taskgraph 0.2.5

Parallel task graph framework.

TaskGraph:

About TaskGraph

TaskGraph is great.

TaskGraph Dependencies

Task Graph is written in pure Python, but if the psutils package is installed the distributed multiprocessing processes will be niced.

Example Use

Install taskgraph with

pip install taskgraph

Then

def _create_list_on_disk(value, length, target_path):
    """Create a numpy array on disk filled with value of `size`."""
    target_list = [value] * length
    pickle.dump(target_list, open(target_path, 'wb'))


def _sum_lists_from_disk(list_a_path, list_b_path, target_path):
    """Read two lists, add them and save result."""
    list_a = pickle.load(open(list_a_path, 'rb'))
    list_b = pickle.load(open(list_b_path, 'rb'))
    target_list = []
    for a, b in zip(list_a, list_b):
        target_list.append(a+b)
    pickle.dump(target_list, open(target_path, 'wb'))

# create a taskgraph that uses 4 multiprocessing subprocesses when possible
task_graph = taskgraph.TaskGraph(self.workspace_dir, 4)
target_a_path = os.path.join(self.workspace_dir, 'a.dat')
target_b_path = os.path.join(self.workspace_dir, 'b.dat')
result_path = os.path.join(self.workspace_dir, 'result.dat')
result_2_path = os.path.join(self.workspace_dir, 'result2.dat')
value_a = 5
value_b = 10
list_len = 10
task_a = task_graph.add_task(
    target=_create_list_on_disk,
    args=(value_a, list_len, target_a_path),
    target_path_list=[target_a_path])
task_b = task_graph.add_task(
    target=_create_list_on_disk,
    args=(value_b, list_len, target_b_path),
    target_path_list=[target_b_path])
sum_task = task_graph.add_task(
    target=_sum_lists_from_disk,
    args=(target_a_path, target_b_path, result_path),
    target_path_list=[result_path],
    dependent_task_list=[task_a, task_b])
sum_task.join()

# expect that result is a list `list_len` long with `value_a+value_b` in it
result = pickle.load(open(result_path, 'rb'))