.. py:currentmodule:: lsst.ap.pipe .. _pipeline-overview: ########################### Overview of the AP pipeline ########################### :doc:`lsst.ap.pipe ` is a data processing pipeline for Prompt Data Products. It is a Command-Line Task which operates on ingested raw data in a Butler repository. It also requires appropriate calibration products and templates. As it runs, `ApPipeTask` generates calibrated exposures, difference images, difference image source catalogs, and a source association database. The initial motivation for :doc:`lsst.ap.pipe `, information about one of the original test datasets, and an outdated tutorial are available in `DMTN-039 `_. The AP Pipeline calls three main tasks and their associated subtasks: 1. `~lsst.pipe.tasks.ProcessCcdTask`, which in turn calls `lsst.ip.isr.IsrTask`, `lsst.pipe.tasks.CharacterizeImageTask`, and `lsst.pipe.tasks.CalibrateTask` to perform image reduction as well as photometric and astrometric calibration; 2. `~lsst.pipe.tasks.ImageDifferenceTask`, which uses many utilities from :doc:`lsst.ip.diffim `; and 3. `~lsst.ap.associate.AssociationTask`, which makes a catalog of Difference Image Analysis (DIA) Objects from the DIASources created during image differencing. In practice, :doc:`lsst.ap.pipe ` is often discussed in the context of :doc:`lsst.ap.verify `. The former is responsible for running the AP Pipeline. The latter uses :doc:`lsst.ap.pipe ` to verify the output. :doc:`ap_pipe ` is entirely written in Python. Key contents include: - `ApPipeTask`: a `~lsst.pipe.base.CmdLineTask` for running the entire AP Pipeline - `ApPipeConfig`: a config for customizing ``ApPipeTask`` for a particular dataset's needs. Supported observatory packages should provide a :ref:`config override file ` that does most of the work.