operator – Functional interface to built-in operators¶
| Purpose: | Functional interface to built-in operators. |
|---|---|
| Available In: | 1.4 and later |
Functional programming using iterators occasionally requires creating small functions for simple expressions. Sometimes these can be expressed as lambda functions, but some operations do not need to be implemented with custom functions at all. The operator module defines functions that correspond to built-in operations for arithmetic and comparison, as well as sequence and dictionary operations.
Logical Operations¶
There are functions for determining the boolean equivalent for a value, negating that to create the opposite boolean value, and comparing objects to see if they are identical.
from operator import *
a = -1
b = 5
print 'a =', a
print 'b =', b
print
print 'not_(a) :', not_(a)
print 'truth(a) :', truth(a)
print 'is_(a, b) :', is_(a,b)
print 'is_not(a, b):', is_not(a,b)
not_() includes the trailing underscore because not is a Python keyword. truth() applies the same logic used when testing an expression in an if statement. is_() implements the same check used by the is keyword, and is_not() does the same test and returns the opposite answer.
$ python operator_boolean.py
a = -1
b = 5
not_(a) : False
truth(a) : True
is_(a, b) : False
is_not(a, b): True
Comparison Operators¶
All of the rich comparison operators are supported.
from operator import *
a = 1
b = 5.0
print
print 'a =', a
print 'b =', b
for func in (lt, le, eq, ne, ge, gt):
print '%s(a, b):' % func.__name__, func(a, b)
The functions are equivalent to the expression syntax using <, <=, ==, >=, and >.
$ python operator_comparisons.py
a = 1
b = 5.0
lt(a, b): True
le(a, b): True
eq(a, b): False
ne(a, b): True
ge(a, b): False
gt(a, b): False
Arithmetic Operators¶
The arithmetic operators for manipulating numerical values are also supported.
from operator import *
a = -1
b = 5.0
c = 2
d = 6
print 'a =', a
print 'b =', b
print 'c =', c
print 'd =', d
print '\nPositive/Negative:'
print 'abs(a):', abs(a)
print 'neg(a):', neg(a)
print 'neg(b):', neg(b)
print 'pos(a):', pos(a)
print 'pos(b):', pos(b)
print '\nArithmetic:'
print 'add(a, b) :', add(a, b)
print 'div(a, b) :', div(a, b)
print 'div(d, c) :', div(d, c)
print 'floordiv(a, b):', floordiv(a, b)
print 'floordiv(d, c):', floordiv(d, c)
print 'mod(a, b) :', mod(a, b)
print 'mul(a, b) :', mul(a, b)
print 'pow(c, d) :', pow(c, d)
print 'sub(b, a) :', sub(b, a)
print 'truediv(a, b) :', truediv(a, b)
print 'truediv(d, c) :', truediv(d, c)
print '\nBitwise:'
print 'and_(c, d) :', and_(c, d)
print 'invert(c) :', invert(c)
print 'lshift(c, d):', lshift(c, d)
print 'or_(c, d) :', or_(c, d)
print 'rshift(d, c):', rshift(d, c)
print 'xor(c, d) :', xor(c, d)
Note
There are two separate division operators: floordiv() (integer division as implemented in Python before version 3.0) and truediv() (floating point division).
$ python operator_math.py
a = -1
b = 5.0
c = 2
d = 6
Positive/Negative:
abs(a): 1
neg(a): 1
neg(b): -5.0
pos(a): -1
pos(b): 5.0
Arithmetic:
add(a, b) : 4.0
div(a, b) : -0.2
div(d, c) : 3
floordiv(a, b): -1.0
floordiv(d, c): 3
mod(a, b) : 4.0
mul(a, b) : -5.0
pow(c, d) : 64
sub(b, a) : 6.0
truediv(a, b) : -0.2
truediv(d, c) : 3.0
Bitwise:
and_(c, d) : 2
invert(c) : -3
lshift(c, d): 128
or_(c, d) : 6
rshift(d, c): 1
xor(c, d) : 4
Sequence Operators¶
The operators for working with sequences can be divided into four groups for building up sequences, searching for items, accessing contents, and removing items from sequences.
from operator import *
a = [ 1, 2, 3 ]
b = [ 'a', 'b', 'c' ]
print 'a =', a
print 'b =', b
print '\nConstructive:'
print ' concat(a, b):', concat(a, b)
print ' repeat(a, 3):', repeat(a, 3)
print '\nSearching:'
print ' contains(a, 1) :', contains(a, 1)
print ' contains(b, "d"):', contains(b, "d")
print ' countOf(a, 1) :', countOf(a, 1)
print ' countOf(b, "d") :', countOf(b, "d")
print ' indexOf(a, 5) :', indexOf(a, 1)
print '\nAccess Items:'
print ' getitem(b, 1) :', getitem(b, 1)
print ' getslice(a, 1, 3) :', getslice(a, 1, 3)
print ' setitem(b, 1, "d") :', setitem(b, 1, "d"), ', after b =', b
print ' setslice(a, 1, 3, [4, 5]):', setslice(a, 1, 3, [4, 5]), ', after a =', a
print '\nDestructive:'
print ' delitem(b, 1) :', delitem(b, 1), ', after b =', b
print ' delslice(a, 1, 3):', delslice(a, 1, 3), ', after a =', a
Some of these operations, such as setitem() and delitem(), modify the sequence in place and do not return a value.
