON = 'json'

    #: Mostly like JSON but passes bytes and datetime objects through
    #: as-is instead of converting them to json-friendly types.
    FIRESTORE = 'firestore'

    #: Output-only codec for human-readable dicts. Uses Python attribute
    #: names as keys, enum ``.name`` as values, and ISO 8601 format for
    #: all datetime/date values. NOT suitable for round-trip parsing;
    #: decoding with this codec raises a ``ValueError``.
    HUMAN = 'human'


class IOExtendedData:
    """A class types can inherit from for extra functionality."""

    def will_output(self) -> None:
        """Called before data is sent to an outputter.

        Can be overridden to validate or filter data before
        sending it on its way. Fires on every dataclass instance in
        the object graph (not just the top level), in top-down order.
        Mutations made here are visible to the caller after output,
        since this runs on the caller's own instance.
        """

    @classmethod
    def will_input(cls, data: dict) -> None:
        """Called on data before a class instance is created from it.

        Can be overridden to migrate old data formats to new, etc.
        Fires on every dataclass-shaped dict in the input (not just
        the top level), in top-down order. Mutations to ``data`` are
        applied in place and are visible to the caller.
        """

    def did_input(self) -> None:
        """Called on a class instance after created from data.

        Can be useful to correct values from the db, etc. in the
        type-safe form. Fires on every dataclass instance in the
        object graph (not just the top level), in bottom-up order
        (children are fully constructed and have had their own
        ``did_input`` called before their parent's runs).
        """

    # pylint: disable=useless-return

    @classmethod
    def handle_input_error(cls, exc: Exception) -> Self | None:
        """Called when an error occurs during input decoding.

        This allows a type to optionally return substitute data
        to be used in place of the failed decode. If it returns
        None, the original exception is re-raised.

        It is generally a bad idea to apply catch-alls such as this,
        as it can lead to silent data loss. This should only be used
        in specific cases such as user settings where an occasional
        reset is harmless and is preferable to keeping all contained
        enums and other values backward compatible indefinitely.
        """
        del exc  # Unused.

        # By default we let things fail.
        return None

    # pylint: enable=useless-return


class IOMultiType[EnumT: Enum]:
    """A base class for types that can map to multiple dataclass types.

    This enables usage of high level base classes (for example a
    ``Message`` type) in annotations, with dataclassio automatically
    serializing & deserializing type-specific data for subclasses
    (``MessagePing``, ``MessageChat``, etc.)

    Standard usage involves a 'registry' class inheriting from this one
    and dataclass classes inheriting from that registry class.
    Dataclassio will then do the right thing when that registry class is
    used in type annotations.

    For an example multitype class (useful to use as a starting point
    for your own) see :class:`efro.dataclassio.templatemultitype`.
    """

    @classmethod
    def get_type(cls, type_id: EnumT) -> type[Self]:
        """Return a specific subclass given a type-id.

        Should be overridden by child classes. Generally, users of the
        class should call
        :meth:`~efro.dataclassio.IOMultiType.get_type_cached()` instead
        of this, as it is more efficient.
        """
        raise NotImplementedError()

    @final
    @classmethod
    def get_type_cached(cls, type_id: EnumT) -> type[Self]:
        """Version of :meth:`get_type()` with caching.

        Generally end-users of a multi-type class should use this
        instead of calling :meth:`get_type()` directly. It lazily caches
        looked up types so can be significantly more efficient with
        large multitypes and repeat lookups.
        """
        storage: dict[EnumT, type[Self]] | None = getattr(
            cls, '_iomt_tp_cache', None
        )
        if storage is None:
            storage = {}
            setattr(cls, '_iomt_tp_cache', storage)
        tp: type[Self] | None = storage.get(type_id)
        if tp is None:
            tp = storage[type_id] = cls.get_type(type_id)
        return tp

    @classmethod
    def get_type_id(cls) -> EnumT:
        """Return the type-id for this subclass."""
        raise NotImplementedError()

    @classmethod
    def get_type_id_type(cls) -> type[EnumT]:
        """Return the Enum type this class uses as its type-id."""
        out: type[EnumT] = cls.__orig_bases__[0].__args__[0]  # type: ignore
        assert issubclass(out, Enum)
        return out

    @classmethod
    def get_type_id_storage_name(cls) -> str:
        """Return the key used to store type id in serialized data.

