import json
import re
from datetime import datetime, timedelta
from google.protobuf.field_mask_pb2 import FieldMask


class ObjectSerializer(object):

    def __init__(self, to_dict_value, from_dict_value):
        self.to_dict_value = to_dict_value
        self.from_dict_value = from_dict_value


class PredefinedSerializer(ObjectSerializer):

    def __init__(self):
        """Predefined objects such as int, float etc are serialized/deserialized directly."""
        ObjectSerializer.__init__(self, lambda cls, v, _: v, lambda cls, v: v)


# Adapted from https://stackoverflow.com/questions/1175208/elegant-python-function-to-convert-camelcase-to-snake-case
_pascal_to_upper_snake_case_regex = re.compile("((?<=[a-z0-9])[A-Z]|(?!^)[A-Z](?=[a-z]))")


def _pascal_case_to_upper_snake_case(string):
    return _pascal_to_upper_snake_case_regex.sub(r"_\1", string).upper()


def _convert(camel_input):
    words = re.findall(r"[A-Z]?[a-z]+|[A-Z]{2,}(?=[A-Z][a-z]|\d|\W|$)|\d+", camel_input)
    return "_".join(map(str.lower, words))


class EnumSerializer(ObjectSerializer):

    def __init__(self):
        """
        Enum objects are serialized using their ".name" field and deserialized by indexing the string in the Enum type.
        Example:
        class Foo(Enum):
           TEST = 1
        foo = Foo.TEST
        foo.name # => returns "TEST"
        Foo["TEST"] # => returns Foo.TEST enum value.
        """
        ObjectSerializer.__init__(
            self,
            lambda cls, v, _: EnumSerializer._to_str(cls, v),
            lambda cls, v: EnumSerializer._from_str(cls, v),
        )

    @staticmethod
    def _to_str(cls, v):
        # "v" corresponds to an enum instance: Example foo or Foo.Test above.
        # "cls" corresponds to the enum type Foo above.
        return v.name

    @staticmethod
    def _from_str(cls, v):
        # "v" corresponds to enum string: Example "TEST" above.
        # "cls" corresponds to the enum type Foo above.
        try:
            return cls[v]
        except KeyError:
            dct = vars(cls)
            n = v.lower()
            nn = _convert(v).lower()
            enum_prefix = _pascal_case_to_upper_snake_case(cls.__name__).lower()
            for key in dct.keys():
                k = key.lower()
                if k == n:
                    return dct[key]
                if k.startswith(enum_prefix) and k.endswith(n) or k.endswith(nn):
                    return dct[key]
            raise


class ListSerializer(ObjectSerializer):

    def __init__(self, item_serializer: ObjectSerializer):
        """
        Lists are serialized based on the type they contain. Since objects are generated from proto files, a list always
        contains objects of the same type, which is serialized/deserialized using "item_serializer".
        """
        ObjectSerializer.__init__(
            self,
            lambda cls, l, ignore_defaults: [item_serializer.to_dict_value(cls, v, ignore_defaults) for v in l],
            lambda cls, l: [item_serializer.from_dict_value(cls, v) for v in l],
        )


class MapSerializer(ObjectSerializer):

    def __init__(self, item_serializer: ObjectSerializer):
        """
        Maps are serialized based on type of their values. Since maps keys are always predefined types, we don't need a
        serializer for them.
        """
        ObjectSerializer.__init__(
            self,
            lambda cls, d, ignore_defaults: {
                k: item_serializer.to_dict_value(cls, v, ignore_defaults) for k, v in d.items()
            },
            lambda cls, d: {k: item_serializer.from_dict_value(cls, v) for k, v in d.items()},
        )


class DateTimeSerializer(ObjectSerializer):

    def __init__(self):
        """Date times are serialized/deserialized as a string in iso format"""
        ObjectSerializer.__init__(
            self,
            lambda cls, dt, _: DateTimeSerializer._to_str(dt),
            lambda _, v: DateTimeSerializer._from_str(v),
        )

    @staticmethod
    def _to_str(dt):
        return dt.isoformat(timespec="milliseconds") + "Z"

    @staticmethod
    def _from_str(v):
        v = v.rstrip("Z")
        fields = v.rsplit(".", maxsplit=1)
        if len(fields) == 1:
            return datetime.fromisoformat(v)
        (dt, nanos) = fields
        millis = nanos[:3]
        try:
            return datetime.fromisoformat(f"{dt}.{millis}")
        except ValueError:
            return datetime.fromisoformat(dt)  # Python 3.9, 3.10


class TimeDeltaSerializer(ObjectSerializer):
    # Scaling factors idea from https://github.com/protocolbuffers/protobuf/blob/master/csharp/src/Google.Protobuf/JsonParser.cs
    SUBSECOND_SCALING_FACTORS = [
        0,
        100_000_000,
        10_000_000,
        1_000_000,
        100_000,
        10_000,
        1_000,
        100,
        10,
        1,
    ]

    def __init__(self):
        """Time deltas are serialized/deserialized as a string in "<seconds>.<nanoseconds>s" format. Example: 151.500s"""
        ObjectSerializer.__init__(
            self,
            lambda cls, t, _: TimeDeltaSerializer._to_dict_value(t),
            lambda cls, v: TimeDeltaSerializer._from_dict_value(v),
        )

    @staticmethod
    def _to_dict_value(delta):
        seconds = delta.seconds
        nanos_str = TimeDeltaSerializer._nanos_to_str(delta.microseconds * 1000)
        if nanos_str is None:
            return "{}s".format(seconds)
        return "{}.{}s".format(seconds, nanos_str)

