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A lightweight Python module for creating and running ordered graphs of computations.

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GraphKit

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Full Documentation

It's a DAG all the way down

simple graphkit computation

Lightweight computation graphs for Python

GraphKit is an an understandable and lightweight Python module for building and running ordered graphs of computations. The API posits a fair compromise between features and complexity without precluding any. It might be of use in computer vision, machine learning and other data science domains, or become the core of a custom ETL pipelne.

Quick start

Here's how to install:

pip install graphkit

OR with dependencies for plotting support (and you need to install Graphviz program separately with your OS tools):

pip install graphkit[plot]

Here's a Python script with an example GraphKit computation graph that produces multiple outputs (a * b, a - a * b, and abs(a - a * b) ** 3):

>>> from operator import mul, sub
>>> from graphkit import compose, operation

>>> # Computes |a|^p.
>>> def abspow(a, p):
...     c = abs(a) ** p
...     return c

>>> # Compose the mul, sub, and abspow operations into a computation graph.
>>> graphop = compose(name="graphop")(
...     operation(name="mul1", needs=["a", "b"], provides=["ab"])(mul),
...     operation(name="sub1", needs=["a", "ab"], provides=["a_minus_ab"])(sub),
...     operation(name="abspow1", needs=["a_minus_ab"], provides=["abs_a_minus_ab_cubed"], params={"p": 3})(abspow)
... )

simple graphkit computation

>>> # Run the graph and request all of the outputs.
>>> out = graphop({'a': 2, 'b': 5})
>>> print(out)
{'a': 2, 'b': 5, 'ab': 10, 'a_minus_ab': -8, 'abs_a_minus_ab_cubed': 512}

>>> # Run the graph and request a subset of the outputs.
>>> out = graphop({'a': 2, 'b': 5}, outputs=["a_minus_ab"])
>>> print(out)
{'a_minus_ab': -8}

simple graphkit computation

As you can see, any function can be used as an operation in GraphKit, even ones imported from system modules!

Plotting

For debugging the above graph-operation you may plot either the newly omposed graph or the execution plan of the last computation executed, using these methods:

graphop.plot(show=True)                # open a matplotlib window
graphop.plot("graphop.svg")            # other supported formats: png, jpg, pdf, ...
graphop.plot()                         # without arguments return a pydot.DOT object
graphop.plot(solution=out)             # annotate graph with solution values

Graphkit Legend

TIP: The pydot.Dot instances returned by plot() are rendered as SVG in Jupyter/IPython.

License

Code licensed under the Apache License, Version 2.0 license. See LICENSE file for terms.

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A lightweight Python module for creating and running ordered graphs of computations.

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