区别：
- 首先sorted和sort 的区别主要在于sorted是将排序完的数据赋予给一个新变量，而sort则是在原变量的基础上直接进行排序，不产生新变量；
- 调用方式：
list.sort() #list本身改变了顺序
sorted(iterable) - sort只能对iterable的列表排序，sorted既能对列表也包括任何iterable ；
In [201]: s3 = {1: 'D', 2: 'B', 4: 'B', 3: 'E', 5: 'A'} #字典类型的
In [202]: sorted(s3) #只能用sorted排序
Out[202]: [1, 2, 3, 4, 5]
<font color=red>safds</font>
In [183]: s1 = 'python'
In [184]: s2 = ['c','a','b']
In [185]: sorted(s1)
Out[185]: ['h', 'n', 'o', 'p', 't', 'y']
In [186]: s1
Out[186]: 'python'
In [187]: sorted(s2)
Out[187]: ['a', 'b', 'c']
In [188]: s2
Out[188]: ['c', 'a', 'b']
In [189]:
In [189]: s2.sort()
In [190]: s2
Out[190]: ['a', 'b', 'c']
In [191]:
In [191]: s1.sort()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-191-e125c1850991> in <module>()
----> 1 s1.sort()
AttributeError: 'str' object has no attribute 'sort'
用法：
1. 原址排序：
列表有自己的sort方法，其对列表进行原址排序，既然是原址排序，那显然元组不可能拥有这种方法，因为元组是不可修改的
x = [4, 6, 2, 1, 7, 9]
x.sort()
print x # [1, 2, 4, 6, 7, 9]
2. 副本排序
-
(1）[:]分片方法
x =[4, 6, 2, 1, 7, 9]
y = x[ : ]
y.sort()
print y #[1, 2, 4, 6, 7, 9]
print x #[4, 6, 2, 1, 7, 9]
注意：y = x[:] 通过分片操作将列表x的元素全部拷贝给y，如果简单的把x赋值给y：y = x，y和x还是指向同一个列表，并没有产生新的副本。
-
(2）sorted方法
sorted返回一个有序的副本，并且类型总是列表，如下：
x =[4, 6, 2, 1, 7, 9]
y = sorted(x)
print y #[1, 2, 4, 6, 7, 9]
print x #[4, 6, 2, 1, 7, 9]
1
print sorted('Python') #['P', 'h', 'n', 'o', 't', 'y']
复杂排序
In [147]: a= [('b',1), ('c',2), ('a',3)]
In [148]: a
Out[148]: [('b', 1), ('c', 2), ('a', 3)]
In [149]: d = sorted(a)
In [150]: d
Out[150]: [('a', 3), ('b', 1), ('c', 2)]
In [151]: a
Out[151]: [('b', 1), ('c', 2), ('a', 3)]
In [152]: c = a.sort()
In [153]: a
Out[153]: [('a', 3), ('b', 1), ('c', 2)]
In [154]: c
3. 给对象中的项排序
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)]
The same technique works for objects with named attributes. For example:
>>> 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)]
note：sorted(student_objects, key=lambda student: student.age)写法
4. 给对象中的两项排序
>>>sorted(student_tuples, key=itemgetter(1,2))
[('john', 'A', 15), ('dave', 'B', 10), ('jane', 'B', 12)]
>>>> sorted(student_objects, key=attrgetter('grade', 'age'))
[('john', 'A', 15), ('dave', 'B', 10), ('jane', 'B', 12)]
5. 根据含有子串的数目排序
例子如下：根据字符串含有"!"的个数进行排序
For example:
>>>> from operator import methodcaller
>>> messages = ['critical!!!', 'hurry!', 'standby', 'immediate!!']
>>> sorted(messages, key=methodcaller('count', '!'))
['standby', 'hurry!', 'immediate!!', 'critical!!!']
6. 升序和降序
默认是升序，也可以按照降序排序
# 按照升序和降序排序
def sort4():
student_tuples = [('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]
print sorted(student_tuples, key=lambda student: student[2]) #[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
print sorted(student_tuples, key=lambda student: student[2],reverse=True) #[('john', 'A', 15), ('jane', 'B', 12), ('dave', 'B', 10)]
7. 更复杂排序
更复杂地你可以构建多个步骤来进行更复杂的排序，例如对student数据先以age升序排列，再以grade降序排列。
>>> s = sorted(student_objects, key=attrgetter('age')) # sort on secondary key
>>> sorted(s, key=attrgetter('grade'), reverse=True) # now sort on primary key, descending
[('dave', 'B', 10), ('jane', 'B', 12), ('john', 'A', 15)]
参考：https://www.cnblogs.com/sunny3312/archive/2017/01/07/6260472.html
