http://wiki.python.org/moin/HowTo/Sorting?highlight=%28howto%29#The_Old_Way_Using_the_cmp_Parameter
一个列表存储了由数字组成的 字符串,比如 '21'
|
from operator import itemgetter,attrgetter
s = [('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10),]
print itemgetter(0,2)
print sorted(s,key=itemgetter(2))
from operator import itemgetter,attrgetter
d = {'data1':3,'data2':1,'data3':2,'data4':4}
print d.items()
print sorted(d.iteritems(),key = itemgetter(0)) #根据元组的第一项进行排序,此处即字典的键
print sorted(d.iteritems(),key = itemgetter(1)) #根据元组的第二项进行排序,此处即字典的值
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python列表排序
简单记一下python中List的sort方法(或者sorted内建函数)的用法。
关键字:
python列表排序 python字典排序 sorted
List的元素可以是各种东西,字符串,字典,自己定义的类等。
sorted函数用法如下:
- sorted(data, cmp=None, key=None, reverse=False)
其中,data是待排序数据,可以使List或者iterator, cmp和key都是函数,这两个函数作用与data的元素上产生一个结果,sorted方法根据这个结果来排序。
cmp(e1, e2) 是带两个参数的比较函数, 返回值: 负数: e1 < e2, 0: e1 == e2, 正数: e1 > e2. 默认为 None, 即用内建的比较函数.
key 是带一个参数的函数, 用来为每个元素提取比较值. 默认为 None, 即直接比较每个元素.
通常, key 和 reverse 比 cmp 快很多, 因为对每个元素它们只处理一次; 而 cmp 会处理多次.
通过例子来说明sorted的用法:
1. 对由tuple组成的List排序
- >>> students = [('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10),]
用key函数排序(lambda的用法见 注释1)
- >>> sorted(students, key=lambda s : s[2]) # sort by age
- [('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
用cmp函数排序
- >>> sorted(students, cmp=lambda x,y : cmp(x[2], y[2])) # sort by age asc
- [('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
- >>> sorted(students, cmp=lambda x,y : cmp(y[2], x[2])) # sort by age
desc,交换x/y的位置
- [('john', 'A', 15),
('jane', 'B', 12),('dave', 'B', 10)]
用 operator 函数来加快速度, 上面排序等价于:(itemgetter的用法见 注释2)
- >>> from operator import itemgetter, attrgetter
- >>> sorted(students, key=itemgetter(2))
用 operator 函数进行多级排序
- >>> sorted(students, key=itemgetter(1,2)) # sort by grade then by age
- [('john', 'A', 15), ('dave', 'B', 10), ('jane', 'B', 12)]
2. 对由字典排序
- >>> d = {'data1':3, 'data2':1, 'data3':2, 'data4':4}
- >>> sorted(d.iteritems(), key=itemgetter(1), reverse=True)
- [('data4', 4), ('data1', 3), ('data3', 2), ('data2', 1)]
from operator import itemgetter,attrgetter
d = {'data1':3,'data2':1,'data3':2,'data4':4}
print d.items()
print sorted(d.iteritems(),key = itemgetter(0)) #根据字典的键进行排序
print sorted(d.iteritems(),key = itemgetter(1)) #根据字典的值进行排序
注释1
参考:http://jasonwu.me/2011/10/29/introduce-to-python-lambda.html
注释2
参考:http://ar.newsmth.net/thread-90745710c90cf1.html
class itemgetter(__builtin__.object)
| itemgetter(item, ...) --> itemgetter object
|
| Return a callable object that fetches the given item(s) from its operand.
| After, f=itemgetter(2), the call f(r) returns r[2].
| After, g=itemgetter(2,5,3), the call g(r) returns (r[2], r[5], r[3])
相当于
- def itemgetter(i,*a):
- def func(obj):
- r = obj[i]
- if a:
- r = (r,) + tuple(obj[i] for i in a)
- return r
- return func
- >>> a = [1,2,3]
- >>> b=operator.itemgetter(1)
- >>> b(a)
- 2
- >>> b=operator.itemgetter(1,0)
- >>> b(a)
- (2, 1)
- >>> b=itemgetter(1)
- >>> b(a)
- 2
- >>> b=itemgetter(1,0)
- >>> b(a)
- (2, 1)
In Py2.x, sort allowed an optional function which can be called for doing thecomparisons. That function should take two arguments to be compared andthen return a negative value for less-than, return zero if they are equal,or return a positive value for greater-than. For example, we can do:
>>> def numeric_compare(x, y): return x - y>>> sorted([5, 2, 4, 1, 3], cmp=numeric_compare)[1,
2, 3, 4, 5]
Or you can reverse the order of comparison with:
>>> def reverse_numeric(x, y): return y - x>>> sorted([5, 2, 4, 1, 3], cmp=reverse_numeric)[5,
4, 3, 2, 1]
list.sort() method is only defined for lists. In contrast, the sorted() function accepts any iterable.
>>> sorted({1: 'D', 2: 'B', 3: 'B', 4: 'E', 5: 'A'})[1, 2, 3, 4, 5]