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A graph scheduler generates the order in which the nodes of a directed acyclic graph (DAG) are executed using the structure of the graph and expressive conditions. Specifically, a scheduler uses a topological ordering of the nodes as a base sequence of execution and further restricts execution based on predefined or custom conditions provided by the user. Patterns of execution are linked to abstract units of time and may optionally be mapped to real time units using pint.
Documentation is available on github-pages for the current
release and for the
current main
branch. For
prior releases, go to
https://kmantel.github.io/graph-scheduler/tag/<tag_name>
.
Install from pypi:
pip install graph-scheduler
The graph is specified here in dependency dictionary format, but networkx Digraphs are also supported.
>>> import graph_scheduler
>>> graph = {
'A': set(),
'B': {'A'},
'C': {'A'},
'D': {'B', 'C'},
}
>>> sched = graph_scheduler.Scheduler(graph=graph)
>>> sched.add_condition('C', graph_scheduler.EveryNCalls('A', 2))
>>> sched.add_condition('D', graph_scheduler.EveryNCalls('C', 2))
>>> print(list(sched.run()))
[{'A'}, {'B'}, {'A'}, {'C', 'B'}, {'A'}, {'B'}, {'A'}, {'C', 'B'}, {'D'}]
FAQs
A graph-based scheduler of nodes based on structure and conditions
We found that graph-scheduler demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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