    @staticmethod
    def _nanos_to_str(nanos):
        if nanos == 0:
            return None
        if nanos < 0:
            nanos *= -1
        if nanos % 1000000 == 0:
            return "{}".format(nanos / 1000000)
        elif nanos % 1000 == 0:
            return "{}".format(nanos / 1000)
        else:
            return "{}".format(nanos)

    @staticmethod
    def _from_dict_value(value):
        (seconds, nanosRaw) = value.rstrip("s").split(".")
        nanos = int(nanosRaw) * TimeDeltaSerializer.SUBSECOND_SCALING_FACTORS[len(nanosRaw)]
        return timedelta(seconds=int(seconds), microseconds=int(int(nanos) / 1000))


class FieldMaskSerializer(ObjectSerializer):

    def __init__(self):
        """Field masks are serialized/deserialized as a string that contains a list of paths with a comma delimiter"""
        ObjectSerializer.__init__(
            self,
            lambda cls, m, _: m.ToJsonString(),
            lambda cls, v: FieldMaskSerializer._from_joined_paths(v),
        )

    @staticmethod
    def _from_joined_paths(joined_paths):
        mask = FieldMask()
        mask.FromJsonString(joined_paths)
        return mask


class KaggleObjectSerializer(ObjectSerializer):

    def __init__(self):
        """
        Kaggle objects (i.e., proto-generated types that inherit from KaggleObject) have custom "to_dict" and "from_dict"
        methods that serialize/deserialize them to/from dictionaries.
        """
        ObjectSerializer.__init__(
            self,
            # "v" is an instance of a KaggleObject. For example: "req = ListCompetitionsRequest()".
            # So "req.to_dict()" returns a dictionary with keys as json field names. Example:
            # '{"pageSize": 10, "page": 2}'
            lambda cls, v, ignore_defaults: cls.to_dict(v, ignore_defaults),
            # "cls" is the type of a KaggleObject. For example: ListCompetitionsRequest. All
            # generated Kaggle objects have "from_dict" class method that takes a dict to create a
            # new instance of the object. See "KaggleObject" class definition below.
            lambda cls, v: cls.from_dict(v),
        )


class FieldMetadata(object):

    def __init__(
        self,
        json_name,
        field_name,
        private_field_name,
        field_type,
        default_value,
        serializer,
        optional=False,
    ):
        self.json_name = json_name
        self.field_name = field_name
        self.private_field_name = private_field_name
        self.field_type = field_type
        self.default_value = default_value
        self.serializer = serializer
        self.optional = optional

    def get_as_dict_item(self, instance, ignore_defaults=True):
        value = getattr(instance, self.private_field_name)
        if ignore_defaults and value == self.default_value:
            return None
        if value is None:
            return None
        return self.serializer.to_dict_value(self.field_type, value, ignore_defaults)

    def set_from_dict(self, instance, json_dict):
        if self.json_name not in json_dict:
            return  # Ignore unknown fields
        value = json_dict[self.json_name]
        if value == self.default_value:
            return  # Ignore default values
        try:
            setattr(
                instance,
                self.private_field_name,
                self.serializer.from_dict_value(self.field_type, value),
            )
        except Exception as e:
            raise


class KaggleObject(object):

    def endpoint(self):
        raise "Error: endpoint must be defined by the request object"

    @staticmethod
    def endpoint_path():
        return None

    @staticmethod
    def body_fields():
        return None

    @classmethod
    def prepare_from(cls, http_response):
        return cls.from_json(http_response.text)

    @staticmethod
    def method():
        return "GET"

    def _freeze(self):
        self._is_frozen = True

    def __setattr__(self, key, value):
        if hasattr(self, "_is_frozen") and not hasattr(self, key):
            raise AttributeError(f"Unknown field for {self.__class__.__name__}: {key}")
        object.__setattr__(self, key, value)

    def to_dict(self, ignore_defaults=True):
        kv_pairs = [(field.json_name, field.get_as_dict_item(self, ignore_defaults)) for field in self._fields]
        return {k: v for (k, v) in kv_pairs if not ignore_defaults or v is not None}

    def to_field_map(self, ignore_defaults=True):
        kv_pairs = [(field.field_name, field.get_as_dict_item(self, ignore_defaults)) for field in self._fields]
        return {k: v for (k, v) in kv_pairs if not ignore_defaults or v is not None}

    @classmethod
    def from_dict(cls, json_dict):
        instance = cls()
        for field in cls._fields:
            field.set_from_dict(instance, json_dict)
        return instance

    @classmethod
    def from_json(cls, json_str):
        return cls.from_dict(json.loads(json_str))

    def to_json(self, ignore_defaults=True):
        return json.dumps(self.to_dict(ignore_defaults))

    def __str__(self):
        return self.to_json(ignore_defaults=False)

    def __repr__(self):
        return self.to_json(ignore_defaults=False)

    def __contains__(self, field_name):
        try:
            field = self._get_field(field_name)
        except ValueError:
            return False
        value = getattr(self, field.private_field_name)
        if field.optional:
            return value is not None
        else:
            return value != field.default_value

    def __delattr__(self, field_name):
        field = self._get_field(field_name)
        setattr(self, field.private_field_name, field.default_value)

    def _get_field(self, field_name):
        field = next((f for f in self._fields if f.field_name == field_name), None)
        if field is None:
            raise ValueError(f'Protocol message {self.__class__.__name__} has no "{field_name}" field.')
        return field