部分应用很酷。functools有什么功能。部分报价，你不能通过lambdas?
>>> sum = lambda x, y : x + y
>>> sum(1, 2)
3
>>> incr = lambda y : sum(1, y)
>>> incr(2)
3
>>> def sum2(x, y):
return x + y
>>> incr2 = functools.partial(sum2, 1)
>>> incr2(4)
5
functools在某种程度上更有效或更可读吗?
当前回答
在最新版本的Python(>=2.7)中，你可以pickle一个partial，但不能pickle一个lambda:
>>> pickle.dumps(partial(int))
'cfunctools\npartial\np0\n(c__builtin__\nint\np1\ntp2\nRp3\n(g1\n(tNNtp4\nb.'
>>> pickle.dumps(lambda x: int(x))
Traceback (most recent call last):
File "<ipython-input-11-e32d5a050739>", line 1, in <module>
pickle.dumps(lambda x: int(x))
File "/usr/lib/python2.7/pickle.py", line 1374, in dumps
Pickler(file, protocol).dump(obj)
File "/usr/lib/python2.7/pickle.py", line 224, in dump
self.save(obj)
File "/usr/lib/python2.7/pickle.py", line 286, in save
f(self, obj) # Call unbound method with explicit self
File "/usr/lib/python2.7/pickle.py", line 748, in save_global
(obj, module, name))
PicklingError: Can't pickle <function <lambda> at 0x1729aa0>: it's not found as __main__.<lambda>
其他回答
好吧，这里有一个例子可以说明区别:
In [132]: sum = lambda x, y: x + y
In [133]: n = 5
In [134]: incr = lambda y: sum(n, y)
In [135]: incr2 = partial(sum, n)
In [136]: print incr(3), incr2(3)
8 8
In [137]: n = 9
In [138]: print incr(3), incr2(3)
12 8
Ivan Moore的这些帖子扩展了“lambda的限制”和python中的闭包:
Python闭包(第2部分) Python闭包(第3部分)
functools是否更有效?
作为对这个问题的部分回答，我决定测试性能。以下是我的例子:
from functools import partial
import time, math
def make_lambda():
x = 1.3
return lambda: math.sin(x)
def make_partial():
x = 1.3
return partial(math.sin, x)
Iter = 10**7
start = time.clock()
for i in range(0, Iter):
l = make_lambda()
stop = time.clock()
print('lambda creation time {}'.format(stop - start))
start = time.clock()
for i in range(0, Iter):
l()
stop = time.clock()
print('lambda execution time {}'.format(stop - start))
start = time.clock()
for i in range(0, Iter):
p = make_partial()
stop = time.clock()
print('partial creation time {}'.format(stop - start))
start = time.clock()
for i in range(0, Iter):
p()
stop = time.clock()
print('partial execution time {}'.format(stop - start))
在Python 3.3上，它给出:
lambda creation time 3.1743163756961392
lambda execution time 3.040552701787919
partial creation time 3.514482823352731
partial execution time 1.7113973411608114
这意味着部分需要更多的时间来创建，但执行的时间要少得多。这很可能是ars的回答中讨论的早期和晚期绑定的影响。
我最容易理解第三个例子的意图。
当我解析lambdas时，我期望比标准库直接提供的更复杂/奇怪。
另外，你会注意到第三个例子是唯一一个不依赖于sum2的完整签名的例子;从而使它的耦合稍微松散一些。
在最新版本的Python(>=2.7)中，你可以pickle一个partial，但不能pickle一个lambda:
>>> pickle.dumps(partial(int))
'cfunctools\npartial\np0\n(c__builtin__\nint\np1\ntp2\nRp3\n(g1\n(tNNtp4\nb.'
>>> pickle.dumps(lambda x: int(x))
Traceback (most recent call last):
File "<ipython-input-11-e32d5a050739>", line 1, in <module>
pickle.dumps(lambda x: int(x))
File "/usr/lib/python2.7/pickle.py", line 1374, in dumps
Pickler(file, protocol).dump(obj)
File "/usr/lib/python2.7/pickle.py", line 224, in dump
self.save(obj)
File "/usr/lib/python2.7/pickle.py", line 286, in save
f(self, obj) # Call unbound method with explicit self
File "/usr/lib/python2.7/pickle.py", line 748, in save_global
(obj, module, name))
PicklingError: Can't pickle <function <lambda> at 0x1729aa0>: it's not found as __main__.<lambda>
除了Alex提到的额外功能，functools的另一个优点是。偏微分是速度。使用partial，你可以避免构造(和破坏)另一个堆栈框架。
由partial和lambdas生成的函数默认都没有文档字符串(尽管你可以通过__doc__为任何对象设置文档字符串)。
你可以在这个博客中找到更多细节:Python中的部分函数应用
