Python不仅提供了list.sort（）方法来实现列表的排序，而且提供了内建sorted()函数来实现对复杂列表的排序以及按照字典的key和value进行排序。
sorted函数原型
sorted(data, cmp=None, key=None, reverse=False) #data为数据 #cmp和key均为比较函数 #reverse为排序方向，True为倒序，False为正序
基本用法
对于列表，直接进行排序
>>> sorted([5, 2, 3, 1, 4]) [1, 2, 3, 4, 5] >>> a = [5, 2, 3, 1, 4] >>> a.sort() >>> a [1, 2, 3, 4, 5]
对于字典，只对key进行排序
sorted({1: 'D', 2: 'B', 3: 'B', 4: 'E', 5: 'A'})
[1, 2, 3, 4, 5]
key函数
key函数应该接受一个参数并返回一个用于排序的key值。由于该函数只需要调用一次，因而排序速度较快。
复杂列表
>>> student_tuples = [ ('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10), ] >>> sorted(student_tuples, key=lambda student: student[2]) # sort by age [('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
如果列表内容是类的话，
>>> class Student: def __init__(self, name, grade, age): self.name = name self.grade = grade self.age = age def __repr__(self): return repr((self.name, self.grade, self.age)) >>> student_objects = [ Student('john', 'A', 15), Student('jane', 'B', 12), Student('dave', 'B', 10), ] >>> sorted(student_objects, key=lambda student: student.age) # sort by age [('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
字典
>>> student = [ {"name":"xiaoming", "score":60}, {"name":"daxiong", "score":20},
{"name":"maodou", "score":30},
]
>>> student
[{'score': 60, 'name': 'xiaoming'}, {'score': 20, 'name': 'daxiong'}, {'score': 30, 'name': 'maodou'}]
>>> sorted(student, key=lambda d:d["score"])
[{'score': 20, 'name': 'daxiong'}, {'score': 30, 'name': 'maodou'}, {'score': 60, 'name': 'xiaoming'}]
此外，Python提供了operator.itemgetter和attrgetter提高执行速度。
>>> from operator import itemgetter, attrgetter >>> student = [ ("xiaoming",60), ("daxiong", 20), ("maodou", 30}] >>> sorted(student, key=lambda d:d[1]) [('daxiong', 20), ('maodou', 30), ('xiaoming', 60)] >>> sorted(student, key=itemgetter(1)) [('daxiong', 20), ('maodou', 30), ('xiaoming', 60)]
operator提供了多个字段的复杂排序。
>>> sorted(student, key=itemgetter(0,1)) #根据第一个字段和第二个字段 [('daxiong', 20), ('maodou', 30), ('xiaoming', 60)]
operator.methodcaller()函数会按照提供的函数来计算排序。
>>> messages = ['critical!!!', 'hurry!', 'standby', 'immediate!!'] >>> sorted(messages, key=methodcaller('count', '!')) ['standby', 'hurry!', 'immediate!!', 'critical!!!']
首先通过count函数对"!"来计算出现次数，然后按照出现次数进行排序。
CMP
cmp参数是Python2.4之前使用的排序方法。
def numeric_compare(x, y): return x - y >>> sorted([5, 2, 4, 1, 3], cmp=numeric_compare) [1, 2, 3, 4, 5] >>> def reverse_numeric(x, y): return y - x >>> sorted([5, 2, 4, 1, 3], cmp=reverse_numeric) [5, 4, 3, 2, 1]
在functools.cmp_to_key函数提供了比较功能
>>> sorted([5, 2, 4, 1, 3], key=cmp_to_key(reverse_numeric)) [5, 4, 3, 2, 1] def cmp_to_key(mycmp): 'Convert a cmp= function into a key= function' class K(object): def __init__(self, obj, *args): self.obj = obj def __lt__(self, other): return mycmp(self.obj, other.obj) < 0 def __gt__(self, other): return mycmp(self.obj, other.obj) > 0 def __eq__(self, other): return mycmp(self.obj, other.obj) == 0 def __le__(self, other): return mycmp(self.obj, other.obj) <= 0 def __ge__(self, other): return mycmp(self.obj, other.obj) >= 0 def __ne__(self, other): return mycmp(self.obj, other.obj) != 0 return K
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