itemgetter和attrgetter能替代从序列中取出元素或读取对象属性的lambda表达式，会自动构建函数

itemgetter

1，根据元组某个字段给元组列表排序，下例中

itemgetter(1) == lambda field : field[1]

2,如果把多个参数传给itemgetter ,它构建的函数会返回提取的值构成元组

metro_data = [

("tykyo",'jp',36.944,(35.68944,139.69166)),

("delhi ncr",'in',21.935,(36.64944,138.79166)),

("mexico city",'mx',46.944,(33.68944,129.69166)),

("new york-newark",'us',20.944,(35.68944,139.69166)),

("sao paulo",'br',16.944,(25.68944,149.69166))

]

#1

from operator import itemgetter

for city in sorted(metro_data,key=itemgetter(1)):

print(city)

#2

cc_name=itemgetter(1,0)

for city in metro_data:

print(cc_name(city))

返回：

('sao paulo', 'br', 16.944, (25.68944, 149.69166))

('delhi ncr', 'in', 21.935, (36.64944, 138.79166))

('tykyo', 'jp', 36.944, (35.68944, 139.69166))

('mexico city', 'mx', 46.944, (33.68944, 129.69166))

('new york-newark', 'us', 20.944, (35.68944, 139.69166))

-------------------------------------------------------------------------------------

('jp', 'tykyo')

('in', 'delhi ncr')

('mx', 'mexico city')

('us', 'new york-newark')

('br', 'sao paulo')

attrgetter它创建的函数根据名称提取对象的属性

metro_data = [

("tykyo",'jp',36.944,(35.68944,139.69166)),

("delhi ncr",'in',21.935,(36.64944,138.79166)),

("mexico city",'mx',46.944,(33.68944,129.69166)),

("new york-newark",'us',20.944,(35.68944,139.69166)),

("sao paulo",'br',16.944,(25.68944,149.69166))

]

from operator import itemgetter

from collections import namedtuple

LatLong = namedtuple('LatLong','lat long')#定义LatLong

Metropolis = namedtuple('Metropolis','name cc pop coord')#定义Metropolis

#使用嵌套的元祖拆包提取(Lat,Long)

Metro_areas = [Metropolis(name,cc,pop,LatLong(Lat,Long)) for name,cc,pop,(Lat,Long) in metro_data]

print(Metro_areas)

print(Metro_areas[0])

print(Metro_areas[0].coord)

print(Metro_areas[0].coord.lat)

from operator import attrgetter

name_lat = attrgetter('name','coord.lat')

for city in sorted(Metro_areas,key=attrgetter('coord.lat')):

print(name_lat(city))

返回：

[Metropolis(name='tykyo', cc='jp', pop=36.944, coord=LatLong(lat=35.68944, long=139.69166)), Metropolis(name='delhi ncr', cc='in', pop=21.935, coord=LatLong(lat=36.64944, long=138.79166)), Metropolis(name='mexico city', cc='mx', pop=46.944, coord=LatLong(lat=33.68944, long=129.69166)), Metropolis(name='new york-newark', cc='us', pop=20.944, coord=LatLong(lat=35.68944, long=139.69166)), Metropolis(name='sao paulo', cc='br', pop=16.944, coord=LatLong(lat=25.68944, long=149.69166))]

Metropolis(name='tykyo', cc='jp', pop=36.944, coord=LatLong(lat=35.68944, long=139.69166))

LatLong(lat=35.68944, long=139.69166)

35.68944

('sao paulo', 25.68944)

('mexico city', 33.68944)

('tykyo', 35.68944)

('new york-newark', 35.68944)

('delhi ncr', 36.64944)

functools.partial

:冻结参数

：基于一个函数创建一个新的可调用对象，把原函数的某些参数固定，使用这个函数可以吧接受一个或多个参数的函数改编成需要回调的API，这样参数更少

from operator import mul

from functools import partial

triple = partial(mul,3)

print(triple(7))

l = list(map(triple,range(1,10)))

print(l)

返回：

21

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

def tag(name,*content,cls=None,**attrs):

if cls is not None:

attrs['class'] = cls

if attrs:

attrs_str = ''.join(' %s="%s" ' % (attr,value) for attr,value in sorted(attrs.items()))

else:

attrs_str=''

if content:

return '\n'.join('<%s %s >%s%s>' % (name,attrs_str,c,name) for c in content)

else:

return '<%s%s />' % (name,attrs_str)

from functools import partial

picture = partial(tag,'img',cls='pic-frame')

print(picture)

p = picture(src='sunlong.jpeg')

print(p)

print(picture.args)

print(picture.keywords)

返回：

functools.partial(, 'img', cls='pic-frame')

('img',)

{'cls': 'pic-frame'}