1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
|
:mod:`numbers` --- Numeric abstract base classes
================================================
.. module:: numbers
:synopsis: Numeric abstract base classes (Complex, Real, Integral, etc.).
**Source code:** :source:`Lib/numbers.py`
--------------
The :mod:`numbers` module (:pep:`3141`) defines a hierarchy of numeric
:term:`abstract base classes <abstract base class>` which progressively define
more operations. None of the types defined in this module can be instantiated.
.. class:: Number
The root of the numeric hierarchy. If you just want to check if an argument
*x* is a number, without caring what kind, use ``isinstance(x, Number)``.
The numeric tower
-----------------
.. class:: Complex
Subclasses of this type describe complex numbers and include the operations
that work on the built-in :class:`complex` type. These are: conversions to
:class:`complex` and :class:`bool`, :attr:`.real`, :attr:`.imag`, ``+``,
``-``, ``*``, ``/``, :func:`abs`, :meth:`conjugate`, ``==``, and ``!=``. All
except ``-`` and ``!=`` are abstract.
.. attribute:: real
Abstract. Retrieves the real component of this number.
.. attribute:: imag
Abstract. Retrieves the imaginary component of this number.
.. abstractmethod:: conjugate()
Abstract. Returns the complex conjugate. For example, ``(1+3j).conjugate()
== (1-3j)``.
.. class:: Real
To :class:`Complex`, :class:`Real` adds the operations that work on real
numbers.
In short, those are: a conversion to :class:`float`, :func:`math.trunc`,
:func:`round`, :func:`math.floor`, :func:`math.ceil`, :func:`divmod`, ``//``,
``%``, ``<``, ``<=``, ``>``, and ``>=``.
Real also provides defaults for :func:`complex`, :attr:`~Complex.real`,
:attr:`~Complex.imag`, and :meth:`~Complex.conjugate`.
.. class:: Rational
Subtypes :class:`Real` and adds
:attr:`~Rational.numerator` and :attr:`~Rational.denominator` properties, which
should be in lowest terms. With these, it provides a default for
:func:`float`.
.. attribute:: numerator
Abstract.
.. attribute:: denominator
Abstract.
.. class:: Integral
Subtypes :class:`Rational` and adds a conversion to :class:`int`. Provides
defaults for :func:`float`, :attr:`~Rational.numerator`, and
:attr:`~Rational.denominator`. Adds abstract methods for ``**`` and
bit-string operations: ``<<``, ``>>``, ``&``, ``^``, ``|``, ``~``.
Notes for type implementors
---------------------------
Implementors should be careful to make equal numbers equal and hash
them to the same values. This may be subtle if there are two different
extensions of the real numbers. For example, :class:`fractions.Fraction`
implements :func:`hash` as follows::
def __hash__(self):
if self.denominator == 1:
# Get integers right.
return hash(self.numerator)
# Expensive check, but definitely correct.
if self == float(self):
return hash(float(self))
else:
# Use tuple's hash to avoid a high collision rate on
# simple fractions.
return hash((self.numerator, self.denominator))
Adding More Numeric ABCs
~~~~~~~~~~~~~~~~~~~~~~~~
There are, of course, more possible ABCs for numbers, and this would
be a poor hierarchy if it precluded the possibility of adding
those. You can add ``MyFoo`` between :class:`Complex` and
:class:`Real` with::
class MyFoo(Complex): ...
MyFoo.register(Real)
.. _implementing-the-arithmetic-operations:
Implementing the arithmetic operations
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
We want to implement the arithmetic operations so that mixed-mode
operations either call an implementation whose author knew about the
types of both arguments, or convert both to the nearest built in type
and do the operation there. For subtypes of :class:`Integral`, this
means that :meth:`__add__` and :meth:`__radd__` should be defined as::
class MyIntegral(Integral):
def __add__(self, other):
if isinstance(other, MyIntegral):
return do_my_adding_stuff(self, other)
elif isinstance(other, OtherTypeIKnowAbout):
return do_my_other_adding_stuff(self, other)
else:
return NotImplemented
def __radd__(self, other):
if isinstance(other, MyIntegral):
return do_my_adding_stuff(other, self)
elif isinstance(other, OtherTypeIKnowAbout):
return do_my_other_adding_stuff(other, self)
elif isinstance(other, Integral):
return int(other) + int(self)
elif isinstance(other, Real):
return float(other) + float(self)
elif isinstance(other, Complex):
return complex(other) + complex(self)
else:
return NotImplemented
There are 5 different cases for a mixed-type operation on subclasses
of :class:`Complex`. I'll refer to all of the above code that doesn't
refer to ``MyIntegral`` and ``OtherTypeIKnowAbout`` as
"boilerplate". ``a`` will be an instance of ``A``, which is a subtype
of :class:`Complex` (``a : A <: Complex``), and ``b : B <:
Complex``. I'll consider ``a + b``:
1. If ``A`` defines an :meth:`__add__` which accepts ``b``, all is
well.
2. If ``A`` falls back to the boilerplate code, and it were to
return a value from :meth:`__add__`, we'd miss the possibility
that ``B`` defines a more intelligent :meth:`__radd__`, so the
boilerplate should return :const:`NotImplemented` from
:meth:`__add__`. (Or ``A`` may not implement :meth:`__add__` at
all.)
3. Then ``B``'s :meth:`__radd__` gets a chance. If it accepts
``a``, all is well.
4. If it falls back to the boilerplate, there are no more possible
methods to try, so this is where the default implementation
should live.
5. If ``B <: A``, Python tries ``B.__radd__`` before
``A.__add__``. This is ok, because it was implemented with
knowledge of ``A``, so it can handle those instances before
delegating to :class:`Complex`.
If ``A <: Complex`` and ``B <: Real`` without sharing any other knowledge,
then the appropriate shared operation is the one involving the built
in :class:`complex`, and both :meth:`__radd__` s land there, so ``a+b
== b+a``.
Because most of the operations on any given type will be very similar,
it can be useful to define a helper function which generates the
forward and reverse instances of any given operator. For example,
:class:`fractions.Fraction` uses::
def _operator_fallbacks(monomorphic_operator, fallback_operator):
def forward(a, b):
if isinstance(b, (int, Fraction)):
return monomorphic_operator(a, b)
elif isinstance(b, float):
return fallback_operator(float(a), b)
elif isinstance(b, complex):
return fallback_operator(complex(a), b)
else:
return NotImplemented
forward.__name__ = '__' + fallback_operator.__name__ + '__'
forward.__doc__ = monomorphic_operator.__doc__
def reverse(b, a):
if isinstance(a, Rational):
# Includes ints.
return monomorphic_operator(a, b)
elif isinstance(a, numbers.Real):
return fallback_operator(float(a), float(b))
elif isinstance(a, numbers.Complex):
return fallback_operator(complex(a), complex(b))
else:
return NotImplemented
reverse.__name__ = '__r' + fallback_operator.__name__ + '__'
reverse.__doc__ = monomorphic_operator.__doc__
return forward, reverse
def _add(a, b):
"""a + b"""
return Fraction(a.numerator * b.denominator +
b.numerator * a.denominator,
a.denominator * b.denominator)
__add__, __radd__ = _operator_fallbacks(_add, operator.add)
# ...
|
