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Python call graph visualization for recursive functions.

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rcviz

  • Python module to visualize a recursion as a tree with arguments and return values at each node.
  • Provides a decorator to instrument target functions (as opposed to trace or debugger based approaches)
  • Uses pygraphviz to render the graph.

Usage

Use the @viz decorator to instrument the recursive function.

@viz
def factorial(n):
    # ...

Then call it

factorial(8)

and inspect the resulting factorial.png file. Note that the file name is derived from the function name, so for example the output of quicksort would be written to quicksort.png.

Example

from rcviz import viz

@viz
def quicksort(items):
    if len(items) <= 1:
        return items
    else:
        pivot = items[0]
        lesser = quicksort([x for x in items[1:] if x < pivot])
        greater = quicksort([x for x in items[1:] if x >= pivot])
        return lesser + [pivot] + greater

print(quicksort(list("helloworld")))

output

quicksort rcviz output

Note:

  1. The edges are numbered by the order in which they were traversed by the execution.
  2. The edges are colored from black to grey to indicate order of traversal : black edges first, grey edges last.

Experimental

Show intermediate values of local variables in the output render by invoking decoratedfunction.track(param1=val1, param2=val2,...). In the quicksort example above you can track the pivot with:

	pivot = items[0]
	quicksort.track(the_pivot=pivot) # shows a new row labelled the_pivot in each node

dependencies

This requires graphviz and pygraphviz to work.

On ubuntu:

$sudo apt-get install graphviz libgraphviz-dev
$sudo python setup.py install

Tested on Python 2.7 and 3.4.

Setup script by adampetrovic.

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Python call graph visualization for recursive functions.

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