How to use timeit module

Question

I understand the concept of what timeit does but I am not sure how to implement it in my code   How can I compare two functions  say insertion sort and tim sort  with timeit

User · Answer

lets setup the same dictionary in each of the following and test the execution time.

The setup argument is basically setting up the dictionary

Number is to run the code 1000000 times. Not the setup but the stmt

When you run this you can see that index is way faster than get. You can run it multiple times to see.

The code basically tries to get the value of c in the dictionary.

import timeit

print('Getting value of C by index:', timeit.timeit(stmt="mydict['c']", setup="mydict={'a':5, 'b':6, 'c':7}", number=1000000))
print('Getting value of C by get:', timeit.timeit(stmt="mydict.get('c')", setup="mydict={'a':5, 'b':6, 'c':7}", number=1000000))

Here are my results, yours will differ.

by index: 0.20900007452246427

by get: 0.54841166886888

User · Answer

If you want to compare two blocks of code   functions quickly you could do   import timeit  start time   timeit default timer   func1   print timeit default timer   - start time   start time   timeit default timer   func2   print timeit default timer   - start time

User · Answer

The built-in timeit module works best from the IPython command line   To time functions from within a module   from timeit import default timer as timer import sys  def timefunc func   args    kwargs          Time a function        args          iterations 3      Usage example          timeit myfunc  1  b 2              try          iterations   kwargs pop  iterations       except KeyError          iterations   3     elapsed   sys maxsize     for   in range iterations           start   timer           result   func  args    kwargs          elapsed   min timer   - start  elapsed      print   Best of             9f   format iterations  func   name    elapsed        return result

User · Answer

simply pass your entire code as an argument of timeit   import timeit  print timeit timeit          limit   10000 prime list    i for i in range 2  limit 1    for prime in prime list      for elem in range prime 2  max prime list  1  prime           if elem in prime list              prime list remove elem           number 10

User · Answer

import timeit   def oct x      return x x   timeit Timer  for x in range 100   oct x     gc enable     timeit

User · Answer

This works great       python -m timeit -c    cat file name py

User · Answer

for me  this is the fastest way   import timeit def foo        print  here is my code to time        timeit timeit stmt foo  number 1234567

User · Answer

I ll let you in on a secret  the best way to use timeit is on the command line   On the command line  timeit does proper statistical analysis  it tells you how long the shortest run took  This is good because all error in timing is positive  So the shortest time has the least error in it  There s no way to get negative error because a computer can t ever compute faster than it can compute   So  the command-line interface      gt  python -m timeit  1   2  10000000 loops  best of 3  0 0468 usec per loop   That s quite simple  eh   You can set stuff up      gt  python -m timeit -s  x   range 10000    sum x   1000 loops  best of 3  543 usec per loop   which is useful  too   If you want multiple lines  you can either use the shell s automatic continuation or use separate arguments      gt  python -m timeit -s  x   range 10000   -s  y   range 100    sum x    min y   1000 loops  best of 3  554 usec per loop   That gives a setup of  x   range 1000  y   range 100    and times  sum x  min y      If you want to have longer scripts you might be tempted to move to timeit inside a Python script  I suggest avoiding that because the analysis and timing is simply better on the command line  Instead  I tend to make shell scripts    SETUP           lots of stuff       echo Minmod arr1  python -m timeit -s   SETUP   Minmod arr1     echo pure minmod arr1  python -m timeit -s   SETUP   pure minmod arr1     echo better minmod arr1  python -m timeit -s   SETUP   better minmod arr1         etc   This can take a bit longer due to the multiple initialisations  but normally that s not a big deal     But what if you want to use timeit inside your module   Well  the simple way is to do   def function                timeit Timer function  timeit number NUMBER    and that gives you cumulative  not minimum   time to run that number of times   To get a good analysis  use  repeat and take the minimum   min timeit Timer function  repeat repeat REPEATS  number NUMBER     You should normally combine this with functools partial instead of lambda      to lower overhead  Thus you could have something like   from functools import partial  def to time items            test items    1  2  3    100 times   timeit Timer partial to time  test items   repeat 3  1000     Divide by the number of repeats time taken   min times    1000     You can also do   timeit timeit        setup  from   main   import       number NUMBER    which would give you something closer to the interface from the command-line  but in a much less cool manner  The  from   main   import      lets you use code from your main module inside the artificial environment created by timeit   It s worth noting that this is a convenience wrapper for Timer      timeit      and so isn t particularly good at timing  I personally far prefer using Timer      repeat      as I ve shown above     Warnings  There are a few caveats with timeit that hold everywhere    Overhead is not accounted for  Say you want to time x    1  to find out how long addition takes    gt  gt  gt  python -m timeit -s  x   0   x    1  10000000 loops  best of 3  0 0476 usec per loop   Well  it s not 0 0476   s  You only know that it s less than that  All error is positive   So try and find pure overhead    gt  gt  gt  python -m timeit -s  x   0           100000000 loops  best of 3  0 014 usec per loop   That s a good 30  overhead just from timing  This can massively skew relative timings  But you only really cared about the adding timings  the look-up timings for x also need to be included in overhead    gt  gt  gt  python -m timeit -s  x   0   x  100000000 loops  best of 3  0 0166 usec per loop   The difference isn t much larger  but it s there  Mutating methods are dangerous    gt  gt  gt  python -m timeit -s  x    0  100000   while x  x pop    10000000 loops  best of 3  0 0436 usec per loop   But that s completely wrong  x is the empty list after the first iteration  You ll need to reinitialize    gt  gt  gt  python -m timeit  x    0  100000   while x  x pop    100 loops  best of 3  9 79 msec per loop   But then you have lots of overhead  Account for that separately    gt  gt  gt  python -m timeit  x    0  100000                     1000 loops  best of 3  261 usec per loop   Note that subtracting the overhead is reasonable here only because the overhead is a small-ish fraction of the time   For your example  it s worth noting that both Insertion Sort and Tim Sort have completely unusual timing behaviours for already-sorted lists  This means you will require a random shuffle between sorts if you want to avoid wrecking your timings

