python sorted排序

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