headergen 1.0.0

HeaderGen: Automated cell header generator

HeaderGen

HeaderGen is a tool-based approach to enhance the comprehension and navigation of undocumented Python based Jupyter notebooks by automatically creating a narrative structure in the notebook.

Data scientists build an ML-based solution notebook by first preparing the data, then extracting key features, and then creating and training the model. HeaderGen leverages the implicit narrative structure of an ML notebook to add structural headers as annotations to the notebook.

Features

• Automated Markdown Header Insertion: Through a taxonomy for machine-learning operations, HeaderGen annotates code cells with relevant markdown headers.

• Function Call Taxonomy: Methodically classifies function calls based on a machine-learning operations taxonomy.

• Advanced Call Graph Analysis: Enhances PyCG framework with flow-sensitivity and external library return-type resolution.

• Precision in External Libraries: capability to accurately resolve function return types from external libraries using typestubs.

• Syntax Pattern Matching: Employs type data for pattern matching.

Folder Structure

• callsites-jupyternb-micro-benchmark: Micro benchmark
• callsites-jupyternb-real-world-benchmark: Real-world benchmark
• evaluation: Contains manual header annotation and user study results
• framework_models: Function calls to ML Taxonomy mapping
• typestub-database: Type-stbs for ML libraries
• headergen: Source code of HeaderGen
• pycg_extended: Source code of extended PyCG
• headergen-extension: Jupyter notebook plugin for HG
• headergen_output: Folder where the generated notebooks from the docker container are stored

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1. Build container

• Get source files

  git clone --recursive
  git submodule update --init --recursive
  git pull --recurse-submodules
  

• Linux

  docker build -t headergen .
  docker run -v {$PWD}/headergen_output:/results -it headergen bash
  

• Windows

  docker build -t headergen .
  docker run -v "%cd%"/headergen_output:/results -it headergen bash
  

2. Run HeaderGen benchmarks from inside contatiner

Output generated from the following commands, such as annotated notebooks, reports, callsites, headers, etc, are stored in the local folder headergen_output after the following commands are done executing.

• Micro Benchmark (generates a csv file with results)

  make microbench
  

• Real-world Benchmark (generates annotated notebooks and csv file that reproduce table 2)

  make realworldbench
  

• Both Benchmarks

  make all
  

• Clean generated output

  make clean
  

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This repo contains code for the paper "Enhancing Comprehension and Navigation in Jupyter Notebooks with Static Analysis" published at the SANER Conference 2023.