        The default is a short obscure value so that it is unlikely to
        conflict with members of individual type attrs, but in some
        cases one might prefer to serialize it to something simpler like
        'type' by overriding this call. One just needs to make sure that
        no encompassed types serialize anything to that same name
        themself (dataclassio will error if they do).
        """
        return '_t'

    # NOTE: Currently (Jan 2025) mypy complains if overrides annotate
    # return type of 'Self | None'. Substituting their own explicit type
    # works though (see test_dataclassio).
    @classmethod
    def get_unknown_type_fallback(cls) -> Self | None:
        """Return a fallback object in cases of unrecognized types.

        This can allow newer data to remain readable in older
        environments. Use caution with this option, however, as it
        effectively modifies data.
        """
        return None


class IOAttrs:
    """Used to customize dataclassio behavior for particular fields.

    Example: specify that 'value2' will be stored as 'v2'::

        @ioprepped
        @dataclass
        class MyData:
            value1: int = 1
            value2: Annotated[int, IOAttrs('v2')] = 2

        >>> print(dataclass_to_dict(MyData()))

        # Output: {'value1': 1, 'v2': 2}

    Providing fixed storagenames for all fields can allow the freedom to
    rename fields later without worrying about breaking existing data.

    .. note::

       Any dataclass using ``IOAttrs`` in its field annotations should
       be decorated with ``@ioprepped`` (or ``@will_ioprep``). This
       ensures annotations are evaluated at runtime, which is required
       by systems such as ``FormDataclass`` that inspect type hints.
       It also satisfies the project's pylint plugin, which only
       preserves annotations on ``@ioprepped`` classes when deferred
       annotation evaluation (``from __future__ import annotations``)
       is active.
    """

    # A sentinel object to detect if a parameter is supplied or not. Use
    # a class to give it a better repr.
    class _MissingType:

        @override
        def __repr__(self) -> str:
            return '<MISSING>'

    #: :meta private:
    MISSING = _MissingType()

    #: If passed, is the name used when storing to json/etc.
    storagename: str | None = None

    #: Can be set to ``False`` to avoid writing values when equal to the
    #: default value. Note that this requires the dataclass field to
    #: define a ``default`` or ``default_factory`` or for its ``IOAttrs``
    #: to define a ``soft_default`` value.
    store_default: bool = True

    #: If True, requires datetime values to be exactly on day boundaries
    #: (see :meth:`efro.util.utc_today()`).
    whole_days: bool = False

    #: If ``True``, requires datetime values to lie exactly on hour
    #: boundaries (see :meth:`efro.util.utc_this_hour()`).
    whole_hours: bool = False

    #: If ``True``, requires ``datetime.datetime`` values to lie exactly on
    #: minute boundaries (see :meth:`efro.util.utc_this_minute()`).
    whole_minutes: bool = False

    #: If ``True``, requires ``datetime.datetime`` values to lie exactly on
    #: second boundaries (see :meth:`efro.util.utc_this_second()`).
    whole_seconds: bool = False

    #: If ``True``, values of type ``datetime.datetime`` (in json codec)
    #: and ``datetime.timedelta`` (in all codecs) will be stored as single
    #: float timestamp/seconds values instead of the default list of
    #: ints. This is more concise but introduces the possibility of
    #: restored values varying slightly from originals due to
    #: floating-point precision limitations.
    #:
    #: .. deprecated::
    #:     Use :attr:`time_format` instead.
    float_times: bool = False

