How do I get time of a Python program's execution?


I have a command line program in Python that takes a while to finish. I want to know the exact time it takes to finish running.

I’ve looked at the timeit module, but it seems it’s only for small snippets of code. I want to time the whole program.

Asked By: john2x



In Linux or Unix:

$ time python

In Windows, see this StackOverflow question: How do I measure execution time of a command on the Windows command line?

For more verbose output,

$ time -v python
    Command being timed: "python3"
    User time (seconds): 0.08
    System time (seconds): 0.02
    Percent of CPU this job got: 98%
    Elapsed (wall clock) time (h:mm:ss or m:ss): 0:00.10
    Average shared text size (kbytes): 0
    Average unshared data size (kbytes): 0
    Average stack size (kbytes): 0
    Average total size (kbytes): 0
    Maximum resident set size (kbytes): 9480
    Average resident set size (kbytes): 0
    Major (requiring I/O) page faults: 0
    Minor (reclaiming a frame) page faults: 1114
    Voluntary context switches: 0
    Involuntary context switches: 22
    Swaps: 0
    File system inputs: 0
    File system outputs: 0
    Socket messages sent: 0
    Socket messages received: 0
    Signals delivered: 0
    Page size (bytes): 4096
    Exit status: 0
Answered By: steveha

The simplest way in Python:

import time
start_time = time.time()
print("--- %s seconds ---" % (time.time() - start_time))

This assumes that your program takes at least a tenth of second to run.


--- 0.764891862869 seconds ---
Answered By: rogeriopvl
import time

start_time = time.clock()
print(time.clock() - start_time, "seconds")

time.clock() returns the processor time, which allows us to calculate only the time used by this process (on Unix anyway). The documentation says "in any case, this is the function to use for benchmarking Python or timing algorithms"

Answered By: newacct

I put this module into my own site-packages directory, and just insert import timing at the top of my module:

import atexit
from time import clock

def secondsToStr(t):
    return "%d:%02d:%02d.%03d" % 
        reduce(lambda ll,b : divmod(ll[0],b) + ll[1:],

line = "="*40
def log(s, elapsed=None):
    print line
    print secondsToStr(clock()), '-', s
    if elapsed:
        print "Elapsed time:", elapsed
    print line

def endlog():
    end = clock()
    elapsed = end-start
    log("End Program", secondsToStr(elapsed))

def now():
    return secondsToStr(clock())

start = clock()
log("Start Program")

I can also call timing.log from within my program if there are significant stages within the program I want to show. But just including import timing will print the start and end times, and overall elapsed time. (Forgive my obscure secondsToStr function, it just formats a floating point number of seconds to hh:mm:ss.sss form.)

Note: A Python 3 version of the above code can be found here or here.

Answered By: PaulMcG

I really like Paul McGuire’s answer, but I use Python 3. So for those who are interested: here’s a modification of his answer that works with Python 3 on *nix (I imagine, under Windows, that clock() should be used instead of time()):

import atexit
from time import time, strftime, localtime
from datetime import timedelta

def secondsToStr(elapsed=None):
    if elapsed is None:
        return strftime("%Y-%m-%d %H:%M:%S", localtime())
        return str(timedelta(seconds=elapsed))

def log(s, elapsed=None):
    line = "="*40
    print(secondsToStr(), '-', s)
    if elapsed:
        print("Elapsed time:", elapsed)

def endlog():
    end = time()
    elapsed = end-start
    log("End Program", secondsToStr(elapsed))

start = time()
log("Start Program")

If you find this useful, you should still up-vote his answer instead of this one, as he did most of the work ;).

Answered By: Nicojo

You can use the Python profiler cProfile to measure CPU time and additionally how much time is spent inside each function and how many times each function is called. This is very useful if you want to improve performance of your script without knowing where to start. This answer to another Stack Overflow question is pretty good. It’s always good to have a look in the documentation too.

Here’s an example how to profile a script using cProfile from a command line:

$ python -m cProfile

1007 function calls in 0.061 CPU seconds

Ordered by: standard name
ncalls  tottime  percall  cumtime  percall filename:lineno(function)
    1    0.000    0.000    0.061    0.061 <string>:1(<module>)
 1000    0.051    0.000    0.051    0.000<lambda>)
    1    0.005    0.005    0.061    0.061<module>)
    1    0.000    0.000    0.061    0.061 {execfile}
    1    0.002    0.002    0.053    0.053 {map}
    1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler objects}
    1    0.000    0.000    0.000    0.000 {range}
    1    0.003    0.003    0.003    0.003 {sum}
Answered By: jacwah

I like the output the datetime module provides, where time delta objects show days, hours, minutes, etc. as necessary in a human-readable way.

