Python中的列表生成式与生成器学习教程
列表生成式
即创建列表的方式，最笨的方法就是写循环逐个生成，前面也介绍过可以使用range()函数来生成，不过只能生成线性列表，下面看看更为高级的生成方式：
>>> [x * x for x in range(1, 11)] [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
写列表生成式时，把要生成的元素x * x放到前面，后面跟for循环，就可以把list创建出来，十分有用，多写几次，很快就可以熟悉这种语法。
你甚至可以在后面加上if判断：
>>> [x * x for x in range(1, 11) if x % 2 == 0] [4, 16, 36, 64, 100]
循环嵌套，全排列：
>>> [m + n for m in 'ABC' for n in 'XYZ'] ['AX', 'AY', 'AZ', 'BX', 'BY', 'BZ', 'CX', 'CY', 'CZ']
看一个简单应用，列出当前目录下所有文件和目录：
>>> import os
>>> [d for d in os.listdir('.')]
['README.md', '.git', 'image', 'os', 'lib', 'sublime-imfix', 'src']
前面也说过Python里循环中可以同时引用两个变量，所以生成变量也可以：
>>> d = {'x': 'A', 'y': 'B', 'z': 'C' }
>>> [k + '=' + v for k, v in d.iteritems()]
['y=B', 'x=A', 'z=C']
也可以通过一个list生成另一个list，例如把一个list中所有字符串变为小写：
>>> L = ['Hello', 'World', 'IBM', 'Apple'] >>> [s.lower() for s in L] ['hello', 'world', 'ibm', 'apple']
但是这里有个问题，list中如果有其他非字符串类型，那么lower()会报错，解决办法：
>>> L = ['Hello', 'World', 'IBM', 'Apple', 12, 34] >>> [s.lower() if isinstance(s,str) else s for s in L] ['hello', 'world', 'ibm', 'apple', 12, 34]
此外，列表生成式还有许多神奇用法，说明请看注释：
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
list(range(1, 11))
# 生成1乘1，2乘2...10乘10
L = []
for x in range(1, 11):
L.append(x * x)
# 上面太麻烦，看下面
[x * x for x in range(1, 11)]
# [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
# 加上if，就可以筛选出仅偶数的平方
[x * x for x in range(1, 11) if x % 2 == 0]
# [4, 16, 36, 64, 100]
# 两层循环，可以生成全排列
[m + n for m in 'ABC' for n in 'XYZ']
# ['AX', 'AY', 'AZ', 'BX', 'BY', 'BZ', 'CX', 'CY', 'CZ']
# 列出当前目录下的所有文件和目录名
import os
[d for d in os.listdir('.')] # on.listdir可以列出文件和目录
# 列表生成式也可以使用两个变量来生成list:
d = {'x': 'A', 'y': 'B', 'z': 'C'}
[k + '=' + v for k, v in d.items()]
# ['x=A', 'z=C', 'y=B']
# 把一个list中所有的字符串变成小写
L = ['Hello', 'World', 'IBM', 'Apple']
[s.lower() for s in L]
# ['hello', 'world', 'ibm', 'apple']
L1 = ['Hello', 'World', 18, 'Apple', None]
L2 = [s.lower() for s in L1 if isinstance(s, str)]
print(L2)
# ['hello', 'world', 'apple']
# isinstance函数可以判断一个变量是不是字符串
生成器
列表生成式虽然强大，但是也会有一个问题，当我们想生成一个很大的列表时，会非常耗时，并且占用很大的存储空间，关键是这里面的元素可能你只需要用到前面很少的一部分，大部分的空间和时间都浪费了。Python提供了一种边计算边使用的机制，称为生成器(Generator)，创建一个Generator最简单的方法就是把[]改为()：
>>> g = (x * x for x in range(10)) >>> g <generator object <genexpr> at 0x7fe73eb85cd0>
如果要一个一个打印出来，可以通过generator的next()方法：
>>> g.next() 0 >>> g.next() 1 >>> g.next() 4 >>> g.next() 9 >>> g.next() 16 >>> g.next() 25 >>> g.next() 36 >>> g.next() 49 >>> g.next() 64 >>> g.next() 81 >>> g.next() Traceback (most recent call last): File "<stdin>", line 1, in <module> StopIteration
其实generator object也是可迭代的，所以可以用循环打印，还不会报错。
>>> g = (x * x for x in range(10)) >>> for n in g: ... print n ...
这是简单的推算算法，但是如果算法比较复杂，写在()里就不太合适了，我们可以换一种方式，使用函数来实现。
比如，著名的斐波拉契数列（Fibonacci），除第一个和第二个数外，任意一个数都可由前两个数相加得到：
1, 1, 2, 3, 5, 8, 13, 21, 34, …
斐波拉契数列用列表生成式写不出来，但是，用函数把它打印出来却很容易：
def fib(max):
n, a, b = 0, 0, 1
while n < max:
print b
a, b = b, a + b
n = n + 1
上面的函数可以输出斐波那契数列的前N个数,这个也是通过前面的数推算出后面的，所以可以把函数变成generator object，只需要把print b改为yield b即可。
def fib(max):
n, a, b = 0, 0, 1
while n < max:
yield b
a, b = b, a + b
n = n + 1
如果一个函数定义中包含了yield关键字，这个函数就不在是普通函数，而是一个generator object。
>>> fib(6) <generator object fib at 0x7fa1c3fcdaf0> >>> fib(6).next() 1
所以要想调用这个函数，需要使用next()函数，并且遇到yield语句返回(可以把yield理解为return):
def odd(): print 'step 1' yield 1 print 'step 2' yield 3 print 'step 3' yield 5
看看调用输出结果：
>>> o = odd() >>> o.next() step 1 1 >>> o.next() step 2 3 >>> o.next() step 3 5 >>> o.next() Traceback (most recent call last): File "<stdin>", line 1, in <module> StopIteration
同样也可以改为for循环语句输出。例如：
def odd():
print 'step 1'
yield 1
print 'step 2'
yield 2
print 'step 3'
yield 3
if __name__ == '__main__':
o = odd()
while True:
try:
print o.next()
except:
break
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