讨厌 Python 的人总是会说，他们不想用 Python 的一个重要原因是 Python 很慢。而事实上，无论使用什么编程语言，特定程序的运行速度很大程度上取决于编写程序的开发人员以及他们优化程序、加快程序运行速度的技能。
# slow_program.py
from decimal import *
def exp(x):
getcontext().prec += 2
i, lasts, s, fact, num = 0, 0, 1, 1, 1
while s != lasts:
lasts = s
i += 1
fact *= i
num *= x
s += num / fact
getcontext().prec -= 2
return +s
exp(Decimal(150))
exp(Decimal(400))
exp(Decimal(3000))~ $ time python3.8 slow_program.py
real 0m11,058s
user 0m11,050s
sys 0m0,008s~ $ python3.8 -m cProfile -s time slow_program.py
1297 function calls (1272 primitive calls) in 11.081 seconds
Ordered by: internal time
ncalls tottime percall cumtime percall filename:lineno(function)
3 11.079 3.693 11.079 3.693 slow_program.py:4(exp)
1 0.000 0.000 0.002 0.002 {built-in method _imp.create_dynamic}
4/1 0.000 0.000 11.081 11.081 {built-in method builtins.exec}
6 0.000 0.000 0.000 0.000 {built-in method __new__ of type object at 0x9d12c0}
6 0.000 0.000 0.000 0.000 abc.py:132(__new__)
23 0.000 0.000 0.000 0.000 _weakrefset.py:36(__init__)
245 0.000 0.000 0.000 0.000 {built-in method builtins.getattr}
2 0.000 0.000 0.000 0.000 {built-in method marshal.loads}
10 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap_external>:1233(find_spec)
8/4 0.000 0.000 0.000 0.000 abc.py:196(__subclasscheck__)
15 0.000 0.000 0.000 0.000 {built-in method posix.stat}
6 0.000 0.000 0.000 0.000 {built-in method builtins.__build_class__}
1 0.000 0.000 0.000 0.000 __init__.py:357(namedtuple)
48 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap_external>:57(_path_join)
48 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap_external>:59(<listcomp>)
1 0.000 0.000 11.081 11.081 slow_program.py:1(<module>)
...def timeit_wrapper(func):
@wraps(func)
def wrapper(*args, **kwargs):
start = time.perf_counter() # Alternatively, you can use time.process_time()
func_return_val = func(*args, **kwargs)
end = time.perf_counter()
print('{0:<10}.{1:<8} : {2:<8}'.format(func.__module__, func.__name__, end - start))
return func_return_val
return wrapper@timeit_wrapper
def exp(x):
...
print('{0:<10} {1:<8} {2:^8}'.format('module', 'function', 'time'))
exp(Decimal(150))
exp(Decimal(400))
exp(Decimal(3000))~ $ python3.8 slow_program.py
module function time
__main__ .exp : 0.003267502994276583
__main__ .exp : 0.038535295985639095
__main__ .exp : 11.728486061969306import functools
import time
# caching up to 12 different results
@functools.lru_cache(maxsize=12)
def slow_func(x):
time.sleep(2) # Simulate long computation
return x
slow_func(1) # ... waiting for 2 sec before getting result
slow_func(1) # already cached - result returned instantaneously!
slow_func(3) # ... waiting for 2 sec before getting result# Example #1
class FastClass:
def do_stuff(self):
temp = self.value # this speeds up lookup in loop
for i in range(10000):
... # Do something with `temp` here
# Example #2
import random
def fast_function():
r = random.random
for i in range(10000):
print(r()) # calling `r()` here, is faster than global random.random()
使用函数
def main():
... # All your previously global code
main()# Slow:
import re
def slow_func():
for i in range(10000):
re.findall(regex, line) # Slow!
# Fast:
from re import findall
def fast_func():
for i in range(10000):
findall(regex, line) # Faster!f'{s} {t}' # Fast!
s + ' ' + t
' '.join((s, t))
'%s %s' % (s, t)
'{} {}'.format(s, t)
Template('$s $t').substitute(s=s, t=t) # Slow!