yield 的学习，模拟无限数据 ::-- ZoomQuiet [DateTime(2007-10-24T04:15:39Z)] TableOfContents

Include(CPUGnav) {{{Albert Lee <[email protected]> hide details 12:08 pm (2 minutes ago)

• reply-to [email protected] to "Python.cn@google" <[email protected]> date Oct 24, 2007 12:08 PM subject [CPyUG:34110] yield 的学习，模拟无限数据 mailed-by googlegroups.com

}}}

1. FPy 模拟

1.1. yield 的学习，模拟无限数据

对haskell我最喜爱的特性是惰性计算和无限数据结构，以及函数组合。 这些特性在python中是否可以模拟出来呢？ 今天作了一些尝试

python中提供了yield 和 decorators, 应当可以模拟出。

1.1.1. 尝试: 无限数据结构

haskell: [1..]

Hugs> take 5 [1..]
[1,2,3,4,5]

Python:

>>> def inf_list1():
i = 0
while 1:
i += 1
yield i

>>> def take(n, it):
cnt = 0
for i in it():
cnt += 1
if cnt > n: break
yield i

>>> take(5, m)

>>> [i for i in take(5, inf_list1)]
[1, 2, 3, 4, 5]

Python 的 take 也实现为一个 generator ，这样的好处是可以串起来执行，比如，我要实现 haskell中的： Hugs> drop 3 $ take 5 [1..] [4,5]

• 那么再实现一个 drop 函数：

>>> def drop(n, it):
t = 0
for i in it():
t += 1
if t > n:
yield i

>>> def m10():
for i in range(10):
yield i

>>> [i for i in drop(3, m10)]
[3, 4, 5, 6, 7, 8, 9]
>>> [i for i in take(5, m10)]
[0, 1, 2, 3, 4]
>>>

• 不过，在组合 take 和 drop 的时候遇到了麻烦

>>> drop(3, take(5, m10))

>>> [i for i in drop(3, take(5, m10))]

Traceback (most recent call last):
File "", line 1, in -toplevel-
[i for i in drop(3, take(5, m10))]
File "", line 3, in drop
for i in it():
TypeError: 'generator' object is not callable
>>>

• 修改下 drop, take 的定义如下：

>>> def take(n, it):
cnt = 0
if callable(it): it=it()
for i in it:
cnt += 1
if cnt > n: break
yield i
>>> def drop(n, it):
cnt = 0
if callable(it): it = it()
for i in it:
cnt += 1
if cnt > n:
yield i

>>> [i for i in take(2, drop(3, take(7, inf_list1)))]
[4, 5]
>>>

1.1.2. 对应 haskell

Hugs> take 2 $ drop 3 $ take 7 [1..]
[4,5]
Hugs>

基本达到目的。

1.1.3. 用itertools模块更简单

{{{Qiangning Hong <[email protected]> hide details 12:57 pm (8 minutes ago)

• reply-to [email protected] to [email protected] date Oct 24, 2007 12:57 PM subject [CPyUG:34115] Re: yield 的学习，模拟无限数据：

}}}

{{{!python import sys from itertools import count, islice

def inf_list():

• return count(1)

def take(n, it):

• return islice(it, n)

def drop(n, it):

• return islice(it, n, sys.maxint)

list(take(5, inf_list()) -> [1, 2, 3, 4, 5] list(drop(3, take(5, inf_list()))) -> [4, 5] list(take(2, drop(3, take(7, count(1))))) -> [4, 5] }}}

1.2. 函数的组合

比较简单:

Hugs> ((*2) . (+3)) 5
16

• 在Python

  >>> def m2(x):
         return  x * 2
  
  >>> def add3(x):
         return x + 3
  
  >>> def compose(f, g):
         return lambda x:f(g(x))
  
  >>> compose(m2, add3)
  <function <lambda> at 0x012875F0>
  >>> compose(m2, add3)(5)
  16
  >>>

1.2.1. 对compose的装饰：

infix 来自 cookbook

class Infix:
   def __init__(self, function):
       self.function = function
   def __ror__(self, other):
       return Infix(lambda x, self=self, other=other: self.function(other, x))
   def __or__(self, other):
       return self.function(other)
   def __rlshift__(self, other):
       return Infix(lambda x, self=self, other=other: self.function(other, x))
   def __rshift__(self, other):
       return self.function(other)
   def __call__(self, value1, value2):
       return self.function(value1, value2)

# compose
def compose(f, g):
   return lambda x:f(g(x))

o=Infix(compose)

add2 = lambda x:x+2
multi3 = lambda x:x*3
new_f = add2 |o| multi3
print new_f(3)

---

>>> (add2 <<o>> multi3) (3)
11

已经比较接近了

1.3. 反馈

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