User · Answer

def gen prime x       multiples          results          for i in range 2  x 1           if i not in multiples              results append i              for j in range i i  x 1  i                   multiples append j       return results   import timeit                    start time   timeit default timer   gen prime 3000  print timeit default timer   - start time     start time   timeit default timer     gen prime 1001    print timeit default timer   - start time

User · Answer

You would create two functions and then run something similar to this  Notice  you want to choose the same number of execution run to compare apple to apple  This was tested under Python 3 7    Here is the code for ease of copying it     usr local bin python3 import timeit  def fibonacci n               Returns the n-th Fibonacci number              if n    0           result   0     elif n    1           result   1     else          result   fibonacci n-1    fibonacci n-2      return result  if   name         main         import timeit     t1   timeit Timer  fibonacci 13     from   main   import fibonacci       print  fibonacci ran   t1 timeit number 1000    milliseconds

User · Answer

I find the easiest way to use timeit is from the command line   Given test py   def InsertionSort        def TimSort          run timeit like this     python -mtimeit -s import test   test InsertionSort      python -mtimeit -s import test   test TimSort

User · Answer

If you want to use timeit in an interactive Python session  there are two convenient options    Use the IPython shell   It features the convenient  timeit special function   In  1   def f x               return x x           In  2    timeit for x in range 100   f x  100000 loops  best of 3  20 3 us per loop  In a standard Python interpreter  you can access functions and other names you defined earlier during the interactive session by importing them from   main   in the setup statement    gt  gt  gt  def f x           return x   x        gt  gt  gt  import timeit  gt  gt  gt  timeit repeat  for x in range 100   f x     from   main   import f                     number 100000   2 0640320777893066  2 0876040458679199  2 0520210266113281

User · Answer

The way timeit works is to run setup code once and then make repeated calls to a series of statements   So  if you want to test sorting  some care is required so that one pass at an in-place sort doesn t affect the next pass with already sorted data  that  of course  would make the Timsort really shine because it performs best when the data already partially ordered   Here is an example of how to set up a test for sorting   gt  gt  gt  import timeit   gt  gt  gt  setup       import random  random seed  slartibartfast   s    random random   for i in range 1000   timsort   list sort       gt  gt  gt  print min timeit Timer  a s     timsort a    setup setup  repeat 7  1000   0 334147930145  Note that the series of statements makes a fresh copy of the unsorted data on every pass  Also  note the timing technique of running the measurement suite seven times and keeping only the best time -- this can really help reduce measurement distortions due to other processes running on your system  Those are my tips for using timeit correctly   Hope this helps  -

User · Answer

Example of how to use Python REPL interpreter with function that accepts parameters    gt  gt  gt  import timeit                                                                                            gt  gt  gt  def naive func x                                                                                               a   0                                                                                                      for i in range a                                                                                               a    i                                                                                                 return a                                                                                             gt  gt  gt  def wrapper func   args    kwargs                                                                              def wrapper                                                                                                    return func  args    kwargs                                                                            return wrapper                                                                                       gt  gt  gt  wrapped   wrapper naive func  1 000                                                                      gt  gt  gt  timeit timeit wrapped  number 1 000 000                                                                0 4458435332577161

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