"""
numerictypes: Define the numeric type objects

This module is designed so "from numerictypes import \\*" is safe.
Exported symbols include:

  Dictionary with all registered number types (including aliases):
    typeDict

  Type objects (not all will be available, depends on platform):
      see variable sctypes for which ones you have

    Bit-width names

    int8 int16 int32 int64 int128
    uint8 uint16 uint32 uint64 uint128
    float16 float32 float64 float96 float128 float256
    complex32 complex64 complex128 complex192 complex256 complex512
    datetime64 timedelta64

    c-based names

    bool_

    object_

    void, str_, unicode_

    byte, ubyte,
    short, ushort
    intc, uintc,
    intp, uintp,
    int_, uint,
    longlong, ulonglong,

    single, csingle,
    float_, complex_,
    longfloat, clongfloat,

   As part of the type-hierarchy:    xx -- is bit-width

   generic
     +-> bool_                                  (kind=b)
     +-> number
     |   +-> integer
     |   |   +-> signedinteger     (intxx)      (kind=i)
     |   |   |     byte
     |   |   |     short
     |   |   |     intc
     |   |   |     intp            int0
     |   |   |     int_
     |   |   |     longlong
     |   |   \\-> unsignedinteger  (uintxx)     (kind=u)
     |   |         ubyte
     |   |         ushort
     |   |         uintc
     |   |         uintp           uint0
     |   |         uint_
     |   |         ulonglong
     |   +-> inexact
     |       +-> floating          (floatxx)    (kind=f)
     |       |     half
     |       |     single
     |       |     float_          (double)
     |       |     longfloat
     |       \\-> complexfloating  (complexxx)  (kind=c)
     |             csingle         (singlecomplex)
     |             complex_        (cfloat, cdouble)
     |             clongfloat      (longcomplex)
     +-> flexible
     |   +-> character
     |   |     str_     (string_, bytes_)       (kind=S)    [Python 2]
     |   |     unicode_                         (kind=U)    [Python 2]
     |   |
     |   |     bytes_   (string_)               (kind=S)    [Python 3]
     |   |     str_     (unicode_)              (kind=U)    [Python 3]
     |   |
     |   \\-> void                              (kind=V)
     \\-> object_ (not used much)               (kind=O)

"""
import types as _types
import numbers
import warnings

from numpy.core.multiarray import (
        typeinfo, ndarray, array, empty, dtype, datetime_data,
        datetime_as_string, busday_offset, busday_count, is_busday,
        busdaycalendar
        )
from numpy.core.overrides import set_module

# we add more at the bottom
__all__ = ['sctypeDict', 'sctypeNA', 'typeDict', 'typeNA', 'sctypes',
           'ScalarType', 'obj2sctype', 'cast', 'nbytes', 'sctype2char',
           'maximum_sctype', 'issctype', 'typecodes', 'find_common_type',
           'issubdtype', 'datetime_data', 'datetime_as_string',
           'busday_offset', 'busday_count', 'is_busday', 'busdaycalendar',
           ]

# we don't need all these imports, but we need to keep them for compatibility
# for users using np.core.numerictypes.UPPER_TABLE
from ._string_helpers import (
    english_lower, english_upper, english_capitalize, LOWER_TABLE, UPPER_TABLE
)

from ._type_aliases import (
    sctypeDict,
    sctypeNA,
    allTypes,
    bitname,
    sctypes,
    _concrete_types,
    _concrete_typeinfo,
    _bits_of,
)
from ._dtype import _kind_name

# we don't export these for import *, but we do want them accessible
# as numerictypes.bool, etc.
from builtins import bool, int, float, complex, object, str, bytes
from numpy.compat import long, unicode


# We use this later
generic = allTypes['generic']

genericTypeRank = ['bool', 'int8', 'uint8', 'int16', 'uint16',
                   'int32', 'uint32', 'int64', 'uint64', 'int128',
                   'uint128', 'float16',
                   'float32', 'float64', 'float80', 'float96', 'float128',
                   'float256',
                   'complex32', 'complex64', 'complex128', 'complex160',
                   'complex192', 'complex256', 'complex512', 'object']

@set_module('numpy')
def maximum_sctype(t):
    """
    Return the scalar type of highest precision of the same kind as the input.

    Parameters
    ----------
    t : dtype or dtype specifier
        The input data type. This can be a `dtype` object or an object that
        is convertible to a `dtype`.

