from __future__ import unicode_literals

import io
import json
import shutil
from abc import ABCMeta, abstractmethod, abstractproperty
from builtins import str, bytes
from pathlib import Path

from future.utils import with_metaclass

from snips_inference_agl.common.abc_utils import abstractclassmethod, classproperty
from snips_inference_agl.common.io_utils import temp_dir, unzip_archive
from snips_inference_agl.common.registrable import Registrable
from snips_inference_agl.common.utils import (
    json_string, check_random_state)
from snips_inference_agl.constants import (
    BUILTIN_ENTITY_PARSER, CUSTOM_ENTITY_PARSER, CUSTOM_ENTITY_PARSER_USAGE,
    RESOURCES, LANGUAGE, RANDOM_STATE)
from snips_inference_agl.entity_parser import (
    BuiltinEntityParser, CustomEntityParser, CustomEntityParserUsage)
from snips_inference_agl.exceptions import LoadingError
from snips_inference_agl.pipeline.configs import ProcessingUnitConfig
from snips_inference_agl.pipeline.configs.config import DefaultProcessingUnitConfig
from snips_inference_agl.resources import load_resources


class ProcessingUnit(with_metaclass(ABCMeta, Registrable)):
    """Abstraction of a NLU pipeline unit

    Pipeline processing units such as intent parsers, intent classifiers and
    slot fillers must implement this class.

     A :class:`ProcessingUnit` is associated with a *config_type*, which
    represents the :class:`.ProcessingUnitConfig` used to initialize it.
    """

    def __init__(self, config, **shared):
        if config is None:
            self.config = self.default_config()
        elif isinstance(config, ProcessingUnitConfig):
            self.config = config
        elif isinstance(config, dict):
            self.config = self.config_type.from_dict(config)
        else:
            raise ValueError("Unexpected config type: %s" % type(config))
        if self.config is not None:
            self.config.set_unit_name(self.unit_name)
        self.builtin_entity_parser = shared.get(BUILTIN_ENTITY_PARSER)
        self.custom_entity_parser = shared.get(CUSTOM_ENTITY_PARSER)
        self.resources = shared.get(RESOURCES)
        self.random_state = check_random_state(shared.get(RANDOM_STATE))

    @classproperty
    def config_type(cls):  # pylint:disable=no-self-argument
        return DefaultProcessingUnitConfig

    @classmethod
    def default_config(cls):
        config = cls.config_type()  # pylint:disable=no-value-for-parameter
        config.set_unit_name(cls.unit_name)
        return config

    @classproperty
    def unit_name(cls):  # pylint:disable=no-self-argument
        return ProcessingUnit.registered_name(cls)

    @classmethod
    def from_config(cls, unit_config, **shared):
        """Build a :class:`ProcessingUnit` from the provided config"""
        unit = cls.by_name(unit_config.unit_name)
        return unit(unit_config, **shared)

    @classmethod
    def load_from_path(cls, unit_path, unit_name=None, **shared):
        """Load a :class:`ProcessingUnit` from a persisted processing unit
        directory

        Args:
            unit_path (str or :class:`pathlib.Path`): path to the persisted
                processing unit
            unit_name (str, optional): Name of the processing unit to load.
                By default, the unit name is assumed to be stored in a
                "metadata.json" file located in the directory at unit_path.

        Raises:
            LoadingError: when unit_name is None and no metadata file is found
                in the processing unit directory
        """
        unit_path = Path(unit_path)
        if unit_name is None:
            metadata_path = unit_path / "metadata.json"
            if not metadata_path.exists():
                raise LoadingError(
                    "Missing metadata for processing unit at path %s"
                    % str(unit_path))
            with metadata_path.open(encoding="utf8") as f:
                metadata = json.load(f)
            unit_name = metadata["unit_name"]
        unit = cls.by_name(unit_name)
        return unit.from_path(unit_path, **shared)

    @classmethod
    def get_config(cls, unit_config):
        """Returns the :class:`.ProcessingUnitConfig` corresponding to
        *unit_config*"""
        if isinstance(unit_config, ProcessingUnitConfig):
            return unit_config
        elif isinstance(unit_config, dict):
            unit_name = unit_config["unit_name"]
            processing_unit_type = cls.by_name(unit_name)
            return processing_unit_type.config_type.from_dict(unit_config)
        elif isinstance(unit_config, (str, bytes)):
            unit_name = unit_config
            unit_config = {"unit_name": unit_name}
            processing_unit_type = cls.by_name(unit_name)
            return processing_unit_type.config_type.from_dict(unit_config)
        else:
            raise ValueError(
                "Expected `unit_config` to be an instance of "
                "ProcessingUnitConfig or dict or str but found: %s"
                % type(unit_config))

    @abstractproperty
    def fitted(self):
        """Whether or not the processing unit has already been trained"""
        pass

    def load_resources_if_needed(self, language):
        if self.resources is None or self.fitted:
            required_resources = None
            if self.config is not None:
                required_resources = self.config.get_required_resources()
            self.resources = load_resources(language, required_resources)

    def fit_builtin_entity_parser_if_needed(self, dataset):
        # We only fit a builtin entity parser when the unit has already been
        # fitted or if the parser is none.
        # In the other cases the parser is provided fitted by another unit.
        if self.builtin_entity_parser is None or self.fitted:
            self.builtin_entity_parser = BuiltinEntityParser.build(
                dataset=dataset)
        return self

    def fit_custom_entity_parser_if_needed(self, dataset):
        # We only fit a custom entity parser when the unit has already been
        # fitted or if the parser is none.
        # In the other cases the parser is provided fitted by another unit.
        required_resources = self.config.get_required_resources()
        if not required_resources or not required_resources.get(
                CUSTOM_ENTITY_PARSER_USAGE):
            # In these cases we need a custom entity parser only to do the
            # final slot resolution step, which must be done without stemming.
            parser_usage = CustomEntityParserUsage.WITHOUT_STEMS
        else:
            parser_usage = required_resources[CUSTOM_ENTITY_PARSER_USAGE]

        if self.custom_entity_parser is None or self.fitted:
            self.load_resources_if_needed(dataset[LANGUAGE])
            self.custom_entity_parser = CustomEntityParser.build(
                dataset, parser_usage, self.resources)
        return self

    def persist_metadata(self, path, **kwargs):
        metadata = {"unit_name": self.unit_name}
        metadata.update(kwargs)
        metadata_json = json_string(metadata)
        with (path / "metadata.json").open(mode="w", encoding="utf8") as f:
            f.write(metadata_json)

    # @abstractmethod
    def persist(self, path):
        pass

    @abstractclassmethod
    def from_path(cls, path, **shared):
        pass