The LSST Science Pipelines¶
The LSST Science Pipelines enable optical and near-infrared astronomy in the big data era. We are building the Science Pipelines for the Large Synoptic Survey Telescope (LSST), but our command line task and Python API can be extended for any optical or near-infrared dataset.
The latest release is 14.0: learn what’s new.
Getting started¶
If you’re new to the LSST Science Pipelines, these tutorials will get you up and running with step-by-step installation and processing tutorials.
- Data processing tutorial: Part 1 Data repositories · Part 2 Single frame processing · Part 3 Image coaddition · Part 4 Source measurement.
Join us on the LSST Community forum to get help and share ideas.
Installation¶
Recommended installation path:
- Installing with newinstall.sh
- Setting up installed LSST Science Pipelines
- Top-level packages to install
Alternative distributions and installation methods:
- Running with Docker
- Installing from source with lsstsw
- CernVM FS (contributed by CC-IN2P3)
Related topics:
To install the LSST Simulation software, such as MAF, please follow the LSST Simulations documentation.
More info¶
- Join us on the LSST Community forum, community.lsst.org.
- Fork our code on GitHub at https://github.com/lsst.
- Report issues in JIRA.
- API documentation is currently published with Doxygen.
- DM Developer guidance is at https://developer.lsst.io.
- Learn more about LSST Data Management by visiting http://lsst.org/about/dm.
- Contribute to our documentation. This guide is on GitHub at lsst/pipelines_lsst_io.