For example:

from datetime import datetime
start_time =
# do your work here
end_time =
print('Duration: {}'.format(end_time - start_time))

Sample output e.g.

Duration: 0:00:08.309267


Duration: 1 day, 1:51:24.269711

As J.F. Sebastian mentioned, this approach might encounter some tricky cases with local time, so it’s safer to use:

import time
from datetime import timedelta
start_time = time.monotonic()
end_time = time.monotonic()
print(timedelta(seconds=end_time - start_time))
Answered By: metakermit

There is a timeit module which can be used to time the execution times of Python code.

It has detailed documentation and examples in Python documentation, 26.6. timeit — Measure execution time of small code snippets.

Answered By: Alfie

I liked Paul McGuire’s answer too and came up with a context manager form which suited my needs more.

import datetime as dt
import timeit

class TimingManager(object):
    """Context Manager used with the statement 'with' to time some execution.


    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):

        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: {}',

    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))
Answered By: Gall

I’ve looked at the timeit module, but it seems it’s only for small snippets of code. I want to time the whole program.

$ python -mtimeit -n1 -r1 -t -s "from your_module import main" "main()"

It runs your_module.main() function one time and print the elapsed time using time.time() function as a timer.

To emulate /usr/bin/time in Python see Python subprocess with /usr/bin/time: how to capture timing info but ignore all other output?.

To measure CPU time (e.g., don’t include time during time.sleep()) for each function, you could use profile module (cProfile on Python 2):

$ python3 -mprofile

You could pass -p to timeit command above if you want to use the same timer as profile module uses.

See How can you profile a Python script?

Answered By: jfs

This is Paul McGuire’s answer that works for me. Just in case someone was having trouble running that one.

import atexit
from time import clock

def reduce(function, iterable, initializer=None):
    it = iter(iterable)
    if initializer is None:
        value = next(it)
        value = initializer
    for element in it:
        value = function(value, element)
    return value

def secondsToStr(t):
    return "%d:%02d:%02d.%03d" % 
        reduce(lambda ll,b : divmod(ll[0],b) + ll[1:],

line = "="*40
def log(s, elapsed=None):
    print (line)
    print (secondsToStr(clock()), '-', s)
    if elapsed:
        print ("Elapsed time:", elapsed)
    print (line)

def endlog():
    end = clock()
    elapsed = end-start
    log("End Program", secondsToStr(elapsed))

def now():
    return secondsToStr(clock())

def main():
    start = clock()
    log("Start Program")

Call timing.main() from your program after importing the file.

Answered By: Saurabh Rana

In IPython, “timeit” any script:

def foo():
timeit foo()
Answered By: B.Kocis
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)
Answered By: Qina Yan


Deprecated since version 3.3: The behavior of this function depends
on the platform: use perf_counter() or process_time() instead,
depending on your requirements, to have a well-defined behavior.


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


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.

start = time.process_time()
... do something
elapsed = (time.process_time() - start)
Answered By: Yas

The following snippet prints elapsed time in a nice human readable <HH:MM:SS> format.

import time
from datetime import timedelta

start_time = time.time()

# Perform lots of computations.

elapsed_time_secs = time.time() - start_time

msg = "Execution took: %s secs (Wall clock time)" % timedelta(seconds=round(elapsed_time_secs))

Answered By: Sandeep

To use metakermit’s updated answer for Python 2.7, you will require the monotonic package.

The code would then be as follows:

from datetime import timedelta
from monotonic import monotonic

start_time = monotonic()
end_time = monotonic()
print(timedelta(seconds=end_time - start_time))
Answered By: H0R5E

The time of a Python program’s execution measure could be inconsistent depending on:

  • Same program can be evaluated using different algorithms
  • Running time varies between algorithms
  • Running time varies between implementations
  • Running time varies between computers
  • Running time is not predictable based on small inputs

This is because the most effective way is using the “Order of Growth” and learn the Big “O” notation to do it properly.

Anyway, you can try to evaluate the performance of any Python program in specific machine counting steps per second using this simple algorithm:
adapt this to the program you want to evaluate

import time

now = time.time()
future = now + 10
step = 4 # Why 4 steps? Because until here already four operations executed
while time.time() < future:
    step += 3 # Why 3 again? Because a while loop executes one comparison and one plus equal statement
step += 4 # Why 3 more? Because one comparison starting while when time is over plus the final assignment of step + 1 and print statement
print(str(int(step / 10)) + " steps per second")
Answered By: Manu

Just use the timeit module. It works with both Python 2 and Python 3.

import timeit

start = timeit.default_timer()

# All the program statements
stop = timeit.default_timer()
execution_time = stop - start

print("Program Executed in "+str(execution_time)) # It returns time in seconds

It returns in seconds and you can have your execution time. It is simple, but you should write these in thew main function which starts program execution. If you want to get the execution time even when you get an error then take your parameter “Start” to it and calculate there like:

def sample_function(start,**kwargs):
         # Your statements
         # except statements run when your statements raise an exception
         stop = timeit.default_timer()
         execution_time = stop - start
         print("Program executed in " + str(execution_time))
Answered By: Ravi Kumar

Timeit is a class in Python used to calculate the execution time of small blocks of code.

