import operator
import warnings
from pandas.compat import reduce
from pandas.core.index import Index
import numpy as np
from pandas import algos
from pandas.core import common as com


def match(needles, haystack):
    haystack = Index(haystack)
    needles = Index(needles)
    return haystack.get_indexer(needles)


def cartesian_product(X):
    '''
    Numpy version of itertools.product or pandas.compat.product.
    Sometimes faster (for large inputs)...

    Examples
    --------
    >>> cartesian_product([list('ABC'), [1, 2]])
    [array(['A', 'A', 'B', 'B', 'C', 'C'], dtype='|S1'),
    array([1, 2, 1, 2, 1, 2])]

    '''

    lenX = np.fromiter((len(x) for x in X), dtype=int)
    cumprodX = np.cumproduct(lenX)

    a = np.roll(cumprodX, 1)
    a[0] = 1

    b = cumprodX[-1] / cumprodX

    return [np.tile(np.repeat(np.asarray(com._values_from_object(x)), b[i]),
                    np.product(a[i]))
               for i, x in enumerate(X)]


def _compose2(f, g):
    """Compose 2 callables"""
    return lambda *args, **kwargs: f(g(*args, **kwargs))


def compose(*funcs):
    """Compose 2 or more callables"""
    assert len(funcs) > 1, 'At least 2 callables must be passed to compose'
    return reduce(_compose2, funcs)

### FIXME: remove in 0.16
def value_range(df):
    """
    Return the minimum and maximum of a dataframe in a series object

    Parameters
    ----------
    df : DataFrame

    Returns
    -------
    (maximum, minimum) : Series

    """
    from pandas import Series
    warnings.warn("value_range is deprecated. Use .describe() instead", FutureWarning)

    return Series((min(df.min()), max(df.max())), ('Minimum', 'Maximum'))
