stefan-jansen--machine-learning-for-trading/scripts

Reader scripts

The few standalone command-line tools a reader runs, from the repository root (uv run python scripts/<name>.py). These are programs you execute; the importable library code the notebooks build on lives in utils/.

• verify_installation.py — run this first, right after installing: it imports the core dependencies and reports whether CUDA, matplotlib, and Plotly are working.
• download_artifacts.py — pulls the pre-computed model predictions and backtest results so the Chapter 11–20 case-study notebooks run without retraining from scratch.
• sync_notebooks.py — regenerates a notebook's .ipynb from its Jupytext .py source (or the reverse); pass --check to only report which pairs have drifted.
• sanitize_notebook_paths.py — strips machine-specific absolute paths out of committed notebook outputs and metadata; a CI check fails if any slip through.
• notebook_provenance.py — the pre-commit gate: it stamps each executed notebook with the git hash of its .py source and blocks commits of stale or test-mode runs.

Internal registry-maintenance tooling (backfills, schema migrations, one-off data repairs) is intentionally not in this repository — it lives in the separate maintainer workspace.