2014-08-21 10:27:10 +08:00
|
|
|
|
============================
|
2014-09-02 04:46:28 +08:00
|
|
|
|
4.3 使用生成器创建新的迭代模式
|
2014-08-21 10:27:10 +08:00
|
|
|
|
============================
|
|
|
|
|
|
|
|
|
|
|
|
----------
|
|
|
|
|
|
问题
|
|
|
|
|
|
----------
|
2014-09-23 10:52:16 +08:00
|
|
|
|
你想实现一个自定义迭代模式,跟普通的内置函数比如 ``range()`` , ``reversed()`` 不一样。
|
2014-09-14 19:10:17 +08:00
|
|
|
|
|
2014-08-21 10:27:10 +08:00
|
|
|
|
----------
|
|
|
|
|
|
解决方案
|
|
|
|
|
|
----------
|
2014-09-14 19:10:17 +08:00
|
|
|
|
如果你想实现一种新的迭代模式,使用一个生成器函数来定义它。
|
|
|
|
|
|
下面是一个生产某个范围内浮点数的生成器:
|
|
|
|
|
|
|
|
|
|
|
|
.. code-block:: python
|
|
|
|
|
|
|
|
|
|
|
|
def frange(start, stop, increment):
|
|
|
|
|
|
x = start
|
|
|
|
|
|
while x < stop:
|
|
|
|
|
|
yield x
|
|
|
|
|
|
x += increment
|
|
|
|
|
|
|
2014-09-23 10:52:16 +08:00
|
|
|
|
为了使用这个函数,
|
|
|
|
|
|
你可以用for循环迭代它或者使用其他接受一个可迭代对象的函数(比如 ``sum()`` , ``list()`` 等)。示例如下:
|
2014-09-14 19:10:17 +08:00
|
|
|
|
|
|
|
|
|
|
.. code-block:: python
|
|
|
|
|
|
|
|
|
|
|
|
>>> for n in frange(0, 4, 0.5):
|
|
|
|
|
|
... print(n)
|
|
|
|
|
|
...
|
|
|
|
|
|
0
|
|
|
|
|
|
0.5
|
|
|
|
|
|
1.0
|
|
|
|
|
|
1.5
|
|
|
|
|
|
2.0
|
|
|
|
|
|
2.5
|
|
|
|
|
|
3.0
|
|
|
|
|
|
3.5
|
|
|
|
|
|
>>> list(frange(0, 1, 0.125))
|
|
|
|
|
|
[0, 0.125, 0.25, 0.375, 0.5, 0.625, 0.75, 0.875]
|
|
|
|
|
|
>>>
|
|
|
|
|
|
|
2014-08-21 10:27:10 +08:00
|
|
|
|
----------
|
|
|
|
|
|
讨论
|
|
|
|
|
|
----------
|
2015-09-18 12:15:09 +08:00
|
|
|
|
一个函数中需要有一个 ``yield`` 语句即可将其转换为一个生成器。
|
2014-09-14 19:10:17 +08:00
|
|
|
|
跟普通函数不同的是,生成器只能用于迭代操作。
|
|
|
|
|
|
下面是一个实验,向你展示这样的函数底层工作机制:
|
|
|
|
|
|
|
|
|
|
|
|
.. code-block:: python
|
|
|
|
|
|
|
|
|
|
|
|
>>> def countdown(n):
|
|
|
|
|
|
... print('Starting to count from', n)
|
|
|
|
|
|
... while n > 0:
|
|
|
|
|
|
... yield n
|
|
|
|
|
|
... n -= 1
|
|
|
|
|
|
... print('Done!')
|
|
|
|
|
|
...
|
|
|
|
|
|
|
|
|
|
|
|
>>> # Create the generator, notice no output appears
|
|
|
|
|
|
>>> c = countdown(3)
|
|
|
|
|
|
>>> c
|
|
|
|
|
|
<generator object countdown at 0x1006a0af0>
|
|
|
|
|
|
|
|
|
|
|
|
>>> # Run to first yield and emit a value
|
|
|
|
|
|
>>> next(c)
|
|
|
|
|
|
Starting to count from 3
|
|
|
|
|
|
3
|
|
|
|
|
|
|
|
|
|
|
|
>>> # Run to the next yield
|
|
|
|
|
|
>>> next(c)
|
|
|
|
|
|
2
|
|
|
|
|
|
|
|
|
|
|
|
>>> # Run to next yield
|
|
|
|
|
|
>>> next(c)
|
|
|
|
|
|
1
|
|
|
|
|
|
|
|
|
|
|
|
>>> # Run to next yield (iteration stops)
|
|
|
|
|
|
>>> next(c)
|
|
|
|
|
|
Done!
|
|
|
|
|
|
Traceback (most recent call last):
|
|
|
|
|
|
File "<stdin>", line 1, in <module>
|
|
|
|
|
|
StopIteration
|
|
|
|
|
|
>>>
|
|
|
|
|
|
|
2015-09-18 12:15:09 +08:00
|
|
|
|
一个生成器函数主要特征是它只会回应在迭代中使用到的 *next* 操作。
|
2014-09-14 19:10:17 +08:00
|
|
|
|
一旦生成器函数返回退出,迭代终止。我们在迭代中通常使用的for语句会自动处理这些细节,所以你无需担心。
|
|
|
|
|
|
|