Default_timer is a method in this class which is used to measure the wall clock timing, not CPU execution time. Thus other process execution might interfere with this. Thus it is useful for small blocks of code.

A sample of the code is as follows:

from timeit import default_timer as timer

start= timer()

# Some logic

end = timer()

print("Time taken:", end-start)
Answered By: Utkarsh Dhawan

Use line_profiler.

line_profiler will profile the time individual lines of code take to execute. The profiler is implemented in C via Cython in order to reduce the overhead of profiling.

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)

The results will be:

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))]
Answered By: Yu Jiaao

For the data folks using Jupyter Notebook

In a cell, you can use Jupyter’s %%time magic command to measure the execution time:

[ x**2 for x in range(10000)]


CPU times: user 4.54 ms, sys: 0 ns, total: 4.54 ms
Wall time: 4.12 ms

This will only capture the execution time of a particular cell. If you’d like to capture the execution time of the whole notebook (i.e. program), you can create a new notebook in the same directory and in the new notebook execute all cells:

Suppose the notebook above is called example_notebook.ipynb. In a new notebook within the same directory:

# 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


IPython CPU timings (estimated):
  User   :       0.00 s.
  System :       0.00 s.
Wall time:       0.00 s.
Answered By: Matt

I used a very simple function to time a part of code execution:

import time
def timing():
    start_time = time.time()
    return lambda x: print("[{:.2f}s] {}".format(time.time() - start_time, x))

And to use it, just call it before the code to measure to retrieve function timing, and then call the function after the code with comments. The time will appear in front of the comments. For example:

t = timing()
train = pd.read_csv('train.csv',
                            'id': str,
                            'vendor_id': str,
                            'pickup_datetime': str,
                            'dropoff_datetime': str,
                            'passenger_count': int,
                            'pickup_longitude': np.float64,
                            'pickup_latitude': np.float64,
                            'dropoff_longitude': np.float64,
                            'dropoff_latitude': np.float64,
                            'store_and_fwd_flag': str,
                            'trip_duration': int,
                        parse_dates = ['pickup_datetime', 'dropoff_datetime'],
t("Loaded {} rows data from 'train'".format(len(train)))

Then the output will look like this:

[9.35s] Loaded 1458644 rows data from 'train'
Answered By: Tao Wang

If you want to measure time in microseconds, then you can use the following version, based completely on the answers of Paul McGuire and Nicojo – it’s Python 3 code. I’ve also added some colour to it:

import atexit
from time import time
from datetime import timedelta, datetime

def seconds_to_str(elapsed=None):
    if elapsed is None:
        return"%Y-%m-%d %H:%M:%S.%f")
        return str(timedelta(seconds=elapsed))

def log(txt, elapsed=None):
    colour_cyan = '33[36m'
    colour_reset = '33[0;0;39m'
    colour_red = '33[31m'
    print('n ' + colour_cyan + '  [TIMING]> [' + seconds_to_str() + '] ----> ' + txt + 'n' + colour_reset)
    if elapsed:
        print("n " + colour_red + " [TIMING]> Elapsed time ==> " + elapsed + "n" + colour_reset)

def end_log():
    end = time()
    elapsed = end-start
    log("End Program", seconds_to_str(elapsed))

start = time()
log("Start Program")

log() => function that prints out the timing information.

txt ==> first argument to log, and its string to mark timing.

atexit ==> Python module to register functions that you can call when the program exits.

Answered By: Rui Carvalho

You do this simply in Python. There is no need to make it complicated.

import time

start = time.localtime()
end = time.localtime()
"""Total execution time in minutes$ """
print(end.tm_min - start.tm_min)
"""Total execution time in seconds$ """
print(end.tm_sec - start.tm_sec)
Answered By: Mitul Panchal

This is the simplest way to get the elapsed time for the program:

Write the following code at the end of your program.

import time
Answered By: Kushal Ghosh

I was having the same problem in many places, so I created a convenience package horology. You can install it with pip install horology and then do it in the elegant way:

from horology import Timing

with Timing(name='Important calculations: '):

will output:

Important calculations: 12.43 ms

Or even simpler (if you have one function):

from horology import timed

def main():

will output:

main: 7.12 h

It takes care of units and rounding. It works with python 3.6 or newer.

