Closed prjemian closed 2 years ago
Is it necessary to run black
, flake8
, & pytest
in the publish_docs
workflow? These are out of scope of this workflow. Should not tag (which would actually publish the docs built here) if these processes have failed the unit test or linting worfkflows.
https://github.com/bluesky/hklpy/blob/54defeaabb441bb554df8b6baeccda15342ae24e/Makefile#L5
@mrakitin This is ready for review. I assumed that the gobject-introspection
package requirement would be inherited from the hkl
package. This PR enforces that requirement. The added Diagnotics in the worfklow are useful to identify the problem more quickly.
Is it necessary to run
black
,flake8
, &pytest
in thepublish_docs
workflow? These are out of scope of this workflow. Should not tag (which would actually publish the docs built here) if these processes have failed the unit test or linting worfkflows.https://github.com/bluesky/hklpy/blob/54defeaabb441bb554df8b6baeccda15342ae24e/Makefile#L5
Maybe we could use the needs
feature of the workflows to enable chained conditional execution, as we did in https://github.com/NSLS-II/edrixs/blob/fc1a316df2532950b73325e501b41a7cd37ae80e/.github/workflows/ci-test.yml#L26? It'd look like: https://github.com/NSLS-II/edrixs/actions/runs/1492481471.
@mrakitin Thanks for the quick review. The chained workflow example using needs
is a great suggestion (wondered how to do that). That chained workflow puts the entire workflow into one YAML file.
I'll merge this PR and study implementation in a test project before introducing a chained workflow here.
@mrakitin Thanks for the quick review. The chained workflow example using
needs
is a great suggestion (wondered how to do that). That chained workflow puts the entire workflow into one YAML file.
Yes, that was a shortcoming. I tried to see how this can be split into separate files and that are included in the main workflow, but it apparently requires writing separate actions, which is much more work than just extracting it into a separate file. With Azure Pipelines it's done much more trivially (see e.g., https://github.com/NSLS-II/profile-collection-ci/blob/418b045897dd8cb8bc2a7013a70e18f30bc8006d/nsls2-collection-2021-3.0-py39.yml#L49).