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The proposal is to setup a GitHub workflow to run checks on every commit. For open source repositories this is free.
Motivation
This would be a quick way to check that a commit passes linting and unit tests (possibly other checks too) and could speed up reviews and identify issues.
Design Proposal
Implementation Plan
Add the necessary file to the .github/workflows directory. This has been done on a fork here https://github.com/tgdif/pyoneer/tree/continuous_integration. Note that the commit is failing one check but that is due to a separate issue with one of the existing unit tests.
Alternatives Considered
There are a variety of alternatives (Travis, CircleCI, Azure Pipelines, etc.) though this looks to be the simplest way and does not require adding a separate app.
The text was updated successfully, but these errors were encountered:
Should I also upgrade some of the dependent packages in Pipfile and setup.py? These affect the environments used when running the workflow. Since tensorflow and tensorflow-probability now support TF version 2.0.0 by default on PyPI their versions can be bumped up.
Feature Request
The proposal is to setup a GitHub workflow to run checks on every commit. For open source repositories this is free.
Motivation
This would be a quick way to check that a commit passes linting and unit tests (possibly other checks too) and could speed up reviews and identify issues.
Design Proposal
Implementation Plan
Add the necessary file to the
.github/workflows
directory. This has been done on a fork here https://github.com/tgdif/pyoneer/tree/continuous_integration. Note that the commit is failing one check but that is due to a separate issue with one of the existing unit tests.Alternatives Considered
There are a variety of alternatives (Travis, CircleCI, Azure Pipelines, etc.) though this looks to be the simplest way and does not require adding a separate app.
The text was updated successfully, but these errors were encountered: