"""Helpers to help with encoding Home Assistant objects in JSON."""
from collections import deque
from collections.abc import Callable
import datetime
import json
import logging
from pathlib import Path
from typing import Any, Final

import orjson

from homeassistant.core import Event, State
from homeassistant.util.file import write_utf8_file, write_utf8_file_atomic
from homeassistant.util.json import (  # pylint: disable=unused-import # noqa: F401
    JSON_DECODE_EXCEPTIONS,
    JSON_ENCODE_EXCEPTIONS,
    SerializationError,
    format_unserializable_data,
    json_loads,
)

_LOGGER = logging.getLogger(__name__)


class JSONEncoder(json.JSONEncoder):
    """JSONEncoder that supports Home Assistant objects."""

    def default(self, o: Any) -> Any:
        """Convert Home Assistant objects.

        Hand other objects to the original method.
        """
        if isinstance(o, datetime.datetime):
            return o.isoformat()
        if isinstance(o, set):
            return list(o)
        if hasattr(o, "as_dict"):
            return o.as_dict()

        return json.JSONEncoder.default(self, o)


def json_encoder_default(obj: Any) -> Any:
    """Convert Home Assistant objects.

    Hand other objects to the original method.
    """
    if isinstance(obj, (set, tuple)):
        return list(obj)
    if isinstance(obj, float):
        return float(obj)
    if hasattr(obj, "as_dict"):
        return obj.as_dict()
    if isinstance(obj, Path):
        return obj.as_posix()
    raise TypeError


class ExtendedJSONEncoder(JSONEncoder):
    """JSONEncoder that supports Home Assistant objects and falls back to repr(o)."""

    def default(self, o: Any) -> Any:
        """Convert certain objects.

        Fall back to repr(o).
        """
        if isinstance(o, datetime.timedelta):
            return {"__type": str(type(o)), "total_seconds": o.total_seconds()}
        if isinstance(o, datetime.datetime):
            return o.isoformat()
        if isinstance(o, (datetime.date, datetime.time)):
            return {"__type": str(type(o)), "isoformat": o.isoformat()}
        try:
            return super().default(o)
        except TypeError:
            return {"__type": str(type(o)), "repr": repr(o)}


def json_bytes(data: Any) -> bytes:
    """Dump json bytes."""
    return orjson.dumps(
        data, option=orjson.OPT_NON_STR_KEYS, default=json_encoder_default
    )


def json_bytes_strip_null(data: Any) -> bytes:
    """Dump json bytes after terminating strings at the first NUL."""

    def process_dict(_dict: dict[Any, Any]) -> dict[Any, Any]:
        """Strip NUL from items in a dict."""
        return {key: strip_null(o) for key, o in _dict.items()}

    def process_list(_list: list[Any]) -> list[Any]:
        """Strip NUL from items in a list."""
        return [strip_null(o) for o in _list]

    def strip_null(obj: Any) -> Any:
        """Strip NUL from an object."""
        if isinstance(obj, str):
            return obj.split("\0", 1)[0]
        if isinstance(obj, dict):
            return process_dict(obj)
        if isinstance(obj, list):
            return process_list(obj)
        return obj

    # We expect null-characters to be very rare, hence try encoding first and look
    # for an escaped null-character in the output.
    result = json_bytes(data)
    if b"\\u0000" in result:
        # We work on the processed result so we don't need to worry about
        # Home Assistant extensions which allows encoding sets, tuples, etc.
        data_processed = orjson.loads(result)
        data_processed = strip_null(data_processed)
        result = json_bytes(data_processed)

    return result


def json_dumps(data: Any) -> str:
    """Dump json string.

    orjson supports serializing dataclasses natively which
    eliminates the need to implement as_dict in many places
    when the data is already in a dataclass. This works
    well as long as all the data in the dataclass can also
    be serialized.

    If it turns out to be a problem we can disable this
    with option |= orjson.OPT_PASSTHROUGH_DATACLASS and it
    will fallback to as_dict
    """
    return orjson.dumps(
        data, option=orjson.OPT_NON_STR_KEYS, default=json_encoder_default
    ).decode("utf-8")


def json_dumps_sorted(data: Any) -> str:
    """Dump json string with keys sorted."""
    return orjson.dumps(
        data,
        option=orjson.OPT_NON_STR_KEYS | orjson.OPT_SORT_KEYS,
        default=json_encoder_default,
    ).decode("utf-8")


JSON_DUMP: Final = json_dumps


def _orjson_default_encoder(data: Any) -> str:
    """JSON encoder that uses orjson with hass defaults."""
    return orjson.dumps(
        data,
        option=orjson.OPT_INDENT_2 | orjson.OPT_NON_STR_KEYS,
        default=json_encoder_default,
    ).decode("utf-8")


def save_json(
    filename: str,
    data: list | dict,
    private: bool = False,
    *,
    encoder: type[json.JSONEncoder] | None = None,
    atomic_writes: bool = False,
) -> None:
    """Save JSON data to a file."""
    dump: Callable[[Any], Any]
    try:
        # For backwards compatibility, if they pass in the
        # default json encoder we use _orjson_default_encoder
        # which is the orjson equivalent to the default encoder.
        if encoder and encoder is not JSONEncoder:
            # If they pass a custom encoder that is not the
            # default JSONEncoder, we use the slow path of json.dumps
            dump = json.dumps
            json_data = json.dumps(data, indent=2, cls=encoder)
        else:
            dump = _orjson_default_encoder
            json_data = _orjson_default_encoder(data)
    except TypeError as error:
        formatted_data = format_unserializable_data(
            find_paths_unserializable_data(data, dump=dump)
        )
        msg = f"Failed to serialize to JSON: {filename}. Bad data at {formatted_data}"
        _LOGGER.error(msg)
        raise SerializationError(msg) from error

    if atomic_writes:
        write_utf8_file_atomic(filename, json_data, private)
    else:
        write_utf8_file(filename, json_data, private)


def find_paths_unserializable_data(
    bad_data: Any, *, dump: Callable[[Any], str] = json.dumps
) -> dict[str, Any]:
    """Find the paths to unserializable data.

    This method is slow! Only use for error handling.
    """
    to_process = deque([(bad_data, "$")])
    invalid = {}

    while to_process:
        obj, obj_path = to_process.popleft()

        try:
            dump(obj)
            continue
        except (ValueError, TypeError):
            pass

        # We convert objects with as_dict to their dict values
        # so we can find bad data inside it
        if hasattr(obj, "as_dict"):
            desc = obj.__class__.__name__
            if isinstance(obj, State):
                desc += f": {obj.entity_id}"
            elif isinstance(obj, Event):
                desc += f": {obj.event_type}"

            obj_path += f"({desc})"
            obj = obj.as_dict()

        if isinstance(obj, dict):
            for key, value in obj.items():
                try:
                    # Is key valid?
                    dump({key: None})
                except TypeError:
                    invalid[f"{obj_path}<key: {key}>"] = key
                else:
                    # Process value
                    to_process.append((value, f"{obj_path}.{key}"))
        elif isinstance(obj, list):
            for idx, value in enumerate(obj):
                to_process.append((value, f"{obj_path}[{idx}]"))
        else:
            invalid[obj_path] = obj

    return invalid