python中list列表的高级函数
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().
1）、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]
2）、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]
3）、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 ...
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']
以上就是本文的全部内容，希望对大家的学习有所帮助。
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