breaking-point.py helps to find a size of input data where one function starts outperform another function. It is a convenient way to compare different algorithms for a single task.

pip install breaking-point

from breaking_point import find_breaking_point

find_breaking_point(f1, f2, input_generator, start=1, step=1, limit=1000000, trial_count=1000, repeat_count=3)

there

• f1, f2 - functions to compare.
• inpurt_generator - function that takes n argument (size of input on current iteration) and returns input data for f1 and f2. Return value should be a tuple with first element - list of non-keyworded arguments and second element - dict of keyword arguments.
• start - initial input data size.
• step - step of iteration.
• limit - maximum amount of input data. If breaking point was not found until limit was reached - iteration stops.
• trial_count - number of executions with each input data size.
• repeat_count - repeat trial several times and use average performance result.

Function returns n0 - size of input data for which f2(n0) executed faster than f1(n0) or None if reaches limit.

See example.py.

MIT