what is diffrence between number and repeat in python timeit?

repeat specifies the number of samples to take.

number specifies the number of times to repeat the code for each sample.

Internally there is a loop like this:

samples = []
for _ in range(repeat):
    # start timer
    for _ in range(number):
        do_work()
    # end timer
    samples.append(duration)

Whenever you do a statistical experiment (in this case a timing experiment) you want to repeat (or replicate) the experiment in order to be able to quantify uncertainty.

Now IPython's %timeit has two parameters:

• n, the number of loops (samples)
• r, the number of repeats (replications of the experiment)

One single experiment returns the timing of n loops (that means you will need to divide that value by n to obtain the average timing over all loops).

The experiment is repeated r times.

Uncertainty or uncontrolled variation is given by standard deviation over the r experiments.

This can be seen in this line in the source code (self.loops is the n):

timings =  [dt / self.loops for dt in all_runs]

From https://github.com/ipython/ipython/blob/master/IPython/core/magics/execution.py:

class TimeitResult(object):
    """
    Object returned by the timeit magic with info about the run.
    Contains the following attributes :
    loops: (int) number of loops done per measurement
    repeat: (int) number of times the measurement has been repeated
    best: (float) best execution time / number
    all_runs: (list of float) execution time of each run (in s)
    compile_time: (float) time of statement compilation (s)
    """
    def __init__(self, loops, repeat, best, worst, all_runs, compile_time, precision):
        self.loops = loops
        self.repeat = repeat
        self.best = best
        self.worst = worst
        self.all_runs = all_runs
        self.compile_time = compile_time
        self._precision = precision
        self.timings = [ dt / self.loops for dt in all_runs] 

@property
def average(self):
    return math.fsum(self.timings) / len(self.timings)

@property
def stdev(self):
    mean = self.average
    return (math.fsum([(x - mean) ** 2 for x in self.timings]) / len(self.timings)) ** 0.5

Default n and r

Note that the default number of loops is one million and the default repeat is 7, so I would say for all daily needs it is convenient to use %timeit specifying smaller values, otherwise the timing might take too long/use up too many resources.

Should I use %time instead?

Still, even for a quick timing I wouldn't use the basic %time (just one run) because the timing of a single execution/run could be influenced by many contingent factors.