Dagger performs tasks, providing you with parallel execution, and dependency resolution.
Workflows are defined as graphs (directed acyclic graphs โฆ get it?). You tell dagger to run certain tasks, and it makes sure that dependencies are discovered and run in a correct order.
Tasks are run in a process pool of configurable size.
You define tasks by subclassing Task
:
class DoStuff(Task):
def run(self):
print("Look at me, I'm runniiiiiing ...")
Tasks accept two parameters during creation
config
: Something picklable to customize the tasks behavior at runtimedependencies
: A list ofTask
instances that need to be done before we start this task
If task execution fails, a DaggerException
is raised, with information about which tasks completed
and which failed.
See also examples folder.