nptyping.functions._get_type.get_type_bool() - Code Metrics - Inspection of "Merge pull request #23 from ramonhagenaars/Release..." - ramonhagenaars/nptyping - Measure and Improve Code Quality continuously with Scrutinizer

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by Ramon

created 2020-06-20 21:00 UTC

nptyping.functions._get_type.get_type_bool() A

↳ Parent: nptyping.functions._get_type

Complexity

Conditions

Size

Total Lines	7
Code Lines	2

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	2
dl	0
loc	7
rs	10
c	0
b	0
f	0
cc	1
nop	1

from datetime import datetime, timedelta
from typing import Any, Type, Dict

import numpy
from typish import ClsFunction

from nptyping.functions._py_type import py_type
from nptyping.types._bool import Bool
from nptyping.types._datetime64 import Datetime64
from nptyping.types._ndarray import NDArray
from nptyping.types._nptype import NPType
from nptyping.types._number import (
    Int,
    Float,
    UInt,
    Number,
    DEFAULT_INT_BITS,
    DEFAULT_FLOAT_BITS
)
from nptyping.types._object import Object
from nptyping.types._timedelta64 import Timedelta64
from nptyping.types._unicode import Unicode


def get_type(obj: Any) -> Type['NPType']:
    """
    Return the nptyping type of the given obj. The given obj can be a numpy
    ndarray, a dtype or a Python type. If no corresponding nptyping type
    can be determined, a TypeError is raised.
    :param obj: the object for which an nptyping type is to be returned.
    :return: a subclass of NPType.
    """
    return ClsFunction(_delegates)(obj)


def _get_type_type(type_: type) -> Type['NPType']:
    # Return the nptyping type of a type.
    for super_type, delegate in _delegates:
        if issubclass(type_, super_type):
            break
    return delegate(type_)



def _get_type_dtype(dtype: numpy.dtype) -> Type['NPType']:

    # Return the nptyping type of a numpy dtype.
    np_type_per_py_type = {
        type: _get_type_type,
        bool: get_type_bool,
        int: get_type_int,
        float: get_type_float,
        str: get_type_str,
        datetime: get_type_datetime64,
        timedelta: get_type_timedelta64,
        object: lambda _: Object,
    }
    return np_type_per_py_type[(py_type(dtype))](dtype)


def _get_type_arrary(arr: numpy.ndarray) -> Type['NPType']:
    # Return the nptyping type of a numpy array.
    type_ = get_type(arr.dtype)
    return NDArray[arr.shape, type_]


def _get_type_of_number(

        cls: Type['Number'],
        obj: Any,
        bits_per_type: Dict[type, int]) -> Type[Number]:
    # Return the nptyping Number type of the given obj using cls and
    # bits_per_type.
    bits = (bits_per_type.get(obj)
            or bits_per_type.get(getattr(obj, 'type', None))
            or bits_per_type.get(type(obj)))

    if not bits:
        raise TypeError('Unsupported type {} for {}'
                        .format(type(obj).__name__, cls))

    return cls[bits]


# Library private.
def get_type_bool(_: Any) -> Type[Bool]:
    """
    Return the NPType that corresponds to obj.
    :param _: a bool compatible object.
    :return: a Bool type.
    """
    return Bool


# Library private.
def get_type_str(obj: Any) -> Type[Unicode]:

    """
    Return the NPType that corresponds to obj.
    :param obj: a string compatible object.
    :return: a Unicode type.
    """
    if isinstance(obj, numpy.dtype):
        return Unicode[obj.itemsize / 4]
    if obj == str:
        return Unicode
    if not isinstance(obj, str):
        raise TypeError('Unsupported type {}'.format(type(obj)))
    return Unicode[len(obj)]


# Library private.
def get_type_int(obj: Any) -> Type[Int]:
    """
    Return the NPType that corresponds to obj.
    :param obj: an int compatible object.
    :return: a Int type.
    """
    return _get_type_of_number(Int, obj, {
        numpy.int8: 8,
        numpy.int16: 16,
        numpy.int32: 32,
        numpy.int64: 64,
        int: DEFAULT_INT_BITS,
    })


# Library private.
def get_type_uint(obj: Any) -> Type[UInt]:
    """
    Return the NPType that corresponds to obj.
    :param obj: an uint compatible object.
    :return: an UInt type.
    """
    return _get_type_of_number(UInt, obj, {
        numpy.uint8: 8,
        numpy.uint16: 16,
        numpy.uint32: 32,
        numpy.uint64: 64,
        int: DEFAULT_INT_BITS,
    })


