每周一个 Python 模块 | operator

时间 2019-12-13

原文原文链接

operator 模块是 Python 中内置的操做符函数接口，它定义了算术，比较和与标准对象 API 相对应的其余操做的内置函数。python

operator 模块是用 C 实现的，因此执行速度比 Python 代码快。git

逻辑运算

from operator import *

a = -1
b = 5

print('a =', a)
print('b =', b)
print()

print('not_(a) :', not_(a))       # False
print('truth(a) :', truth(a))	  # True 
print('is_(a, b) :', is_(a, b))	  # False
print('is_not(a, b):', is_not(a, b))  # True
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not_()包括尾随下划线，由于not 是 Python 的关键字。 truth()做为判断表达式用在if语句中，或者将一个表达式转换成bool。 is_()和is关键字的用法同样，is_not()用法相同，只不过返回相反的答案。github

比较运算符

from operator import *

a = 1
b = 5.0

print('a =', a)
print('b =', b)
for func in (lt, le, eq, ne, ge, gt):
    print('{}(a, b): {}'.format(func.__name__, func(a, b)))
    
# 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 
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功能是等同于使用表达式语法<， <=，==，>=，和>。app

算术运算符

from operator import *

a = -1
b = 5.0
c = 2
d = 6

print('\nPositive/Negative:')
print('abs(a):', abs(a))	# abs(a): 1
print('neg(a):', neg(a))	# neg(a): 1
print('neg(b):', neg(b))	# neg(b): -5.0
print('pos(a):', pos(a))	# pos(a): -1
print('pos(b):', pos(b))	# pos(b): 5.0

print('\nArithmetic:')
print('add(a, b) :', add(a, b))			# add(a, b) : 4.0
print('floordiv(a, b):', floordiv(a, b))	# floordiv(a, b): -1.0
print('floordiv(d, c):', floordiv(d, c))	# floordiv(d, c): 3
print('mod(a, b) :', mod(a, b))			# mod(a, b) : 4.0
print('mul(a, b) :', mul(a, b))			# mul(a, b) : -5.0
print('pow(c, d) :', pow(c, d))			# pow(c, d) : 64
print('sub(b, a) :', sub(b, a))			# sub(b, a) : 6.0
print('truediv(a, b) :', truediv(a, b))		# truediv(a, b) : -0.2
print('truediv(d, c) :', truediv(d, c))		# truediv(d, c) : 3.0

print('\nBitwise:')
print('and_(c, d) :', and_(c, d))		# and_(c, d) : 2 
print('invert(c) :', invert(c))		# invert(c) : -3
print('lshift(c, d):', lshift(c, d))	# lshift(c, d): 128
print('or_(c, d) :', or_(c, d))		# or_(c, d) : 6
print('rshift(d, c):', rshift(d, c))	# rshift(d, c): 1
print('xor(c, d) :', xor(c, d))		# xor(c, d) : 4
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序列运算符

使用序列的运算符能够分为四组：构建序列，搜索项目，访问内容以及从序列中删除项目。less

from operator import *

a = [1, 2, 3]
b = ['a', 'b', 'c']

print('\nConstructive:')
print(' concat(a, b):', concat(a, b))		# concat(a, b): [1, 2, 3, 'a', 'b', 'c']

print('\nSearching:')
print(' contains(a, 1) :', contains(a, 1))	# contains(a, 1) : True
print(' contains(b, "d"):', contains(b, "d"))	# contains(b, "d"): False
print(' countOf(a, 1) :', countOf(a, 1))		# countOf(a, 1) : 1
print(' countOf(b, "d") :', countOf(b, "d"))	# countOf(b, "d") : 0
print(' indexOf(a, 5) :', indexOf(a, 1))		# indexOf(a, 5) : 0

print('\nAccess Items:')
print(getitem(b, 1))	# b
print(getitem(b, slice(1, 3))) # ['b', 'c']
print(setitem(b, 1, "d")	# None
print(b)	# ['a', 'd', 'c']
print(setitem(a, slice(1, 3), [4, 5])）	# None
print(a)	# [1, 4, 5]

print('\nDestructive:')
print(delitem(b, 1)）	# None
print(b)	# ['a', 'c']
print(delitem(a, slice(1, 3))	# None
print(a)	# [1]
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其中一些操做（例如setitem()和delitem()）修改了序列而且不返回值。函数

