生成器

基于yield指令，可以暂停一个函数并返回中间结果。该函数将保存执行环境并且可以在必要
时恢复。

>>> def fibonacci():
...     a, b = 0, 1
...     while True:
...             yield b
...             a, b = b, a + b
...
>>> fib = fibonacci()
>>> fib.next()
1
>>> fib.next()
1
>>> fib.next()
2
>>> [fib.next() for i in range(10)]
[3, 5, 8, 13, 21, 34, 55, 89, 144, 233]
>>>

该函数将返回一个特殊的迭代器，也就是generator对象，它知道如何保存执行环境。对它的
调用是不确定的，每次都将产生序列中的下一个元素。

生成器对降低程序复杂性很有帮助:

>>> def power(values):
...     for value in values:
...             print 'powering %s' % value
...             yield value
...
>>> def adder(values):
...     for value in values:
...             print 'adding to %s' % value
...             if value % 2 == 0:
...                     yield value + 3
...             else:
...                     yield value + 2
...
>>> elements = [1, 4, 7, 9, 12, 19]
>>> res = adder(power(elements))
>>> res.next()
powering 1
adding to 1
3
>>> res.next()
powering 4
adding to 4
7

Python引入的与生成器相关的最后一个特性是提供了与next方法调用的代码进行交互的
功能。yield将变成一个表达式，而一个值可以通过名为send的新方法来传递:

>>> def psychologist():
...     print 'Please tell me your problems'
...     while True:
...             answer = (yield)
...             if answer is not None:
...                     if answer.endswith('?'):
...                             print ("Don't ask yourself too much questions")
...                     elif 'good' in answer:
...                             print "A that's good, go on"
...                     elif 'bad' in answer:
...                             print "Don't be so negative"
...
>>> free = psychologist()
>>> free.next()
Please tell me your problems
>>> free.send('I feel bad')
Don't be so negative
>>> free.send("Why i shouldn't ?")
Don't ask yourself too much questions

send的工作机制与next一样，但是yield将变成能够返回传入的值。因为，这个函数可以
根据客户端代码来改变其行为。同时，还添加了throw和close两个函数，以完成该行为。
它们将向生成器抛出一个错误：
    throw允许客户端代码传入要抛出的任何类型的异常；
    close的工作方式是相同的，但是将会抛出一个特定的异常----GeneratorExit,在
         这种情况下，生成器函数必须再次抛出GeneratorExit或StopIteration异
         常。

>>> def my_generator():
...     try:
...             yield 'something'
...     except ValueError:
...             yield 'dealing with the exception'
...     finally:
...             print "ok let's clean"
...
>>> gen = my_generator()
>>> gen.next()
'something'
>>> gen.throw(ValueError('mean mean mean'))
'dealing with the exception'
>>> gen.close()
ok let's clean
>>> gen.next()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration

生成器表达式:

>>> iter = (x**2 for x in range(10) if x % 2 == 0)
>>> for e1 in iter:
...     print e1
...
0
4
16
36
64
>>> iter.next()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration


>>> iter = (x**2 for x in range(10) if x % 2 == 0)
>>> iter.next()
0
>>> iter.next()
4

这种表达式常被称为生成器表达式或genexp。每当在yield表达式上创建简单的循环时，
都应该使用它，或者用它来代替表现类似迭代器的列表推导。