import time
from concurrent import futures

def default_executor():
    thread_count = 5
    return futures.ThreadPoolExecutor(thread_count)


class Executor(object):
    """
    Object to facilitate the running of a task, or a set of tasks on an
    executor that can map multiple tasks across a configurable number of
    threads
    """
    def __init__(self, executor=None):
        self._executor = executor or default_executor()

    @staticmethod
    def do(task):
        return task()

    def task_name(self, task):
        if hasattr(task, 'task_name'):
            return str(task.task_name)
        if hasattr(task, 'func_name'):
            return str(task.func_name)
        return 'UnnamedTask'

    def run(self, tasks):
        """
        Run task or set of tasks
        :param tasks: the task or tasks you want to execute in the
                      executor's pool

        :return: The results of the tasks (list)

        If a single task is pass
        """
        self.start_time = time.time()

        if callable(tasks):
            tasks = [tasks]
        results = [r for r in self._executor.map(self.do, tasks)]

        self.end_time = time.time()
        self.task_time = self.end_time - self.start_time

        task_names = [self.task_name(t) for t in tasks]
        print("Finished Tasks {tasks}s in {time}fs".format(tasks=task_names, time=self.task_time))

        return results

def main():
    def t1():
        return 1

    def t2():
        return 2

    tasks = [t1, t2, t1, t2, t1]
    exe = Executor()

    results = exe.run(tasks)
    assert results == [1, 2, 1, 2, 1]

if __name__ == "__main__":
    main()