我有一个Python命令行程序,需要一段时间才能完成。我想知道完成跑步所需的确切时间。
我看过timeit模块,但它似乎只适用于小代码片段。我想给整个节目计时。
我有一个Python命令行程序,需要一段时间才能完成。我想知道完成跑步所需的确切时间。
我看过timeit模块,但它似乎只适用于小代码片段。我想给整个节目计时。
当前回答
对于使用Jupyter笔记本的数据人员
在单元格中,可以使用Jupyter的%%time魔术命令来测量执行时间:
%%time
[ x**2 for x in range(10000)]
输出
CPU times: user 4.54 ms, sys: 0 ns, total: 4.54 ms
Wall time: 4.12 ms
这将仅捕获特定单元的执行时间。如果您想捕获整个笔记本(即程序)的执行时间,可以在同一目录中创建一个新笔记本,并在新笔记本中执行所有单元格:
假设上面的笔记本名为example_notebook.ipynb。在同一目录中的新笔记本中:
# Convert your notebook to a .py script:
!jupyter nbconvert --to script example_notebook.ipynb
# Run the example_notebook with -t flag for time
%run -t example_notebook
输出
IPython CPU timings (estimated):
User : 0.00 s.
System : 0.00 s.
Wall time: 0.00 s.
其他回答
这是获取程序运行时间的最简单方法:
在程序末尾编写以下代码。
import time
print(time.clock())
对于使用Jupyter笔记本的数据人员
在单元格中,可以使用Jupyter的%%time魔术命令来测量执行时间:
%%time
[ x**2 for x in range(10000)]
输出
CPU times: user 4.54 ms, sys: 0 ns, total: 4.54 ms
Wall time: 4.12 ms
这将仅捕获特定单元的执行时间。如果您想捕获整个笔记本(即程序)的执行时间,可以在同一目录中创建一个新笔记本,并在新笔记本中执行所有单元格:
假设上面的笔记本名为example_notebook.ipynb。在同一目录中的新笔记本中:
# Convert your notebook to a .py script:
!jupyter nbconvert --to script example_notebook.ipynb
# Run the example_notebook with -t flag for time
%run -t example_notebook
输出
IPython CPU timings (estimated):
User : 0.00 s.
System : 0.00 s.
Wall time: 0.00 s.
from time import time
start_time = time()
...
end_time = time()
time_taken = end_time - start_time # time_taken is in seconds
hours, rest = divmod(time_taken,3600)
minutes, seconds = divmod(rest, 60)
我也喜欢Paul McGuire的回答,并提出了一个更符合我需求的上下文管理器表单。
import datetime as dt
import timeit
class TimingManager(object):
"""Context Manager used with the statement 'with' to time some execution.
Example:
with TimingManager() as t:
# Code to time
"""
clock = timeit.default_timer
def __enter__(self):
"""
"""
self.start = self.clock()
self.log('\n=> Start Timing: {}')
return self
def __exit__(self, exc_type, exc_val, exc_tb):
"""
"""
self.endlog()
return False
def log(self, s, elapsed=None):
"""Log current time and elapsed time if present.
:param s: Text to display, use '{}' to format the text with
the current time.
:param elapsed: Elapsed time to display. Dafault: None, no display.
"""
print s.format(self._secondsToStr(self.clock()))
if(elapsed is not None):
print 'Elapsed time: {}\n'.format(elapsed)
def endlog(self):
"""Log time for the end of execution with elapsed time.
"""
self.log('=> End Timing: {}', self.now())
def now(self):
"""Return current elapsed time as hh:mm:ss string.
:return: String.
"""
return str(dt.timedelta(seconds = self.clock() - self.start))
def _secondsToStr(self, sec):
"""Convert timestamp to h:mm:ss string.
:param sec: Timestamp.
"""
return str(dt.datetime.fromtimestamp(sec))
使用line_profiler。
line_profiler将描述单个代码行执行所需的时间。分析器通过Cython在C语言中实现,以减少分析开销。
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()
结果将是:
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))]