jupyter-lsp v3.3.1

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Here is a list of all the pending dependencies (and their versions) for this repo. Please double check all dependencies before merging.

Name	Upstream Version	Current Version
jupyter-lsp	3.3.1

Dependency Analysis

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Analysis of the source code shows a discrepancy between the library's imports and the package's stated requirements in the meta.yaml.

Packages found by inspection but not in the meta.yaml:

• traitlets
• jsonschema
• six
• tornado

Packages found in the meta.yaml but not found by inspection:

• jupyter-lsp-python
• jupyter-lsp
• pyls-isort
• pyls-black
• pyls-memestra
• pyls-mypy
• python-language-server

[conda-forge-linter]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

[fcollonval]

@krassowski There is an inconsistency between the python package and the conda package for jupyterlab-lsp. This one force jupyter-lsp version to the latest version when the python package states jupyter-lsp>=1.1.0. Should we align that behaviour? If so which constrain should be updated; the one in this recipe or the one in jupyterlab-lsp/setup.cfg?

[krassowski]

No strong opinion. Maybe keeping an exact pin would be easier than changing it each time. What are you experiences from jupyterlab-git and other packages?

[bollwyvl]

The pin between the two is somewhat tough: it kinda depends on what the behavior is when folks upgrade. Upstream we don't test the about-to-be-release versions against historical versions, so the upstream really only guarantees that the latest are working, which was kind of my thinking here. This would have to be a nightly CI, i guess, as we can't slow down CI any more.

Given we were considering packaging everything together, i think demanding at least the most-recently-packaged-at-the-same-time version probably makes the most sense. Going any further, e.g. =={{server_version}}`` is probably _not_ what we want, as then it becomes impossible to do patch releases of server ofjupyter-lspwithout doing anotherjupyterlab-lsp`.

So I think we just ship with what we have here, and I'll make an issue upstream.

[fcollonval]

What are you experiences from jupyterlab-git and other packages?

Actually I never published front and back extensions separately. When updating to JLab3 I pick-up the highest version of both if they were not aligned to avoid package resolution errors. This of course implies republishing the python code even if the change is only in the frontend. If we would to choose that principle for jupyterlab-lsp, this means the version needs to be aligned with the frontend version. This will definitely ease the maintenance on the conda side.

[bollwyvl]

Yeah, well... the goal is to be able to support other clients that might not be The JupyterLab, and be testable outside of jupyterlab. If we do pursue the kernel approach, it won't even be sane to depend on a particular client. If somebody wants to write one that works for nteract, colab or whatever, hooray! Maybe they'll PR something. But they definitely won't if it only works with JupyterLab. As a downstream, I'll take slightly more complicated conda over hard and incompatible forks any day.

[fcollonval]

Make sense @bollwyvl. Thanks for the detailed answer