Decorators and Jupyter IPython magic to display a dynamic call graph.
Project description
Callgraph is a Python package that uses GraphViz 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.
Jupyter Usage
$ pip install callgraphIn a Jupyter 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)See https://github.com/osteele/callgraph/blob/master/examples/callgraph-magic-examples.ipynb for additional instructions and examples.
Decorator Usage
$ pip install callgraphfrom 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 https://github.com/osteele/callgraph/blob/master/examples/callgraph-decorator-examples.ipynb for additional instructions and examples.
Development
Install dev tools, and set up a Jupyter kernel for the current python enviromnent:
$ pip install flit
$ pip install ipykernel
$ python -m ipykernel install --userInstall locally:
flit install --symlinkAcknowledgements
Callgraph uses the Python graphviz package. Python graphviz uses the Graphviz package.
License
MIT
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