GraphKit¶

It’s a DAG all the way down!

Lightweight computation graphs for Python¶

GraphKit is a lightweight Python module for creating and running ordered graphs of computations, where the nodes of the graph correspond to computational operations, and the edges correspond to output –> input dependencies between those operations. Such graphs are useful in computer vision, machine learning, and many other domains.

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)
)

# Run the graph-operation and request all of the outputs.
out = graphop({'a': 2, 'b': 5})

# Prints "{'a': 2, 'a_minus_ab': -8, 'b': 5, 'ab': 10, 'abs_a_minus_ab_cubed': 512}".
print(out)

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

# Prints "{'a_minus_ab': -8}".
print(out)

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 the execution plan of the last computation it using these methods:

graphop.plot(show=True)                # open a matplotlib window
graphop.plot("intro.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

The legend for all graphkit diagrams, generated by graphkit.plot.legend().

Tip

The pydot.Dot instances returned by plot() are rendered directly in Jupyter/IPython notebooks as SVG images.

Note

For plots, Graphviz program must be in your PATH, and pydot & matplotlib python packages installed. You may install both when installing graphkit with its plot extras:

pip install graphkit[plot]

License¶

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