time_algo_exec.py

# Author : Bosolindo Edhiengene Roger
# email  : rogerbosolinndo34@gmail.com

# This module contains codes about algorithms complexity as to estimate the time an algorithm
# will take to be run. Why do we find it usable ? Because, knowing this kind of information tells
# you if your code or solution is efficient or not ; it helps you not to fall trying to run such a code.


def calc(operations: dict) -> float:
    """
    calc(operation: dict) -> float:
    This function aims to calculate how long an algorithm take, knowing only primary operations
    :param operations: A dictionary where the values are tuples, consisting of the number of times
                       an operation is performed and its execution time, and the key should
                       preferably be the name of the operation for better clarity and usability.
    :return: the time needed for the execution of this algorithm(if format is okey for "operations") or 0
    #>>> operations1 = {"addition":(2, 0.1), "subtraction":(1, 0.2)}
    #>>> operations2 = {"addition":(2, 0.1), "subtraction":(1, 0.2, 1)}
    #>>> calc(operations1)
    #>>> 0.4
    #>>> calc(operations2)
    #>>> 0
    """
    temps = 0
    for couple in operations.values():
        if len(couple) != 2:
            return 0
        temps += couple[0] * couple[1]

    return temps


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    operations1 = {"addition": (2, 0.1), "subtraction": (1, 0.2)}
    operations2 = {"addition": (2, 0.1), "subtraction": (1, 0.2, 1)}
    print(calc(operations1))
    print(calc(operations2))