import numpy as np
import pandas as pd
from functools import partial

from ..utils import derived_from


def maybe_wrap_pandas(obj, x):
    if isinstance(x, np.ndarray):
        if isinstance(obj, pd.Series):
            return pd.Series(x, index=obj.index, dtype=x.dtype)
        return pd.Index(x)
    return x


class Accessor(object):
    """
    Base class for pandas Accessor objects cat, dt, and str.

    Notes
    -----
    Subclasses should define ``_accessor_name``
    """

    _not_implemented = set()

    def __init__(self, series):
        from .core import Series

        if not isinstance(series, Series):
            raise ValueError("Accessor cannot be initialized")

        series_meta = series._meta
        if hasattr(series_meta, "to_series"):  # is index-like
            series_meta = series_meta.to_series()
        meta = getattr(series_meta, self._accessor_name)

        self._meta = meta
        self._series = series

    @staticmethod
    def _delegate_property(obj, accessor, attr):
        out = getattr(getattr(obj, accessor, obj), attr)
        return maybe_wrap_pandas(obj, out)

    @staticmethod
    def _delegate_method(obj, accessor, attr, args, kwargs):
        out = getattr(getattr(obj, accessor, obj), attr)(*args, **kwargs)
        return maybe_wrap_pandas(obj, out)

    def _property_map(self, attr):
        meta = self._delegate_property(self._series._meta, self._accessor_name, attr)
        token = "%s-%s" % (self._accessor_name, attr)
        return self._series.map_partitions(
            self._delegate_property, self._accessor_name, attr, token=token, meta=meta
        )

    def _function_map(self, attr, *args, **kwargs):
        if "meta" in kwargs:
            meta = kwargs.pop("meta")
        else:
            meta = self._delegate_method(
                self._series._meta_nonempty, self._accessor_name, attr, args, kwargs
            )
        token = "%s-%s" % (self._accessor_name, attr)
        return self._series.map_partitions(
            self._delegate_method,
            self._accessor_name,
            attr,
            args,
            kwargs,
            meta=meta,
            token=token,
        )

    @property
    def _delegates(self):
        return set(dir(self._meta)).difference(self._not_implemented)

    def __dir__(self):
        o = self._delegates
        o.update(self.__dict__)
        o.update(dir(type(self)))
        return list(o)

    def __getattr__(self, key):
        if key in self._delegates:
            if callable(getattr(self._meta, key)):
                return partial(self._function_map, key)
            else:
                return self._property_map(key)
        else:
            raise AttributeError(key)


class DatetimeAccessor(Accessor):
    """ Accessor object for datetimelike properties of the Series values.

    Examples
    --------

    >>> s.dt.microsecond  # doctest: +SKIP
    """

    _accessor_name = "dt"


class StringAccessor(Accessor):
    """ Accessor object for string properties of the Series values.

    Examples
    --------

    >>> s.str.lower()  # doctest: +SKIP
    """

    _accessor_name = "str"
    _not_implemented = {"get_dummies"}

    @derived_from(pd.core.strings.StringMethods)
    def split(self, pat=None, n=-1, expand=False):
        if expand:
            if n == -1:
                raise NotImplementedError(
                    "To use the expand parameter you must specify the number of "
                    "expected splits with the n= parameter. Usually n splits result in n+1 output columns."
                )
            else:
                delimiter = " " if pat is None else pat
                meta = type(self._series._meta)([delimiter.join(["a"] * (n + 1))])
                meta = meta.str.split(n=n, expand=expand, pat=pat)
        else:
            meta = (self._series.name, object)
        return self._function_map("split", pat=pat, n=n, expand=expand, meta=meta)

    @derived_from(pd.core.strings.StringMethods)
    def cat(self, others=None, sep=None, na_rep=None):
        from .core import Series, Index

        if others is None:
            raise NotImplementedError("x.str.cat() with `others == None`")

        valid_types = (Series, Index, pd.Series, pd.Index)
        if isinstance(others, valid_types):
            others = [others]
        elif not all(isinstance(a, valid_types) for a in others):
            raise TypeError("others must be Series/Index")

        return self._series.map_partitions(
            str_cat, *others, sep=sep, na_rep=na_rep, meta=self._series._meta
        )

    @derived_from(pd.core.strings.StringMethods)
    def extractall(self, pat, flags=0):
        # TODO: metadata inference here won't be necessary for pandas >= 0.23.0
        meta = self._series._meta.str.extractall(pat, flags=flags)
        return self._series.map_partitions(
            str_extractall, pat, flags, meta=meta, token="str-extractall"
        )

    def __getitem__(self, index):
        return self._series.map_partitions(str_get, index, meta=self._series._meta)


def str_extractall(series, pat, flags):
    return series.str.extractall(pat, flags=flags)


def str_get(series, index):
    """ Implements series.str[index] """
    return series.str[index]


def str_cat(self, *others, **kwargs):
    return self.str.cat(others=others, **kwargs)
