spark

Getting Started

This guide gets a contributor from clone to successful CLI usage in under 10 minutes.

Prerequisites

• Python 3.10+
• Git 2.x+
• Optional but recommended: a virtual environment tool (venv, uv, or virtualenv)

Installation

git clone https://github.com/rudra496/spark.git
cd spark
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -e .

First-Run CLI Flow

Run these commands from the repository root:

python -m spark validate --root .
python -m spark discover --root .
python -m spark assess --root .
python -m spark health --root .
python -m spark version

Expected behavior:

• validate checks required repository files.
• discover prints repository metadata as JSON.
• assess returns a maturity score and recommendations.
• health exits with 0 only when the repo is valid and workflows exist.
• version prints the installed Spark version.

JSON Automation Usage

Use --json for machine-readable output in CI scripts.

python -m spark validate --root . --json
python -m spark assess --root . --json
python -m spark health --root . --json

Example gate in shell:

python -m spark health --root . --json | python -c "import json,sys; sys.exit(0 if json.load(sys.stdin)['healthy'] else 1)"

Troubleshooting

mkdocs: command not found

Install docs tooling:

pip install mkdocs mkdocs-material

spark validate reports missing files

Run discovery to understand current structure:

python -m spark discover --root .

Then add missing files listed by validate.

Unexpected locale output

List supported locales and re-run with a valid locale code:

python -m spark locales
python -m spark validate --root . --locale en

Command not found for spark

Use module mode if console scripts are unavailable:

python -m spark --help

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