我试图找出如何运行Python line_profiler以逐行执行时间，以this question的答案中给出的格式。
我安装了模块并调用了它的LineProfiler对象，但是我得到的输出只是一次，而不是逐行汇总。
有什么想法吗？此外，如何获得任何函数之外的numbers = [random.randint(1,100) for i in range(1000)]行的时间？
from line_profiler import LineProfiler
import random
def do_stuff(numbers):
s = sum(numbers)
l = [numbers[i]/43 for i in range(len(numbers))]
m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
numbers = [random.randint(1,100) for i in range(1000)]
profile = LineProfiler(do_stuff(numbers))
profile.print_stats()
[] Timer unit: 3.20721e-07 s
答案 0 :(得分：29)
line_profiler测试用例（在GitHub上找到）有一个如何从Python脚本中生成配置文件数据的示例。您必须包装要分析的函数，然后调用包装器传递任何所需的函数参数。
from line_profiler import LineProfiler
import random
def do_stuff(numbers):
s = sum(numbers)
l = [numbers[i]/43 for i in range(len(numbers))]
m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
numbers = [random.randint(1,100) for i in range(1000)]
lp = LineProfiler()
lp_wrapper = lp(do_stuff)
lp_wrapper(numbers)
lp.print_stats()
输出：
Timer unit: 1e-06 s
Total time: 0.000649 s
File: <ipython-input-2-2e060b054fea>
Function: do_stuff at line 4
Line # Hits Time Per Hit % Time Line Contents
==============================================================
4 def do_stuff(numbers):
5 1 10 10.0 1.5 s = sum(numbers)
6 1 186 186.0 28.7 l = [numbers[i]/43 for i in range(len(numbers))]
7 1 453 453.0 69.8 m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
向个人资料添加附加功能
此外，您还可以添加要分析的其他功能。例如，如果您有第二个调用函数并且只包装调用函数，那么您只能看到调用的配置文件结果功能
from line_profiler import LineProfiler
import random
def do_other_stuff(numbers):
s = sum(numbers)
def do_stuff(numbers):
do_other_stuff(numbers)
l = [numbers[i]/43 for i in range(len(numbers))]
m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
numbers = [random.randint(1,100) for i in range(1000)]
lp = LineProfiler()
lp_wrapper = lp(do_stuff)
lp_wrapper(numbers)
lp.print_stats()
以上只会为调用函数生成以下配置文件输出：
Timer unit: 1e-06 s
Total time: 0.000773 s
File: <ipython-input-3-ec0394d0a501>
Function: do_stuff at line 7
Line # Hits Time Per Hit % Time Line Contents
==============================================================
7 def do_stuff(numbers):
8 1 11 11.0 1.4 do_other_stuff(numbers)
9 1 236 236.0 30.5 l = [numbers[i]/43 for i in range(len(numbers))]
10 1 526 526.0 68.0 m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
在这种情况下，您可以将其他名为的函数添加到配置文件中，如下所示：
from line_profiler import LineProfiler
import random
def do_other_stuff(numbers):
s = sum(numbers)
def do_stuff(numbers):
do_other_stuff(numbers)
l = [numbers[i]/43 for i in range(len(numbers))]
m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
numbers = [random.randint(1,100) for i in range(1000)]
lp = LineProfiler()
lp.add_function(do_other_stuff) # add additional function to profile
lp_wrapper = lp(do_stuff)
lp_wrapper(numbers)
lp.print_stats()
输出：
Timer unit: 1e-06 s
Total time: 9e-06 s
File: <ipython-input-4-dae73707787c>
Function: do_other_stuff at line 4
Line # Hits Time Per Hit % Time Line Contents
==============================================================
4 def do_other_stuff(numbers):
5 1 9 9.0 100.0 s = sum(numbers)
Total time: 0.000694 s
File: <ipython-input-4-dae73707787c>
Function: do_stuff at line 7
Line # Hits Time Per Hit % Time Line Contents
==============================================================
7 def do_stuff(numbers):
8 1 12 12.0 1.7 do_other_stuff(numbers)
9 1 208 208.0 30.0 l = [numbers[i]/43 for i in range(len(numbers))]
10 1 474 474.0 68.3 m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
注意：以这种方式向配置文件添加功能不需要更改配置文件代码（即，无需添加@profile装饰器）。
答案 1 :(得分：4)
在您的脚本中，您可以使用@profile
修饰您想要分析的任何函数
您希望使用do_stuff修饰@profile函数，然后运行
kernprof.py -v -l script_to_profile.py
将带注释的输出打印到终端。该配置文件也将写入script_to_profile.py.lprof，您可以稍后使用
python -m line_profiler script_to_profile.py.lprof