    #: Controls the wire format used for ``datetime.datetime`` and
    #: ``datetime.timedelta`` values under the JSON codec. Has no effect
    #: under the Firestore codec, which always stores datetime objects
    #: natively. Does not apply to ``datetime.date`` fields, which are
    #: always serialized as ``YYYY-MM-DD`` strings.
    #:
    #: - ``'ints'`` (default): lossless list of integers
    #:   (``[year, month, day, hour, minute, second, microsecond]`` for
    #:   datetime; ``[days, seconds, microseconds]`` for timedelta).
    #: - ``'float'``: single float value (Unix timestamp for datetime;
    #:   total seconds for timedelta). Compact but subject to
    #:   floating-point precision loss.
    #: - ``'iso'``: RFC 3339 / ISO 8601 UTC string with ``Z`` suffix
    #:   (e.g. ``"2024-03-15T14:30:45.123456Z"``). JSON codec only;
    #:   not valid for ``timedelta`` fields.
    time_format: Literal['ints', 'float', 'iso'] = 'ints'

    #: If passed, injects a default value into dataclass instantiation
    #: when the field is not present in the input data. This allows
    #: dataclasses to add new non-optional fields while gracefully
    #: 'upgrading' old data. Note that when a soft-default is present it
    #: will take precedence over field defaults when determining whether
    #: to store a value for a field with ``store_default=False`` (since
    #: the soft_default value is what we'll get when reading that same
    #: data back in when the field is omitted).
    soft_default: Any = MISSING

    #: Is similar to 'default_factory' in dataclass fields; it should be
    #: used instead of 'soft_default' for mutable types such as lists to
    #: prevent a single default object from unintentionally changing over
    #: time.
    soft_default_factory: Callable[[], Any] | _MissingType = MISSING

    #: If provided, specifies an enum value that can be substituted in
    #: the case of unrecognized input values. This can allow newer data
    #: to remain loadable in older environments. Note that 'lossy' must
    #: be enabled in the top level load call for this to apply, since it
    #: can fundamentally modify data.
    enum_fallback: Enum | None = None

    #: If provided for a string, hints as to whether multi line values
    #: are allowed/expected. Can be referenced when creating UI for
    #: editing the value. Does not actually affect value input/output.
    multiline: bool | None = None

    #: If provided for a string, hints whether the value should be
    #: edited as distinct options in something like a popup menu instead
    #: of as a text field. Can be referenced when creating UI for
    #: editing the value. Does not actually affect value input/output.
    edit_as_options: bool | None = None

    #: If ``True`` for a string field, hints that the value is a literal
    #: identifier (e.g. a slug, filename, or code token) and should be
    #: edited without autocapitalization, autocorrect, or spellcheck.
    #: Does not actually affect value input/output.
    text_literal: bool | None = None

    #: If provided for a string field, supplies placeholder/hint text
    #: shown in the input when its value is empty. Can be referenced
    #: when creating UI for editing the value. Does not actually affect
    #: value input/output.
    placeholder: str | None = None

    #: If provided for a string field, caps the maximum length of the
    #: value at the form/UI layer. This is a *form-only* hint — it is
    #: NOT enforced by dataclassio at serialization (read or write)
    #: time. Form builders (e.g. ``FormDataclass``) read this to emit
    #: an HTML ``maxlength`` attribute and reject oversize submissions
    #: server-side. Existing in-DB data exceeding the cap continues to
    #: deserialize normally. Only meaningful for ``str`` fields; ignored
    #: for sequence/collection types.
    max_length: int | None = None

    def __init__(  # pylint: disable=too-many-branches
        self,
        storagename: str | None = storagename,
        *,
        store_default: bool = store_default,
        whole_days: bool = whole_days,
        whole_hours: bool = whole_hours,
        whole_minutes: bool = whole_minutes,
        whole_seconds: bool = whole_seconds,
        float_times: bool = float_times,
        time_format: Literal['ints', 'float', 'iso'] = 'ints',
        soft_default: Any = MISSING,
        soft_default_factory: Callable[[], Any] | _MissingType = MISSING,
        enum_fallback: Enum | None = None,
        multiline: bool | None = None,
        edit_as_options: bool | None = None,
        text_literal: bool | None = None,
        placeholder: str | None = None,
        max_length: int | None = None,
    ):

