python中list列表的高级应用 高级函数

python基础

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2018-2-23

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在python所有的数据结构中,list具有重要地位,并且非常的方便,这篇文章主要是讲解list列表的高级应用,基础知识可以查看博客
此文章为python英文文档的翻译版本,你也可以查看英文版。https://docs.python.org/2/tutorial/datastructures.html

use a list as a stack: #像栈一样使用列表

stack = [3, 4, 5]
stack.append(6)
stack.append(7)
stack
[3, 4, 5, 6, 7]
stack.pop() #删除最后一个对象
7
stack
[3, 4, 5, 6]
stack.pop()
6
stack.pop()
5
stack
[3, 4]

use a list as a queue: #像队列一样使用列表

> from collections import deque #这里需要使用模块deque 
> queue = deque(["Eric", "John", "Michael"])
> queue.append("Terry")           # Terry arrives
> queue.append("Graham")          # Graham arrives
> queue.popleft()                 # The first to arrive now leaves
'Eric'
> queue.popleft()                 # The second to arrive now leaves
'John'
> queue                           # Remaining queue in order of arrival
deque(['Michael', 'Terry', 'Graham'])

three built-in functions: 三个重要的内建函数

filter(), map(), and reduce().
filter(function, sequence)::
按照function函数的规则在列表sequence中筛选数据

> def f(x): return x % 3 == 0 or x % 5 == 0
... #f函数为定义整数对象x,x性质为是3或5的倍数
> filter(f, range(2, 25))  #筛选
[3, 5, 6, 9, 10, 12, 15, 18, 20, 21, 24]

map(function, sequence):
map函数实现按照function函数的规则对列表sequence做同样的处理,
这里sequence不局限于列表,元组同样也可。

> def cube(x): return x*x*x #这里是立方计算 还可以使用 x**3的方法
...
> map(cube, range(1, 11)) #对列表的每个对象进行立方计算
[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]

注意:这里的参数列表不是固定不变的,主要看自定义函数的参数个数,map函数可以变形为:def func(x,y) map(func,sequence1,sequence2) 举例:

 seq = range(8)   #定义一个列表
> def add(x, y): return x+y  #自定义函数,有两个形参
...
> map(add, seq, seq) #使用map函数,后两个参数为函数add对应的操作数,如果列表长度不一致会出现错误
[0, 2, 4, 6, 8, 10, 12, 14]

reduce(function, sequence):
reduce函数功能是将sequence中数据,按照function函数操作,如 将列表第一个数与第二个数进行function操作,得到的结果和列表中下一个数据进行function操作,一直循环下去…
举例:

def add(x,y): return x+y
...
reduce(add, range(1, 11))
55

List comprehensions:
这里将介绍列表的几个应用:
squares = [x**2 for x in range(10)]
#生成一个列表,列表是由列表range(10)生成的列表经过平方计算后的结果。
[(x, y) for x in [1,2,3] for y in [3,1,4] if x != y]
#[(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)] 这里是生成了一个列表,列表的每一项为元组,每个元组是由x和y组成,x是由列表[1,2,3]提供,y来源于[3,1,4],并且满足法则x!=y。

Nested List Comprehensions:
这里比较难翻译,就举例说明一下吧:

matrix = [                    #此处定义一个矩阵
...     [1, 2, 3, 4],
...     [5, 6, 7, 8],
...     [9, 10, 11, 12],
... ]
[[row[i] for row in matrix] for i in range(4)]
#[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

这里两层嵌套比较麻烦,简单讲解一下:对矩阵matrix,for row in matrix来取出矩阵的每一行,row[i]为取出每行列表中的第i个(下标),生成一个列表,然后i又是来源于for i in range(4) 这样就生成了一个列表的列表。

The del statement:
删除列表指定数据,举例:

> a = [-1, 1, 66.25, 333, 333, 1234.5]
>del a[0] #删除下标为0的元素
>a
[1, 66.25, 333, 333, 1234.5]
>del a[2:4] #从列表中删除下标为2,3的元素
>a
[1, 66.25, 1234.5]
>del a[:] #全部删除 效果同 del a
>a
[]