    Returns
    -------
    out : dtype
        The highest precision data type of the same kind (`dtype.kind`) as `t`.

    See Also
    --------
    obj2sctype, mintypecode, sctype2char
    dtype

    Examples
    --------
    >>> np.maximum_sctype(int)
    <class 'numpy.int64'>
    >>> np.maximum_sctype(np.uint8)
    <class 'numpy.uint64'>
    >>> np.maximum_sctype(complex)
    <class 'numpy.complex256'> # may vary

    >>> np.maximum_sctype(str)
    <class 'numpy.str_'>

    >>> np.maximum_sctype('i2')
    <class 'numpy.int64'>
    >>> np.maximum_sctype('f4')
    <class 'numpy.float128'> # may vary

    """
    g = obj2sctype(t)
    if g is None:
        return t
    t = g
    base = _kind_name(dtype(t))
    if base in sctypes:
        return sctypes[base][-1]
    else:
        return t


@set_module('numpy')
def issctype(rep):
    """
    Determines whether the given object represents a scalar data-type.

    Parameters
    ----------
    rep : any
        If `rep` is an instance of a scalar dtype, True is returned. If not,
        False is returned.

    Returns
    -------
    out : bool
        Boolean result of check whether `rep` is a scalar dtype.

    See Also
    --------
    issubsctype, issubdtype, obj2sctype, sctype2char

    Examples
    --------
    >>> np.issctype(np.int32)
    True
    >>> np.issctype(list)
    False
    >>> np.issctype(1.1)
    False

    Strings are also a scalar type:

    >>> np.issctype(np.dtype('str'))
    True

    """
    if not isinstance(rep, (type, dtype)):
        return False
    try:
        res = obj2sctype(rep)
        if res and res != object_:
            return True
        return False
    except Exception:
        return False


@set_module('numpy')
def obj2sctype(rep, default=None):
    """
    Return the scalar dtype or NumPy equivalent of Python type of an object.

    Parameters
    ----------
    rep : any
        The object of which the type is returned.
    default : any, optional
        If given, this is returned for objects whose types can not be
        determined. If not given, None is returned for those objects.

    Returns
    -------
    dtype : dtype or Python type
        The data type of `rep`.

    See Also
    --------
    sctype2char, issctype, issubsctype, issubdtype, maximum_sctype

    Examples
    --------
    >>> np.obj2sctype(np.int32)
    <class 'numpy.int32'>
    >>> np.obj2sctype(np.array([1., 2.]))
    <class 'numpy.float64'>
    >>> np.obj2sctype(np.array([1.j]))
    <class 'numpy.complex128'>

    >>> np.obj2sctype(dict)
    <class 'numpy.object_'>
    >>> np.obj2sctype('string')

    >>> np.obj2sctype(1, default=list)
    <class 'list'>

    """
    # prevent abstract classes being upcast
    if isinstance(rep, type) and issubclass(rep, generic):
        return rep
    # extract dtype from arrays
    if isinstance(rep, ndarray):
        return rep.dtype.type
    # fall back on dtype to convert
    try:
        res = dtype(rep)
    except Exception:
        return default
    else:
        return res.type


@set_module('numpy')
def issubclass_(arg1, arg2):
    """
    Determine if a class is a subclass of a second class.

    `issubclass_` is equivalent to the Python built-in ``issubclass``,
    except that it returns False instead of raising a TypeError if one
    of the arguments is not a class.

    Parameters
    ----------
    arg1 : class
        Input class. True is returned if `arg1` is a subclass of `arg2`.
    arg2 : class or tuple of classes.
        Input class. If a tuple of classes, True is returned if `arg1` is a
        subclass of any of the tuple elements.

    Returns
    -------
    out : bool
        Whether `arg1` is a subclass of `arg2` or not.

    See Also
    --------
    issubsctype, issubdtype, issctype

    Examples
    --------
    >>> np.issubclass_(np.int32, int)
    False
    >>> np.issubclass_(np.int32, float)
    False
    >>> np.issubclass_(np.float64, float)
    True

    """
    try:
        return issubclass(arg1, arg2)
    except TypeError:
        return False


@set_module('numpy')
def issubsctype(arg1, arg2):
    """
    Determine if the first argument is a subclass of the second argument.

    Parameters
    ----------
    arg1, arg2 : dtype or dtype specifier
        Data-types.

    Returns
    -------
    out : bool
        The result.

    See Also
    --------
    issctype, issubdtype, obj2sctype