        # Only store values that differ from class defaults to keep
        # our instances nice and lean.
        cls = type(self)
        if storagename != cls.storagename:
            self.storagename = storagename
        if store_default != cls.store_default:
            self.store_default = store_default
        if whole_days != cls.whole_days:
            self.whole_days = whole_days
        if whole_hours != cls.whole_hours:
            self.whole_hours = whole_hours
        if whole_minutes != cls.whole_minutes:
            self.whole_minutes = whole_minutes
        if whole_seconds != cls.whole_seconds:
            self.whole_seconds = whole_seconds
        if float_times:
            warnings.warn(
                "IOAttrs 'float_times' is deprecated;"
                " use time_format='float' instead.",
                DeprecationWarning,
                stacklevel=2,
            )
            # Coerce to the new flag when caller did not also set time_format.
            time_format = 'float' if time_format == 'ints' else time_format
        if time_format != cls.time_format:
            self.time_format = time_format
        if soft_default is not cls.soft_default:
            # Do what dataclasses does with its default types and
            # tell the user to use factory for mutable ones.
            if isinstance(soft_default, (list, dict, set)):
                raise ValueError(
                    f'mutable {type(soft_default)} is not allowed'
                    f' for soft_default; use soft_default_factory.'
                )
            self.soft_default = soft_default
        if soft_default_factory is not cls.soft_default_factory:
            self.soft_default_factory = soft_default_factory
            if self.soft_default is not cls.soft_default:
                raise ValueError(
                    'Cannot set both soft_default and soft_default_factory'
                )
        if enum_fallback is not cls.enum_fallback:
            self.enum_fallback = enum_fallback
        if multiline is not cls.multiline:
            self.multiline = multiline
        if edit_as_options is not cls.multiline:
            self.edit_as_options = edit_as_options
        if text_literal is not cls.text_literal:
            self.text_literal = text_literal
        if placeholder is not cls.placeholder:
            self.placeholder = placeholder
        if max_length is not cls.max_length:
            self.max_length = max_length

    def validate_for_field(self, cls: type, field: dataclasses.Field) -> None:
        """Ensure the IOAttrs is ok to use with provided field."""

        # Turning off store_default requires the field to have either a
        # default or a default_factory or for us to have soft
        # equivalents.

        if not self.store_default:
            field_default_factory: Any = field.default_factory
            if (
                field_default_factory is dataclasses.MISSING
                and field.default is dataclasses.MISSING
                and self.soft_default is self.MISSING
                and self.soft_default_factory is self.MISSING
            ):
                raise TypeError(
                    f'Field \'{field.name}\' of {cls} has'
                    f' neither a default nor a default_factory'
                    f' and IOAttrs contains neither a soft_default'
                    f' nor a soft_default_factory;'
                    f' store_default=False cannot be set for it.'
                )

    def validate_datetime(
        self, value: datetime.datetime, fieldpath: str
    ) -> None:
        """Ensure a datetime value meets our value requirements."""
        if self.whole_days:
            if any(
                x != 0
                for x in (
                    value.hour,
                    value.minute,
                    value.second,
                    value.microsecond,
                )
            ):
                raise ValueError(
                    f'Value {value} at {fieldpath} is not a whole day.'
                )
        elif self.whole_hours:
            if any(
                x != 0 for x in (value.minute, value.second, value.microsecond)
            ):
                raise ValueError(
                    f'Value {value} at {fieldpath}' f' is not a whole hour.'
                )
        elif self.whole_minutes:
            if any(x != 0 for x in (value.second, value.microsecond)):
                raise ValueError(
                    f'Value {value} at {fieldpath}' f' is not a whole minute.'
                )
        elif self.whole_seconds:
            if any(x != 0 for x in (value.microsecond,)):
                raise ValueError(
                    f'Value {value} at {fieldpath}' f' is not a whole second.'
                )


class TypeNotPresentError(TypeError):
    """Used to communicate non-loadable multitype classes.

