Science Catalogs Pipeline

Creates photometric “science catalogs” with Dask.

Requirements

• micromamba available in PATH (to create the pipe_sc env)

Install

./install.sh

Creates/updates the micromamba env defined in environment.yaml.

Configure

cp config.template.yaml config.yaml      # generic template
# or
cp config.des_dr2.yaml config.yaml       # DES DR2 example (from the notebook)

Optional: generate config.yaml and env.sh interactively with your paths:

./setup.sh

Run

./run.sh config.yaml run001

Outputs: run001/data, run001/logs, run001/process_info, run001/config.yml.

Project layout

• run.sh, install.sh, setup.sh — orchestration scripts
• environment.yaml — micromamba env (pipe_sc)
• config.template.yaml, config.des_dr2.yaml — config templates/examples
• scripts/sc-run — pipeline entrypoint
• packages/ — core modules (core.py, executor.py, utils.py)
• tsm/ — Training Set Maker bundle kept for reference

Reuse packages/core.py exposes run_pipeline(config_path, cwd). Add packages/ to PYTHONPATH or extract it to a shared package to reuse across pipelines.

Acknowledgements Developed at LIneA as part of contributions to Rubin/LSST, using the LINCC software layer (hats, hats-import, lsdb).