learnlog 0.18

Automatic logging of student code development and test runs

learnlog

A Python package that automatically logs code development and program runs.

By adding import learnlog as the first import in a Python file, every program run is recorded transparently: source code changes, command-line arguments, standard input/output/error, and unhandled exceptions. The data is stored in a hidden local Git repository.

Use cases

• Sharing live-coding sessions. A teacher adds import learnlog to demonstration scripts during a lecture or tutorial. After the session the teacher pushes the log to a remote repository:

  learnlog set-remote [e-mail]:dbosk/lecture01.git
  learnlog push
  

  Students clone the log and replay it step by step:

  learnlog clone [e-mail]:dbosk/lecture01.git
  learnlog play
  

  Alternatively, when a shared Git remote is not available, the teacher can export the log as a portable bundle file:

  learnlog export -o lecture01.bundle
  

  The teacher distributes the file (e.g. via a course page) and students replay it directly:

  learnlog play lecture01.bundle
  

• Studying how students code. A researcher creates an empty Git repository for each student. Each student adds import learnlog to their programs and pushes the log:

  learnlog set-remote [e-mail]:dbosk/alice-log.git
  learnlog push
  

  The researcher then clones each student's repository to analyse the development data:

  learnlog clone [e-mail]:dbosk/alice-log.git
  learnlog play
  learnlog analyse X-Tag=lab1 X-Tag=lab2
  

  The analyse command generates LaTeX reports of edit--run cycles. The optional positional arguments filter events by Column=Regex boundaries—here, only events between tags lab1 and lab2 are included.

  Alternatively, the student can export the log as a bundle and submit it through the course platform:

  learnlog export -o alice-log.bundle
  

  The researcher then replays it directly:

  learnlog play alice-log.bundle
  

  This gives a complete timeline of how students develop and debug their code — for research purposes or to help students refine their debugging techniques.