python性能-函数与生成器函数
我想知道哪一个性能更好:带状态的“常规”python函数,还是生成器。与此不同,我使用最简化的函数来隔离问题: 常规功能:python性能-函数与生成器函数,python,performance,Python,Performance,我想知道哪一个性能更好:带状态的“常规”python函数,还是生成器。与此不同,我使用最简化的函数来隔离问题: 常规功能: >>> def counter_reg(): if not hasattr(count_regular,"c"): count_regular.c = -1 count_regular.c +=1 return count_regular.c 发电机功能: >>
>>> def counter_reg():
if not hasattr(count_regular,"c"):
count_regular.c = -1
count_regular.c +=1
return count_regular.c
发电机功能:
>>> def counter_gen():
c = 0
while True:
yield c
c += 1
>>> counter = counter_gen()
>>> counter = counter.next
% python -mtimeit -s'import test as t' 't.using_count_regular(1000)'
1000 loops, best of 3: 336 usec per loop
% python -mtimeit -s'import test as t' 't.using_counter_gen(1000)'
10000 loops, best of 3: 172 usec per loop
% python -mtimeit -s'import test as t' 't.using_itertools(1000)'
10000 loops, best of 3: 105 usec per loop
在这两种情况下,调用counter()
和counter\u reg()
将产生相同的输出
哪一个性能更好?
谢谢,下面是一个示例,说明如何使用以下工具对Python函数进行基准测试: test.py:
import itertools as IT
def count_regular():
if not hasattr(count_regular,"c"):
count_regular.c = -1
count_regular.c +=1
return count_regular.c
def counter_gen():
c = 0
while True:
yield c
c += 1
def using_count_regular(N):
return [count_regular() for i in range(N)]
def using_counter_gen(N):
counter = counter_gen()
return [next(counter) for i in range(N)]
def using_itertools(N):
count = IT.count()
return [next(count) for i in range(N)]
像这样运行python来计时函数:
>>> def counter_gen():
c = 0
while True:
yield c
c += 1
>>> counter = counter_gen()
>>> counter = counter.next
% python -mtimeit -s'import test as t' 't.using_count_regular(1000)'
1000 loops, best of 3: 336 usec per loop
% python -mtimeit -s'import test as t' 't.using_counter_gen(1000)'
10000 loops, best of 3: 172 usec per loop
% python -mtimeit -s'import test as t' 't.using_itertools(1000)'
10000 loops, best of 3: 105 usec per loop
要进行更彻底的基准测试,请尝试不同的N
,尽管在这种情况下,我认为这无关紧要
因此,正如您所期望的那样,使用
itertools.count
比count\u regular
或counter\u gen都要快,仅通过查看第一个函数,我不建议这样做。至少用\uuu iter\uuuu
定义一个类,或者如果您需要将它作为一个函数,则使用一个默认参数def counter\u reg(c=[-1])
并修改counter\u gen()
每次调用它时都会生成一个新的计数器,counter\u reg()
增加一个全局值(尽管该函数有名称空间)。差别很大。你可以自己用timeit
模块来计时。更好地优化可读性。我怀疑发电机性能是瓶颈。(如果是,您可能不应该使用Python。)