Developers of open source software often have a difficult time understanding how others utilize their libraries. Having better data of when and how functions are being used has many benefits. Some of these are:
- better API design
- determining whether or not a feature can be deprecated or removed.
- more instructive tutorials
- understanding the adoption of new features
We wrote a general tool python-api-inspect to analyze any function/attribute call within a given set of namespaces in a repository. This work was heavily inspired by a blog post on inspecting method usage with Google BigQuery for pandas, NumPy, and SciPy. The previously mentioned work used regular expressions to search for method usage. The primary issue with this approach is that it cannot handle import numpy.random as rand; rand.random(...) unless additional regular expressions are constructed for each case and will result in false positives. Additionally, BigQuery is not a free resource. Thus, this approach is not general enough and does not scale well with the number of libraries that we would like to inspect function and attribute usage.
A more robust
from Planet SciPy
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