simple cases about functional programming

import functools


def fac(n):
    return functools.reduce(lambda a,b:a*b, range(1,n+1))


fac(5)




120

another solution is using operator module

import operator
def fact(n):
    return functools.reduce(operator.mul, range(1,n+1))


fact(5)




120




metro_data = [
    ('Tokyo', 'JP', 36.933, (35.689722, 139.691667)),
    ('Delhi NCR', 'IN', 21.935, (28.613889, 77.208889)),
    ('Mexico City', 'MX', 20.142, (19.433333, -99.133333)),
    ('New York-Newark', 'US', 20.104, (40.808611, -74.020386)),
    ('Sao Paulo', 'BR', 19.649, (-23.547778, -46.635833))
    ]


for city in sorted(metro_data, key=operator.itemgetter(1)):   # 根据国籍排序 使用itemgetter函数
    print(city)

('Sao Paulo', 'BR', 19.649, (-23.547778, -46.635833))
('Delhi NCR', 'IN', 21.935, (28.613889, 77.208889))
('Tokyo', 'JP', 36.933, (35.689722, 139.691667))
('Mexico City', 'MX', 20.142, (19.433333, -99.133333))
('New York-Newark', 'US', 20.104, (40.808611, -74.020386))



country_city_name = operator.itemgetter(1,0)  # an function get values from index 1 and 0 , then collect them in tuple
for ele in map(country_city_name, metro_data):
    print(ele)

('JP', 'Tokyo')
('IN', 'Delhi NCR')
('MX', 'Mexico City')
('US', 'New York-Newark')
('BR', 'Sao Paulo')

由于itemgetter利用了[]操作符，所以它支持任何实现了__getitem__方法的类型，不局限于序列还包括字典。
类似的还有attrgetter，它也是个函数，以属性名称（字符串类型）作为参数，创建函数，最终作用于实例对象，返回tuple类型。
任何能被.(dot)访问的属性都能被attrgetter访问。

import collections
LatLong = collections.namedtuple('LatLong', 'lat long')
Metropolis = collections.namedtuple('Metropolis', 'name cc pop coord')


metro_areas = [Metropolis(name, cc, pop, LatLong(lat, long)) for name, cc, pop, (lat, long) in metro_data]


metro_areas[0]




Metropolis(name='Tokyo', cc='JP', pop=36.933, coord=LatLong(lat=35.689722, long=139.691667))




metro_areas[0].coord.lat




35.689722




name_lat = operator.attrgetter('name','coord.lat')   # a function get attribute named 'name', 'coord.lat'
for city in sorted(metro_areas, key=operator.attrgetter('coord.lat')): # sort use the attribute 'coord.lat'
    print(name_lat(city))

('Sao Paulo', -23.547778)
('Mexico City', 19.433333)
('Delhi NCR', 28.613889)
('Tokyo', 35.689722)
('New York-Newark', 40.808611)



[name for name in dir(operator) if not name.startswith('_')]




['abs',
 'add',
 'and_',
 'attrgetter',
 'concat',
 'contains',
 'countOf',
 'delitem',
 'eq',
 'floordiv',
 'ge',
 'getitem',
 'gt',
 'iadd',
 'iand',
 'iconcat',
 'ifloordiv',
 'ilshift',
 'imod',
 'imul',
 'index',
 'indexOf',
 'inv',
 'invert',
 'ior',
 'ipow',
 'irshift',
 'is_',
 'is_not',
 'isub',
 'itemgetter',
 'itruediv',
 'ixor',
 'le',
 'length_hint',
 'lshift',
 'lt',
 'methodcaller',
 'mod',
 'mul',
 'ne',
 'neg',
 'not_',
 'or_',
 'pos',
 'pow',
 'rshift',
 'setitem',
 'sub',
 'truediv',
 'truth',
 'xor']




s = 'The time has come'


upcase = operator.methodcaller('upper') # a function
print(upcase(s))

THE TIME HAS COME



replce_maker = operator.methodcaller('replace',' ','-')
print(replce_maker(s))

The-time-has-come



 triple = functools.partial(operator.mul, 3)


triple(7)




21




list(map(triple,range(1,11)))




[3, 6, 9, 12, 15, 18, 21, 24, 27, 30]




import unicodedata


nfc = functools.partial(unicodedata.normalize,'NFC')


s1 = 'café'


s2 = 'cafe\u0301'


s1




'café'




s2




'café'




s2 == s1




False




nfc(s1)




'café'




nfc(s2)




'café'




nfc(s1) == nfc(s2)




True