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A functional composition framework that supports:
- State - functions which retain state for their next turn of action.
- Ambiguity - non deterministic composition with priorities.
- Injection of compositions into long pipelines (deep dependency injection).
- Non cancerous
pip install computation-graph
python setup.py sdist bdist_wheel; twine upload dist/*; rm -rf dist/;
We need graphviz to visualize computation graphs:
sudo apt update && apt install graphviz pip install pygraphviz
Debugging is possible by replacing
debug.debugger(filename) as the first argument.
This will save a file on each graph execution to current working directory.
You can use this file in a graph viewer like gephi. Nodes colored red are part of the 'winning' computation path. Each of these nodes has the attributes 'result' and 'state'. 'result' is the output of the node, and 'state' is the new state of the node.
In gephi you can filter for the nodes participating in calculation of final result by filtering on result != null.
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