$ python operator_sequences.py
a = [1, 2, 3]
b = ['a', 'b', 'c']
Constructive:
concat(a, b): [1, 2, 3, 'a', 'b', 'c']
repeat(a, 3): [1, 2, 3, 1, 2, 3, 1, 2, 3]
Searching:
contains(a, 1) : True
contains(b, "d"): False
countOf(a, 1) : 1
countOf(b, "d") : 0
indexOf(a, 5) : 0
Access Items:
getitem(b, 1) : b
getslice(a, 1, 3) : [2, 3]
setitem(b, 1, "d") : None , after b = ['a', 'd', 'c']
setslice(a, 1, 3, [4, 5]): None , after a = [1, 4, 5]
Destructive:
delitem(b, 1) : None , after b = ['a', 'c']
delslice(a, 1, 3): None , after a = [1]
In-place Operators¶
In addition to the standard operators, many types of objects support “in-place” modification through special operators such as +=. There are equivalent functions for in-place modifications, too:
from operator import *
a = -1
b = 5.0
c = [ 1, 2, 3 ]
d = [ 'a', 'b', 'c']
print 'a =', a
print 'b =', b
print 'c =', c
print 'd =', d
print
a = iadd(a, b)
print 'a = iadd(a, b) =>', a
print
c = iconcat(c, d)
print 'c = iconcat(c, d) =>', c
These examples only demonstrate a few of the functions. Refer to the stdlib documentation for complete details.
$ python operator_inplace.py
a = -1
b = 5.0
c = [1, 2, 3]
d = ['a', 'b', 'c']
a = iadd(a, b) => 4.0
c = iconcat(c, d) => [1, 2, 3, 'a', 'b', 'c']
Attribute and Item “Getters”¶
One of the most unusual features of the operator module is the concept of getters. These are callable objects constructed at runtime to retrieve attributes of objects or contents from sequences. Getters are especially useful when working with iterators or generator sequences, where they are intended to incur less overhead than a lambda or Python function.
from operator import *
class MyObj(object):
"""example class for attrgetter"""
def __init__(self, arg):
super(MyObj, self).__init__()
self.arg = arg
def __repr__(self):
return 'MyObj(%s)' % self.arg
l = [ MyObj(i) for i in xrange(5) ]
print l
g = attrgetter('arg')
vals = [ g(i) for i in l ]
print vals
Attribute getters work like lambda x, n='attrname': getattr(x, n):
$ python operator_attrgetter.py
[MyObj(0), MyObj(1), MyObj(2), MyObj(3), MyObj(4)]
[0, 1, 2, 3, 4]
While item getters work like lambda x, y=5: x[y]:
from operator import *
print 'Dictionaries:'
l = [ dict(val=i) for i in xrange(5) ]
print l
g = itemgetter('val')
vals = [ g(i) for i in l ]
print vals
print
print 'Tuples:'
l = [ (i, i*2) for i in xrange(5) ]
print l
g = itemgetter(1)
vals = [ g(i) for i in l ]
print vals
Item getters work with mappings as well as sequences.
$ python operator_itemgetter.py
Dictionaries:
[{'val': 0}, {'val': 1}, {'val': 2}, {'val': 3}, {'val': 4}]
[0, 1, 2, 3, 4]
Tuples:
[(0, 0), (1, 2), (2, 4), (3, 6), (4, 8)]
[0, 2, 4, 6, 8]
Combining Operators and Custom Classes¶
The functions in the operator module work via the standard Python interfaces for their operations, so they work with user-defined classes as well as the built-in types.
from operator import *
class MyObj(object):
"""Example for operator overloading"""
def __init__(self, val):
super(MyObj, self).__init__()
self.val = val
return
def __str__(self):
return 'MyObj(%s)' % self.val
def __lt__(self, other):
"""compare for less-than"""
print 'Testing %s < %s' % (self, other)
return self.val < other.val
def __add__(self, other):
"""add values"""
print 'Adding %s + %s' % (self, other)
return MyObj(self.val + other.val)
a = MyObj(1)
b = MyObj(2)
print 'Comparison:'
print lt(a, b)
print '\nArithmetic:'
print add(a, b)
Refer to the Python reference guide for a complete list of the special methods used by each operator.
$ python operator_classes.py
Comparison:
Testing MyObj(1) < MyObj(2)
True
Arithmetic:
Adding MyObj(1) + MyObj(2)
MyObj(3)
Type Checking¶
Besides the actual operators, there are functions for testing API compliance for mapping, number, and sequence types.
from operator import *
class NoType(object):
"""Supports none of the type APIs"""
class MultiType(object):
"""Supports multiple type APIs"""
def __len__(self):
return 0
def __getitem__(self, name):
return 'mapping'
def __int__(self):
return 0
o = NoType()
t = MultiType()
for func in (isMappingType, isNumberType, isSequenceType):
print '%s(o):' % func.__name__, func(o)
print '%s(t):' % func.__name__, func(t)
The tests are not perfect, since the interfaces are not strictly defined, but they do provide some idea of what is supported.
$ python operator_typechecking.py
isMappingType(o): False
isMappingType(t): True
isNumberType(o): False
isNumberType(t): True
isSequenceType(o): False
isSequenceType(t): True
abc includes abstract base classes that define the APIs for collection types.
