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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.

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Graph Scheduler

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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>.

Installation

Install from pypi:

pip install graph-scheduler

Example

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'}]

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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.

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