原地操做符

除了标准运算符以外，许多类型的对象还支持经过特殊运算符进行“原地”修改，+=一样具备就地修改的功能：测试

from operator import *

a = -1
b = 5.0
c = [1, 2, 3]
d = ['a', 'b', 'c']

a = iadd(a, b)
print('a = iadd(a, b) =>', a)	# a = iadd(a, b) => 4.0

c = iconcat(c, d)
print('c = iconcat(c, d) =>', c)	# c = iconcat(c, d) => [1, 2, 3, 'a', 'b', 'c']
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属性和元素的获取方法

operator 模块最特别的特性之一就是获取方法的概念，获取方法是运行时构造的一些可回调对象，用来获取对象的属性或序列的内容，获取方法在处理迭代器或生成器序列的时候特别有用，它们引入的开销会大大下降 lambda 或 Python 函数的开销。spa

from operator import *


class MyObj:
    """example class for attrgetter"""

    def __init__(self, arg):
        super().__init__()
        self.arg = arg

    def __repr__(self):
        return 'MyObj({})'.format(self.arg)


l = [MyObj(i) for i in range(5)]
print(l)	# [MyObj(0), MyObj(1), MyObj(2), MyObj(3), MyObj(4)]

# Extract the 'arg' value from each object
g = attrgetter('arg')
vals = [g(i) for i in l]
print('arg values:', vals)	# arg values: [0, 1, 2, 3, 4]

# Sort using arg
l.reverse()
print(l)	# [MyObj(4), MyObj(3), MyObj(2), MyObj(1), MyObj(0)]
print(sorted(l, key=g))	# [MyObj(0), MyObj(1), MyObj(2), MyObj(3), MyObj(4)]
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结合操做符和定制类

operator模块中的函数经过标准 Python 接口进行操做，所以它能够使用用户定义的类以及内置类型。.net

from operator import *


class MyObj:
    """Example for operator overloading"""

    def __init__(self, val):
        super(MyObj, self).__init__()
        self.val = val

    def __str__(self):
        return 'MyObj({})'.format(self.val)

    def __lt__(self, other):
        """compare for less-than"""
        print('Testing {} < {}'.format(self, other))
        return self.val < other.val

    def __add__(self, other):
        """add values"""
        print('Adding {} + {}'.format(self, other))
        return MyObj(self.val + other.val)


a = MyObj(1)
b = MyObj(2)

print('Comparison:')
print(lt(a, b))		
# Comparison:
# Testing MyObj(1) < MyObj(2)
# True

print('\nArithmetic:')
print(add(a, b))	
# Arithmetic:
# Adding MyObj(1) + MyObj(2)
# MyObj(3)
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类型检查

operator 模块还包含一些函数用来测试映射、数字和序列类型的 API 兼容性。

from operator import *

class NoType(object):
    pass

class MultiType(object):
    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)

# isMappingType(o): False
# isMappingType(t): True
# isNumberType(o): False
# isNumberType(t): True
# isSequenceType(o): False
# isSequenceType(t): True 
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获取对象方法

使用 methodcaller 能够获取对象的方法。

from operator import methodcaller

class Student(object):
    def __init__(self, name):
        self.name = name

    def getName(self):
        return self.name

stu = Student("Jim")
func = methodcaller('getName')
print func(stu)   # 输出Jim
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还能够给方法传递参数：

f = methodcaller('name', 'foo', bar=1)
f(b)    # return b.name('foo', bar=1)
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methodcaller方法等价于下面这个函数：

def methodcaller(name, *args, **kwargs):
      def caller(obj):
            return getattr(obj, name)(*args, **kwargs)
      return caller
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