Answered By: hans

Later answer, but I use the built-in timeit:

import timeit
code_to_test = """
a = range(100000)
b = []
for i in a:
elapsed_time = timeit.timeit(code_to_test, number=500)
# 10.159821493085474

  • Wrap all your code, including any imports you may have, inside code_to_test.
  • number argument specifies the amount of times the code should repeat.
  • Demo
Answered By: Pedro Lobito

Similar to the response from @rogeriopvl I added a slight modification to convert to hour minute seconds using the same library for long running jobs.

import time
start_time = time.time()
seconds = time.time() - start_time
print('Time Taken:', time.strftime("%H:%M:%S",time.gmtime(seconds)))

Sample Output

Time Taken: 00:00:08
Answered By: user 923227

First, install humanfriendly package by opening Command Prompt (CMD) as administrator and type there –
pip install humanfriendly


from humanfriendly import format_timespan
import time
begin_time = time.time()
# Put your code here
end_time = time.time() - begin_time
print("Total execution time: ", format_timespan(end_time))


enter image description here

Answered By: Amar Kumar

I tried and found time difference using the following scripts.

import time

start_time = time.perf_counter()
[main code here]
print (time.perf_counter() - start_time, "seconds")
Answered By: Hafez Ahmad

For functions, I suggest using this simple decorator I created.

def timeit(method):
    def timed(*args, **kwargs):
        ts = time.time()
        result = method(*args, **kwargs)
        te = time.time()
        if 'log_time' in kwargs:
            name = kwargs.get('log_name', method.__name__.upper())
            kwargs['log_time'][name] = int((te - ts) * 1000)
            print('%r  %2.22f ms' % (method.__name__, (te - ts) * 1000))
        return result
    return timed

def foo():

# foo()
# 'foo'  0.000953 ms
Answered By: Nikita Tonkoskur

Following this answer created a simple but convenient instrument.

import time
from datetime import timedelta

def start_time_measure(message=None):
    if message:
    return time.monotonic()

def end_time_measure(start_time, print_prefix=None):
    end_time = time.monotonic()
    if print_prefix:
        print(print_prefix + str(timedelta(seconds=end_time - start_time)))
    return end_time


total_start_time = start_time_measure()    
start_time = start_time_measure('Doing something...')
# Do something
end_time_measure(start_time, 'Done in: ')
start_time = start_time_measure('Doing something else...')
# Do something else
end_time_measure(start_time, 'Done in: ')
end_time_measure(total_start_time, 'Total time: ')

The output:

Doing something...
Done in: 0:00:01.218000
Doing something else...
Done in: 0:00:01.313000
Total time: 0:00:02.672000
Answered By: Nick Legend

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

import time
start_time = time.perf_counter ()
for x in range(1, 100):
end_time = time.perf_counter ()
print(end_time - start_time, "seconds")
Answered By: Md. Imrul Kayes

I define the following Python decorator:

def profile(fct):
  def wrapper(*args, **kw):
    start_time = time.time()
    ret = fct(*args, **kw)
    print("{} {} {} return {} in {} seconds".format(args[0].__class__.__name__,
                                                    time.time() - start_time))
    return ret
  return wrapper

and use it on functions or class/methods:

def main()
Answered By: Nicolargo

I use tic and toc from ttictoc.

pip install ttictoc

Then you can use in your script:

from ttictoc import tic,toc

# foo()

Answered By: Sasha Vasserfirer

By default, Linux or Unix system (tested on macOS) comes with the time command on the terminal that you can use to run the Python script and get the real, user, sys time information for the execution of the running script.

However, the default output isn’t very clear (at least for me), and the default time command doesn’t even take any options as arguments to format the output. That’s because there are two versions of time – one is built into bash that provides just the minimal version and another one is located on /usr/bin/time.

The /usr/bin/time command accepts additional arguments like -al, -h, -p, and -o. My favorite is -p which shows the output in a new line like the following:

real 2.18
user 17.92
sys 2.71

time.clock has been deprecated in Python 3.3 and was removed from Python 3.8

You should use time.perf_counter or time.process_time instead.

time.perf_counter returns 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 two calls is valid.

time.process_time: time.process_time returns 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 two calls is valid.

You can see this documentation regarding the usage. Also, see the following example:

import time
s_time = time.perf_counter()

// call your function here 

e_time = time.perf_counter()
print(e_time - s_time, "seconds")
Answered By: S M Samnoon Abrar
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