# Library private.
def get_type_float(obj: Any) -> Type[Float]:
    """
    Return the NPType that corresponds to obj.
    :param obj: a float compatible object.
    :return: a Float type.
    """
    return _get_type_of_number(Float, obj, {
        numpy.float16: 16,
        numpy.float32: 32,
        numpy.float64: 64,
        float: DEFAULT_FLOAT_BITS,
    })


# Library private.
def get_type_datetime64(_: Any) -> Type[Datetime64]:
    """
    Return the NPType that corresponds to obj.
    :param _: a datetime compatible object.
    :return: a Datetime64 type.
    """
    return Datetime64


# Library private.
def get_type_timedelta64(_: Any) -> Type[Timedelta64]:
    """
    Return the NPType that corresponds to obj.
    :param _: a timedelta compatible object.
    :return: a Timedelta64 type.
    """
    return Timedelta64


_delegates = [
    (NPType, lambda x: x),
    (type, _get_type_type),
    (bool, get_type_bool),
    (int, get_type_int),
    (float, get_type_float),
    (str, get_type_str),
    (datetime, get_type_datetime64),
    (timedelta, get_type_timedelta64),
    (numpy.datetime64, get_type_datetime64),
    (numpy.timedelta64, get_type_timedelta64),
    (numpy.signedinteger, get_type_int),
    (numpy.unsignedinteger, get_type_uint),
    (numpy.floating, get_type_float),
    (numpy.bool_, get_type_bool),
    (numpy.dtype, _get_type_dtype),
    (numpy.ndarray, _get_type_arrary),
    (object, lambda _: Object),
]