Sets: 集合

> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
>>> fruit = set(basket)               # create a set without duplicates
>>> fruit
set(['orange', 'pear', 'apple', 'banana'])
>>> 'orange' in fruit                 # fast membership testing
True
>>> 'crabgrass' in fruit
False
 
>>> # Demonstrate set operations on unique letters from two words
...
>>> a = set('abracadabra')
>>> b = set('alacazam')
>>> a                                  # unique letters in a
set(['a', 'r', 'b', 'c', 'd'])
>>> a - b                              # letters in a but not in b
set(['r', 'd', 'b'])
>>> a | b                              # letters in either a or b
set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'])
>>> a & b                              # letters in both a and b
set(['a', 'c'])
>>> a ^ b                              # letters in a or b but not both
set(['r', 'd', 'b', 'm', 'z', 'l'])

Dictionaries:字典

>>> tel = {'jack': 4098, 'sape': 4139}
>>> tel['guido'] = 4127 #相当于向字典中添加数据
>>> tel
{'sape': 4139, 'guido': 4127, 'jack': 4098}
>>> tel['jack'] #取数据
4098
>>> del tel['sape']  #删除数据
>>> tel['irv'] = 4127      #修改数据
>>> tel
{'guido': 4127, 'irv': 4127, 'jack': 4098}
>>> tel.keys()        #取字典的所有key值
['guido', 'irv', 'jack']
>>> 'guido' in tel  #判断元素的key是否在字典中
True
>>> tel.get('irv')  #取数据
4127

也可以使用规则生成字典:

>>> {x: x**2 for x in (2, 4, 6)}
{2: 4, 4: 16, 6: 36}

enumerate():遍历元素及下标
enumerate 函数用于遍历序列中的元素以及它们的下标:

>>> for i, v in enumerate(['tic', 'tac', 'toe']):
...     print i, v
...
0 tic
1 tac
2 toe

zip():
zip()是Python的一个内建函数,它接受一系列可迭代的对象作为参数,将对象中对应的元素打包成一个个tuple(元组),然后返回由这些tuples组成的list(列表)。若传入参数的长度不等,则返回list的长度和参数中长度最短的对象相同。利用*号操作符,可以将list unzip(解压)。

>>> questions = ['name', 'quest', 'favorite color']
>>> answers = ['lancelot', 'the holy grail', 'blue']
>>> for q, a in zip(questions, answers):
...     print 'What is your {0}?  It is {1}.'.format(q, a)
...
What is your name?  It is lancelot.
What is your quest?  It is the holy grail.
What is your favorite color?  It is blue.

有关zip举一个简单点儿的例子:

>>> a = [1,2,3]
>>> b = [4,5,6]
>>> c = [4,5,6,7,8]
>>> zipped = zip(a,b)
[(1, 4), (2, 5), (3, 6)]
>>> zip(a,c)
[(1, 4), (2, 5), (3, 6)]
>>> zip(*zipped)
[(1, 2, 3), (4, 5, 6)]

reversed():反转

>>> for i in reversed(xrange(1,10,2)):
...     print i
...
9
7
5
3
1

sorted(): 排序

> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
> for f in sorted(set(basket)):             #这里使用了set函数
...     print f
...
apple
banana
orange
pear

python的set和其他语言类似, 是一个 基本功能包括关系测试和消除重复元素.

To change a sequence you are iterating over while inside the loop (for example to duplicate certain items), it is recommended that you first make a copy. Looping over a sequence does not implicitly make a copy. The slice notation makes this especially convenient:

>>> words = ['cat', 'window', 'defenestrate']
>>> for w in words[:]:  # Loop over a slice copy of the entire list.
...     if len(w) > 6:
...         words.insert(0, w)
...
>>> words
['defenestrate', 'cat', 'window', 'defenestrate']

原文地址:http://lib.csdn.net/article/python/4729

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