- 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.
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.
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")))
Note:
- The edges are numbered by the order in which they were traversed by the execution.
- 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 nodeThis 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.