1"""

2 Module defining global singleton classes.

3

4 This module raises a RuntimeError if an attempt to reload it is made. In that

5 way the identities of the classes defined here are fixed and will remain so

6 even if numpy itself is reloaded. In particular, a function like the following

7 will still work correctly after numpy is reloaded::

8

9 def foo(arg=np._NoValue):

10 if arg is np._NoValue:

11 ...

12

13 That was not the case when the singleton classes were defined in the numpy

14``__init__.py`` file. See gh-7844 for a discussion of the reload problem that

15 motivated this module.

16

17"""

18 import enum

19

20__ALL__ = [

21 'ModuleDeprecationWarning', 'VisibleDeprecationWarning',

22 '_NoValue', '_CopyMode'

23 ]

24

25

26# Disallow reloading this module so as to preserve the identities of the

27# classes defined here.

28 if '_is_loaded' in globals():

29 raise RuntimeError('Reloading numpy._globals is not allowed')

30_is_loaded = True

31

32

33 class ModuleDeprecationWarning(DeprecationWarning):

34 """Module deprecation warning.

35

36 The nose tester turns ordinary Deprecation warnings into test failures.

37 That makes it hard to deprecate whole modules, because they get

38 imported by default. So this is a special Deprecation warning that the

39 nose tester will let pass without making tests fail.

40

41 """

42

43

44 ModuleDeprecationWarning.__module__ = 'numpy'

45

46

47 class VisibleDeprecationWarning(UserWarning):

48 """Visible deprecation warning.

49

50 By default, python will not show deprecation warnings, so this class

51 can be used when a very visible warning is helpful, for example because

52 the usage is most likely a user bug.

53

54 """

55

56

57 VisibleDeprecationWarning.__module__ = 'numpy'

58

59

60 class _NoValueType:

61 """Special keyword value.

62

63 The instance of this class may be used as the default value assigned to a

64 keyword if no other obvious default (e.g., `None`) is suitable,

65

66 Common reasons for using this keyword are:

67

68 - A new keyword is added to a function, and that function forwards its

69 inputs to another function or method which can be defined outside of

70 NumPy. For example, ``np.std(x)`` calls ``x.std``, so when a ``keepdims``

71 keyword was added that could only be forwarded if the user explicitly

72 specified ``keepdims``; downstream array libraries may not have added

73 the same keyword, so adding ``x.std(..., keepdims=keepdims)``

74 unconditionally could have broken previously working code.

75 - A keyword is being deprecated, and a deprecation warning must only be

76 emitted when the keyword is used.

77

78 """

79 __instance = None

80 def __new__(cls):

81 # ensure that only one instance exists

82 if not cls.__instance:

83 cls.__instance = super().__new__(cls)

84 return cls.__instance

85

86 def __repr__(self):

87 return "<no value>"

88

89

90_NoValue = _NoValueType()

91

92

93 class _CopyMode(enum.Enum):

94 """

95 An enumeration for the copy modes supported

96 by numpy.copy() and numpy.array(). The following three modes are supported,

97

98 - ALWAYS: This means that a deep copy of the input

99 array will always be taken.

100 - IF_NEEDED: This means that a deep copy of the input

101 array will be taken only if necessary.

102 - NEVER: This means that the deep copy will never be taken.

103 If a copy cannot be avoided then a `ValueError` will be

104 raised.

105

106 Note that the buffer-protocol could in theory do copies. NumPy currently

107 assumes an object exporting the buffer protocol will never do this.

108 """

109

110 ALWAYS = True

111 IF_NEEDED = False

112 NEVER = 2

113

114 def __bool__(self):

115 # For backwards compatibility

116 if self == _CopyMode.ALWAYS:

117 return True

118

119 if self == _CopyMode.IF_NEEDED:

120 return False

121

122 raise ValueError(f"{self} is neither True nor False.")

123

124

125_CopyMode.__module__ = 'numpy'