Callgraph is a Python package that defines a decorator, and Jupyter magic, to draw dynamic call graphs of Python function calls.
It’s intended for classroom use, but may also be useful for self-guided exploration.
The package defines a Jupyter IPython magic, %callgraph, that displays a call graph within a Jupyter cell:
from functools import lru_cache
@lru_cache()
def lev(a, b):
if "" in (a, b):
return len(a) + len(b)
candidates = []
if a[0] == b[0]:
candidates.append(lev(a[1:], b[1:]))
else:
candidates.append(lev(a[1:], b[1:]) + 1)
candidates.append(lev(a, b[1:]) + 1)
candidates.append(lev(a[1:], b) + 1)
return min(candidates)
%callgraph -w10 lev("big", "dog"); lev("dig", "dog")
It also provides a Python decorator, callgraph.decorator, that instruments a function to collect call graph information and render the result.
In a Jupyter IPython notebook:
%load_ext callgraph
def nchoosek(n, k):
if k == 0:
return 1
if n == k:
return 1
return nchoosek(n - 1, k - 1) + nchoosek(n - 1, k)
%callgraph nchoosek(4, 2)
As an alternative to including %load_ext callgraph in each notebook that uses %callgraph, you can add the extension to the Notebook configuration file in your IPython profile.
Your configuration file is probably called ~/.ipython/profile_default/ipython_config.py. (You can run ipython profile locate to find it.) Edit this file to include the following line:
c.InteractiveShellApp.extensions = ["callgraph.extension"]
(If your configuration file already includes an uncommented statement c.InteractiveShellApp.extensions = […], edit the list of extensions in that line to include "callgraph.extension".
See extension example notebook for additional examples.
from functools import lru_cache
import callgraph.decorator as callgraph
@callgraph()
@lru_cache()
def nchoosek(n, k):
if k == 0:
return 1
if n == k:
return 1
return nchoosek(n - 1, k - 1) + nchoosek(n - 1, k)
nchoosek(5, 2)
nchoosek.__callgraph__.view()
See the API documentation for additional documentation.
See the decorator example notebook for additional instructions and examples.
Install dev tools, and set up a Jupyter kernel for the current python enviromnent:
$ pip install -r requirements-dev.txt $ python -m ipykernel install --user
Install locally:
Callgraph uses the Python graphviz package. Python graphviz uses the Graphviz package.
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