    This allows lossy loading of multitype objects in environments where
    their type enum is known but their actual class is not available. A
    IOMultiType's get_type() method should raise this in such cases.
    """


def _raise_type_error(
    fieldpath: str, valuetype: type, expected: tuple[type, ...]
) -> None:
    """Raise an error when a field value's type does not match expected."""
    assert isinstance(expected, tuple)
    assert all(isinstance(e, type) for e in expected)
    if len(expected) == 1:
        expected_str = expected[0].__name__
    else:
        expected_str = ' | '.join(t.__name__ for t in expected)
    raise TypeError(
        f'Invalid value type for "{fieldpath}";'
        f' expected "{expected_str}", got'
        f' "{valuetype.__name__}".'
    )


def _is_valid_for_codec(obj: Any, codec: Codec) -> bool:
    """Return whether a value consists solely of json-supported types.

    Note that this does not include things like tuples which are
    implicitly translated to lists by python's json module.
    """
    if obj is None:
        return True

    objtype = type(obj)
    if objtype in (int, float, str, bool):
        return True
    if objtype is dict:
        # JSON 'objects' supports only string dict keys, but all value
        # types.
        return all(
            isinstance(k, str) and _is_valid_for_codec(v, codec)
            for k, v in obj.items()
        )
    if objtype is list:
        return all(_is_valid_for_codec(elem, codec) for elem in obj)

    # A few things are valid in firestore but not json.
    if issubclass(objtype, datetime.datetime) or objtype is bytes:
        return codec is Codec.FIRESTORE

    return False


def _get_origin(anntype: Any) -> Any:
    """Given a type annotation, return its origin or itself if there is none.

    This differs from typing.get_origin in that it will never return
    None. This lets us use the same code path for handling typing.List
    that we do for handling list, which is good since they can be used
    interchangeably in annotations.
    """
    origin = typing.get_origin(anntype)
    return anntype if origin is None else origin


def parse_annotated(anntype: Any) -> tuple[Any, IOAttrs | None]:
    """Parse Annotated() constructs, returning annotated type & IOAttrs."""

    # If we get an Annotated[foo, bar, eep] we take foo as the actual
    # type, and we look for IOAttrs instances in bar/eep to affect our
    # behavior.
    ioattrs: IOAttrs | None = None
    if isinstance(anntype, _AnnotatedAlias):
        annargs = get_args(anntype)
        for annarg in annargs[1:]:
            if isinstance(annarg, IOAttrs):
                if ioattrs is not None:
                    raise RuntimeError(
                        'Multiple IOAttrs instances found for a'
                        ' single annotation; this is not supported.'
                    )
                ioattrs = annarg

            # I occasionally just throw a 'x' down when I mean
            # IOAttrs('x'); catch these mistakes.
            elif isinstance(annarg, (str, int, float, bool)):
                raise RuntimeError(
                    f'Raw {type(annarg)} found in Annotated[] entry:'
                    f' {anntype}; this is probably not what you intended.'
                )
        anntype = annargs[0]
    return anntype, ioattrs


# Note to self: this logic seems a bit redundant with _Inputter.run();
# should do a cleanup pass.
def _get_multitype_type(
    cls: type[IOMultiType], fieldpath: str, val: Any
) -> type[Any]:
    if not isinstance(val, dict):
        raise ValueError(
            f"Found a {type(val)} at '{fieldpath}'; expected a dict."
        )
    storename = cls.get_type_id_storage_name()
    id_val = val.get(storename)
    if id_val is None:
        raise ValueError(
            f"Expected a '{storename}'" f" value for object at '{fieldpath}'."
        )
    id_enum_type = cls.get_type_id_type()
    id_enum = id_enum_type(id_val)
    return cls.get_type_cached(id_enum)