1		from datetime import datetime, timedelta
2		from typing import Any, Type, Dict
3
4		import numpy
5		from typish import ClsFunction
6
7		from nptyping.functions._py_type import py_type
8		from nptyping.types._bool import Bool
9		from nptyping.types._datetime64 import Datetime64
10		from nptyping.types._ndarray import NDArray
11		from nptyping.types._nptype import NPType
12		from nptyping.types._number import (
13		Int,
14		Float,
15		UInt,
16		Number,
17		DEFAULT_INT_BITS,
18		DEFAULT_FLOAT_BITS
19		)
20		from nptyping.types._object import Object
21		from nptyping.types._timedelta64 import Timedelta64
22		from nptyping.types._unicode import Unicode
23
24
25		def get_type(obj: Any) -> Type['NPType']:
26		"""
27		Return the nptyping type of the given obj. The given obj can be a numpy
28		ndarray, a dtype or a Python type. If no corresponding nptyping type
29		can be determined, a TypeError is raised.
30		:param obj: the object for which an nptyping type is to be returned.
31		:return: a subclass of NPType.
32		"""
33		return ClsFunction(_delegates)(obj)
34
35
36		def _get_type_type(type_: type) -> Type['NPType']:
37		# Return the nptyping type of a type.
38		for super_type, delegate in _delegates:
39		if issubclass(type_, super_type):
40		break
41		return delegate(type_)
		0 ignored issues – show introduced 2020-05-30 20:00 UTC by Report Bug Copy Issue Report The variable `delegate` does not seem to be defined in case the `for` loop on line `38` is not entered. Are you sure this can never be the case? Loading history...
42
43
44	View Code Duplication	def _get_type_dtype(dtype: numpy.dtype) -> Type['NPType']:
		0 ignored issues – show Duplication introduced 2020-06-20 20:30 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
45		# Return the nptyping type of a numpy dtype.
46		np_type_per_py_type = {
47		type: _get_type_type,
48		bool: get_type_bool,
49		int: get_type_int,
50		float: get_type_float,
51		str: get_type_str,
52		datetime: get_type_datetime64,
53		timedelta: get_type_timedelta64,
54		object: lambda _: Object,
55		}
56		return np_type_per_py_type[(py_type(dtype))](dtype)
57
58
59		def _get_type_arrary(arr: numpy.ndarray) -> Type['NPType']:
60		# Return the nptyping type of a numpy array.
61		type_ = get_type(arr.dtype)
62		return NDArray[arr.shape, type_]
63
64
65	View Code Duplication	def _get_type_of_number(
		0 ignored issues – show Duplication introduced 2020-05-30 20:00 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
66		cls: Type['Number'],
67		obj: Any,
68		bits_per_type: Dict[type, int]) -> Type[Number]:
69		# Return the nptyping Number type of the given obj using cls and
70		# bits_per_type.
71		bits = (bits_per_type.get(obj)
72		or bits_per_type.get(getattr(obj, 'type', None))
73		or bits_per_type.get(type(obj)))
74
75		if not bits:
76		raise TypeError('Unsupported type {} for {}'
77		.format(type(obj).__name__, cls))
78
79		return cls[bits]
80
81
82		# Library private.
83		def get_type_bool(_: Any) -> Type[Bool]:
84		"""
85		Return the NPType that corresponds to obj.
86		:param _: a bool compatible object.
87		:return: a Bool type.
88		"""
89		return Bool
90
91
92		# Library private.
93	View Code Duplication	def get_type_str(obj: Any) -> Type[Unicode]:
		0 ignored issues – show Duplication introduced 2020-05-30 20:00 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
94		"""
95		Return the NPType that corresponds to obj.
96		:param obj: a string compatible object.
97		:return: a Unicode type.
98		"""
99		if isinstance(obj, numpy.dtype):
100		return Unicode[obj.itemsize / 4]
101		if obj == str:
102		return Unicode
103		if not isinstance(obj, str):
104		raise TypeError('Unsupported type {}'.format(type(obj)))
105		return Unicode[len(obj)]
106
107
108		# Library private.
109		def get_type_int(obj: Any) -> Type[Int]:
110		"""
111		Return the NPType that corresponds to obj.
112		:param obj: an int compatible object.
113		:return: a Int type.
114		"""
115		return _get_type_of_number(Int, obj, {
116		numpy.int8: 8,
117		numpy.int16: 16,
118		numpy.int32: 32,
119		numpy.int64: 64,
120		int: DEFAULT_INT_BITS,
121		})
122
123
124		# Library private.
125		def get_type_uint(obj: Any) -> Type[UInt]:
126		"""
127		Return the NPType that corresponds to obj.
128		:param obj: an uint compatible object.
129		:return: an UInt type.
130		"""
131		return _get_type_of_number(UInt, obj, {
132		numpy.uint8: 8,
133		numpy.uint16: 16,
134		numpy.uint32: 32,
135		numpy.uint64: 64,
136		int: DEFAULT_INT_BITS,
137		})
138
139
140		# Library private.
141		def get_type_float(obj: Any) -> Type[Float]:
142		"""
143		Return the NPType that corresponds to obj.
144		:param obj: a float compatible object.
145		:return: a Float type.
146		"""
147		return _get_type_of_number(Float, obj, {
148		numpy.float16: 16,
149		numpy.float32: 32,
150		numpy.float64: 64,
151		float: DEFAULT_FLOAT_BITS,
152		})
153
154
155		# Library private.
156		def get_type_datetime64(_: Any) -> Type[Datetime64]:
157		"""
158		Return the NPType that corresponds to obj.
159		:param _: a datetime compatible object.
160		:return: a Datetime64 type.
161		"""
162		return Datetime64
163
164
165		# Library private.
166		def get_type_timedelta64(_: Any) -> Type[Timedelta64]:
167		"""
168		Return the NPType that corresponds to obj.
169		:param _: a timedelta compatible object.
170		:return: a Timedelta64 type.
171		"""
172		return Timedelta64
173
174
175		_delegates = [
176		(NPType, lambda x: x),
177		(type, _get_type_type),
178		(bool, get_type_bool),
179		(int, get_type_int),
180		(float, get_type_float),
181		(str, get_type_str),
182		(datetime, get_type_datetime64),
183		(timedelta, get_type_timedelta64),
184		(numpy.datetime64, get_type_datetime64),
185		(numpy.timedelta64, get_type_timedelta64),
186		(numpy.signedinteger, get_type_int),
187		(numpy.unsignedinteger, get_type_uint),
188		(numpy.floating, get_type_float),
189		(numpy.bool_, get_type_bool),
190		(numpy.dtype, _get_type_dtype),
191		(numpy.ndarray, _get_type_arrary),
192		(object, lambda _: Object),
193		]
194

ramonhagenaars / nptyping

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nptyping.functions._get_type.get_type_bool() A

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