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Common task classes used by the DKIST Science Data Processing pipelines to process DKIST data.

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  • License: MIT
  • Author: NSO / AURA
  • Requires: Python >=3.8
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Project description

This repository works in concert with dkist-processing-core and dkist-processing-*instrument* to form the DKIST calibration processing stack.

Usage

The classes in this repository should be used as the base of any DKIST processing pipeline tasks. Science tasks should subclass ScienceTaskL0ToL1Base.

Each class is built on an abstract base class with the run method left for a developer to fill out with the required steps that the task should take. This class is then used as the callable object for the workflow and scheduling engine.

Example

from dkist_processing_common.tasks.base import ScienceTaskL0ToL1Base


class RemoveArtifacts(ScienceTaskL0ToL1Base):
    def run(self):
        # task code here
        total = 2 + 5

Deployment

dkist-processing-common is deployed to PyPI

Development

git clone git@bitbucket.org:dkistdc/dkist-processing-common.git
cd dkist-processing-common
pre-commit install
pip install -e .[test]
pytest -v --cov dkist_processing_common

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