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It reads raw [cstimer](https://cstimer.net) JSON exports, writes a parquet\nbacking store for fast analytics, computes summary statistics, and renders exploratory\nmatplotlib plots. Entries from the json files are deduplicated.\n\n## Quick start\n\n```bash\nuv sync --dev          # create the virtualenv and install runtime + pytest\nuv run cube add ~/cube/*.txt\nuv run cube analyze  # summary + latest 15 solves\nuv run cube plot\nuv run cube plot --axis=solve\nuv run cube info\n```\n\nThe CLI accepts any number of export files and consolidates them into\na single parquet file stored under your user data directory (per\n`platformdirs`). Analysis prints a readable summary plus the latest 15\nsolves with Ao5/Ao12 values, and plots are rendered interactively\n(choose `--axis=solve` for stepped x-axis by solve order) with\nAo5/Ao12 overlays. Run `cube info` at any time to print the resolved\ndataset path.\n\n## Development\n\n- `uv add \u003cpackage\u003e` manages dependencies in `pyproject.toml`\n- `uv run pytest` executes the automated test suite\n- install [prek](https://prek.j178.dev/) for pre-commit hooks\n\n## Other packages\n\nThe cstimer import is based on\n[scramble-history](https://github.com/purarue/scramble-history), which\ndoes most of what I wanted (and more), but did not seem to have a\nparquet file backend for a single storage.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farunpersaud%2Fcube","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Farunpersaud%2Fcube","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farunpersaud%2Fcube/lists"}