[python] How do you determine a processing time in Python?

I'm new to Python, and confused by the date/time documentation. I want to compute the time that it takes to perform a computation.

In java, I would write:

long timeBefore = System.currentTimeMillis();
doStuff();
long timeAfter = System.currentTimeMillis();
elapsed time = timeAfter - timeBefore;

I'm sure it's even easier in Python. Can anyone help?

python -m timeit -h

If all you want is the time between two points in code (and it seems that's what you want) I have written tic() toc() functions ala Matlab's implementation. The basic use case is:

tic()

''' some code that runs for an interesting amount of time '''

toc()

# OUTPUT:
# Elapsed time is: 32.42123 seconds

Super, incredibly easy to use, a sort of fire-and-forget kind of code. It's available on Github's Gist https://gist.github.com/tyleha/5174230

Building on and updating a number of earlier responses (thanks: SilentGhost, nosklo, Ramkumar) a simple portable timer would use timeit's default_timer():

>>> import timeit
>>> tic=timeit.default_timer()
>>> # Do Stuff
>>> toc=timeit.default_timer()
>>> toc - tic #elapsed time in seconds

This will return the elapsed wall clock (real) time, not CPU time. And as described in the timeit documentation chooses the most precise available real-world timer depending on the platform.

ALso, beginning with Python 3.3 this same functionality is available with the time.perf_counter performance counter. Under 3.3+ timeit.default_timer() refers to this new counter.

For more precise/complex performance calculations, timeit includes more sophisticated calls for automatically timing small code snippets including averaging run time over a defined set of repetitions.

For Python 3.3 and later time.process_time() is very nice:

import time

t = time.process_time()
#do some stuff
elapsed_time = time.process_time() - t

For some further information on how to determine the processing time, and a comparison of a few methods (some mentioned already in the answers of this post) - specifically, the difference between:

start = time.time()

versus the now obsolete (as of 3.3, time.clock() is deprecated)

start = time.clock()

see this other article on Stackoverflow here:

Python - time.clock() vs. time.time() - accuracy?

If nothing else, this will work good:

start = time.time()

... do something

elapsed = (time.time() - start)

I also got a requirement to calculate the process time of some code lines. So I tried the approved answer and I got this warning.

DeprecationWarning: time.clock has been deprecated in Python 3.3 and will be removed from Python 3.8: use time.perf_counter or time.process_time instead

So python will remove time.clock() from Python 3.8. You can see more about it from issue #13270. This warning suggest two function instead of time.clock(). In the documentation also mention about this warning in-detail in time.clock() section.

Deprecated since version 3.3, will be removed in version 3.8: The behaviour of this function depends on the platform: use perf_counter() or process_time() instead, depending on your requirements, to have a well defined behaviour.

Let's look at in-detail both functions.

• time.perf_counter()

Return the value (in fractional seconds) of a performance counter, i.e. a clock with the highest available resolution to measure a short duration. It does include time elapsed during sleep and is system-wide. The reference point of the returned value is undefined, so that only the difference between the results of consecutive calls is valid.

New in version 3.3.

So if you want it as nanoseconds, you can use time.perf_counter_ns() and if your code consist with time.sleep(secs), it will also count. Ex:-

import time


def func(x):
    time.sleep(5)
    return x * x


lst = [1, 2, 3]
tic = time.perf_counter()
print([func(x) for x in lst])
toc = time.perf_counter()
print(toc - tic)

# [1, 4, 9]
# 15.0041916 --> output including 5 seconds sleep time

• time.process_time()

Return the value (in fractional seconds) of the sum of the system and user CPU time of the current process. It does not include time elapsed during sleep. It is process-wide by definition. The reference point of the returned value is undefined, so that only the difference between the results of consecutive calls is valid.

New in version 3.3.

So if you want it as nanoseconds, you can use time.process_time_ns() and if your code consist with time.sleep(secs), it won't count. Ex:-

import time


def func(x):
    time.sleep(5)
    return x * x


lst = [1, 2, 3]
tic = time.process_time()
print([func(x) for x in lst])
toc = time.process_time()
print(toc - tic)

# [1, 4, 9]
# 0.0 --> output excluding 5 seconds sleep time

Please note both time.perf_counter_ns() and time.process_time_ns() come up with Python 3.7 onward.

You can implement two tic() and tac() functions, where tic() captures the time which it is called, and tac() prints the time difference since tic() was called. Here is a short implementation:

import time

_start_time = time.time()

def tic():
    global _start_time 
    _start_time = time.time()

def tac():
    t_sec = round(time.time() - _start_time)
    (t_min, t_sec) = divmod(t_sec,60)
    (t_hour,t_min) = divmod(t_min,60) 
    print('Time passed: {}hour:{}min:{}sec'.format(t_hour,t_min,t_sec))

Now in your code you can use it as:

tic()
do_some_stuff()
tac()

and it will, for example, output:

Time passed: 0hour:7min:26sec

See also:

• Python's datetime library: https://docs.python.org/2/library/datetime.html
• Python's time library: https://docs.python.org/2/library/time.html

Use timeit. http://docs.python.org/library/timeit.html