Skip to main content

Science processing code for the DLNIRSP instrument on DKIST

Project description

Overview

The dkist-processing-dlnirsp library contains the implementation of the DLNIRSP pipelines as a collection of the dkist-processing-core framework and dkist-processing-common Tasks.

The recommended project structure is to separate tasks and workflows into separate packages. Having the workflows in their own package facilitates using the build_utils to test the integrity of those workflows in the unit test.

Calibration Pipeline

Build

Artifacts are built through Bitbucket Pipelines.

The pipeline can be used in other repos with a modification of the package and artifact locations to use the names relevant to the target repo.

e.g. dkist-processing-test -> dkist-processing-vbi and dkist_processing_test -> dkist_processing_vbi

Deployment

Deployment is done with turtlebot and follows the process detailed in dkist-processing-core

Environment Variables

Only those specified by dkist-processing-core and dkist-processing-common.

Development

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

Changelog

When you make any change to this repository it MUST be accompanied by a changelog file. The changelog for this repository uses the towncrier package. Entries in the changelog for the next release are added as individual files (one per change) to the changelog/ directory.

Writing a Changelog Entry

A changelog entry accompanying a change should be added to the changelog/ directory. The name of a file in this directory follows a specific template:

<PULL REQUEST NUMBER>.<TYPE>[.<COUNTER>].rst

The fields have the following meanings:

  • <PULL REQUEST NUMBER>: This is the number of the pull request, so people can jump from the changelog entry to the diff on BitBucket.

  • <TYPE>: This is the type of the change and must be one of the values described below.

  • <COUNTER>: This is an optional field, if you make more than one change of the same type you can append a counter to the subsequent changes, i.e. 100.bugfix.rst and 100.bugfix.1.rst for two bugfix changes in the same PR.

The list of possible types is defined in the towncrier section of pyproject.toml, the types are:

  • feature: This change is a new code feature.

  • bugfix: This is a change which fixes a bug.

  • doc: A documentation change.

  • removal: A deprecation or removal of public API.

  • misc: Any small change which doesn’t fit anywhere else, such as a change to the package infrastructure.

Rendering the Changelog at Release Time

When you are about to tag a release first you must run towncrier to render the changelog. The steps for this are as follows:

  • Run towncrier build –version vx.y.z using the version number you want to tag.

  • Agree to have towncrier remove the fragments.

  • Add and commit your changes.

  • Tag the release.

NOTE: If you forget to add a Changelog entry to a tagged release (either manually or automatically with towncrier) then the Bitbucket pipeline will fail. To be able to use the same tag you must delete it locally and on the remote branch:

# First, actually update the CHANGELOG and commit the update
git commit

# Delete tags
git tag -d vWHATEVER.THE.VERSION
git push --delete origin vWHATEVER.THE.VERSION

# Re-tag with the same version
git tag vWHATEVER.THE.VERSION
git push --tags origin main

Science Changelog

Whenever a release involves changes to the scientific quality of L1 data, additional changelog fragment(s) should be created. These fragments are intended to be as verbose as is needed to accurately capture the scope of the change(s), so feel free to use all the fancy RST you want. Science fragments are placed in the same changelog/ directory as other fragments, but are always called:

<PR NUMBER | +>.science[.<COUNTER>].rst

In the case that a single pull request encapsulates the entirety of the scientific change then the first field should be that PR number (same as the normal CHANGELOG). If, however, there is not a simple mapping from a single PR to a scienctific change then use the character “+” instead; this will create a changelog entry with no associated PR. For example:

$ ls changelog/
99.bugfix.rst    # This is a normal changelog fragment associated with a bugfix in PR 99
99.science.rst   # Apparently that bugfix also changed the scientific results, so that PR also gets a science fragment
+.science.rst    # This fragment is not associated with a PR

When it comes time to build the SCIENCE_CHANGELOG, use the science_towncrier.sh script in this repo to do so. This script accepts all the same arguments as the default towncrier. For exmaple:

./science_towncrier.sh build --version vx.y.z

This will update the SCIENCE_CHANGELOG and remove any science fragments from the changelog directory.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dkist_processing_dlnirsp-0.17.1.tar.gz (128.5 kB view details)

Uploaded Source

Built Distribution

dkist_processing_dlnirsp-0.17.1-py3-none-any.whl (163.2 kB view details)

Uploaded Python 3

File details

Details for the file dkist_processing_dlnirsp-0.17.1.tar.gz.

File metadata

File hashes

Hashes for dkist_processing_dlnirsp-0.17.1.tar.gz
Algorithm Hash digest
SHA256 473518203830f152d64ac92972ec2716fe868f8bad92410fb98e2368f1431682
MD5 c0648b77f41c542f3b2f58dca079d050
BLAKE2b-256 b82d189dca2b106aceec5725310891d111a11586638846991ef70417120b53ba

See more details on using hashes here.

File details

Details for the file dkist_processing_dlnirsp-0.17.1-py3-none-any.whl.

File metadata

File hashes

Hashes for dkist_processing_dlnirsp-0.17.1-py3-none-any.whl
Algorithm Hash digest
SHA256 e18575104df8fce74e14e32f0f93db8597eee8e782d7df5ae6c092680e63f08c
MD5 b3043a6aaada173074c9dfaeecebb163
BLAKE2b-256 25a134c5a4b1f7c795e7e64af348dc5f58bc0cfc3d6ef5c6be355740f607b907

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page