Python从门到精通(四):性能监控（python监控cpu使用率）

Python从门到精通(四):性能监控（python监控cpu使用率）

经过上述几章基础基本全覆盖了，可以写一些简单的程序。本章比较简单，就介绍下如何测试Python程序的性能。但这些方式一般适用于开发阶段，因为线上的系统往往比较复杂。

一、CPU

1.1、用unix函数测试

(venv) MacBook:chapter14 liudong$ time python profile_test.py __main__.countdown time spend: 0.446525065scounting time spend: 0.671478864smath.sqrt time spend: 0.063568925ssqrt time spend: 0.043364856000000174smath.sqrt time spend: 0.6419396199999998ssqrt time spend: 0.42504095399999997sreal 0m2.337suser 0m2.318ssys 0m0.016s

1.2、使用cProfile模块

需要先安装 pip install cprofiler

(venv) MacBook:chapter14 liudong$ python -m cProfile profile_test.py __main__.countdown time spend: 0.450556833scounting time spend: 0.726764442smath.sqrt time spend: 0.18848818400000011ssqrt time spend: 0.15792459199999986smath.sqrt time spend: 1.8039463000000002ssqrt time spend: 1.5490455310000004s 22000655 function calls (22000645 primitive calls) in 3.597 seconds Ordered by: standard name ncalls tottime percall cumtime percall filename:lineno(function) 3/2 0.000 0.000 0.002 0.001 :1002(_find_and_load) 3 0.000 0.000 0.000 0.000 :112(release) 3 0.000 0.000 0.000 0.000 :152(__init__) 3 0.000 0.000 0.000 0.000 :156(__enter__) 3 0.000 0.000 0.000 0.000 :160(__exit__) 3 0.000 0.000 0.000 0.000 :166(_get_module_lock) 3 0.000 0.000 0.000 0.000 :185(cb) 5/3 0.000 0.000 0.001 0.000 :220(_call_with_frames_removed) 37 0.000 0.000 0.000 0.000 :231(_verbose_message) 1 0.000 0.000 0.000 0.000 :241(_requires_builtin_wrapper) 1 0.000 0.000 0.000 0.000 :35(_new_module) 3 0.000 0.000 0.000 0.000 :351(__init__) ncalls：相应代码/函数被执行的次数tottime: 相应代码/函数被执行的总执行时间，不包括命令调用等percall：tottime/ncallscumtime: 相应代码/函数被执行的总执行时间,包括命令调用等percall：cumtime/ncalls

def fib_seq(n): res = [] if n > 0: res.extend(fib_seq(n-1)) res.append(fib(n)) return resimport cProfilecProfile.run('fib_seq(30)')

1.3、使用line_profiler模块

需要安装pip install line_profiler

(venv) MacBook:chapter16 liudong$ kernprof -l -v fib_test_3.pyWrote profile results to fib_test_3.py.lprofTimer unit: 1e-06 sTotal time: 6.80702 sFile: fib_test_3.pyFunction: fib at line 1Line # Hits Time Per Hit % Time Line Contents============================================================== 1 @profile 2 def fib(n): 3 7049123 1839146.0 0.3 27.0 if n == 0: 4 1346269 298856.0 0.2 4.4 return 0 5 5702854 1450236.0 0.3 21.3 elif n == 1: 6 2178308 486185.0 0.2 7.1 return 1 7 else: 8 3524546 2732599.0 0.8 40.1 return fib(n-1) + fib(n-2)

@profiledef fib_seq(n): res = [] if n > 0: res.extend(fib_seq(n-1)) res.append(fib(n)) return resif __name__ == "__main__": fib_seq(30)

1.4、自定义工具函数

import timefrom functools import wrapsdef time_use(func): """ Decorator that reports the execution time. :param func: :return: """ @wraps(func) def wrapper(*args, **kwargs): start = time.time() result = func(*args, **kwargs) end = time.time() print(f'func name is: {func.__name__}, time use: {end - start} s') return result return wrapper

1.5、自定义性能函数

import timefrom functools import wrapsdef time_this(func): @wraps(func) def wrapper(*args, **kwargs): start = time.perf_counter() r = func(*args, **kwargs) end = time.perf_counter() print(f'{func.__module__}.{func.__name__} time spend: {end - start}s') return r return wrapper#装饰器@time_thisdef countdown(n): while n > 0: n -= 1countdown(10000000)from contextlib import contextmanager@contextmanagerdef time_block(label): start = time.perf_counter() try: yield finally: end = time.perf_counter() print(f'{label} time spend: {end - start}s')with time_block('counting'): n = 10000000 while n > 0: n -= 1from timeit import timeitprint(f"math.sqrt time spend: {timeit('math.sqrt(2)', 'import math')}s")print(f"sqrt time spend: {timeit('sqrt(2)', 'from math import sqrt')}s")print(f"math.sqrt time spend: {timeit('math.sqrt(2)', 'import math', number=10000000)}s")print(f"sqrt time spend: {timeit('sqrt(2)', 'from math import sqrt', number=10000000)}s")from functools import wrapsdef time_this(func): @wraps(func) def wrapper(*args, **kwargs): start = time.process_time() r = func(*args, **kwargs) end = time.process_time() print(f'{func.__module__}.{func.__name__} : {end - start}') return r return wrapper

/Users/liudong/PycharmProjects/pythonProject/venv/bin/python /Users/liudong/PycharmProjects/pythonProject/app/chapter14/profile_test.py__main__.countdown time spend: 0.466810053scounting time spend: 0.911959559smath.sqrt time spend: 0.0725984340000001ssqrt time spend: 0.04869681800000003smath.sqrt time spend: 0.6943450900000001ssqrt time spend: 0.48345576300000026s进程已结束，退出代码为 0

二、内存

2.1、内存使用memory_profiler模块

需要安装memory_profiler

(venv) MacBook:chapter16 liudong$ python -m memory_profiler mem_pro_exp.py Filename: mem_pro_exp.pyLine # Mem usage Increment Occurrences Line Contents============================================================= 1 15.805 MiB 15.805 MiB 1 @profile 2 def my_func(): 3 23.438 MiB 7.633 MiB 1 a = [1] * (10 ** 6) 4 176.031 MiB 152.594 MiB 1 b = [2] * (2 * 10 ** 7) 5 176.031 MiB 0.000 MiB 1 del b 6 176.031 MiB 0.000 MiB 1 return a

@profiledef my_func(): a = [1] * (10 ** 6) b = [2] * (2 * 10 ** 7) del b return aif __name__ == '__main__': my_func()

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