Hi all, As a heavy user of Gitpod (mostly for quick fixes) I would also like to point out that you *can* still use it - it's just that the development environment won't be set up by default. I agree it has been breaking far too often and requires a lot of optimization to reach reasonable setup times, and while I haven't been using the codespaces setup I can see the gain in maintenance effort there. Cheers, Melissa On Tue, Mar 21, 2023 at 9:21 AM Klaus Zimmermann <klaus.zimmermann@smhi.se> wrote:
Hi,
this sounds all reasonable to me, and as mostly a lurker on this list my input shouldn't carry too much weight anyway.
I wanted to point out one thing: Docker does continue to offer free access for Open Source projects, it's just that they restructured the way of how to do this. So if there is still value in Docker, an application to the Docker-Sponsored Open Source tier should certainly fit Numpy. A bit more information is at
https://www.docker.com/blog/we-apologize-we-did-a-terrible-job-announcing-th...
Cheers Klaus
On 20/03/2023 22:09, Ralf Gommers wrote:
Hi all,
We received a notification from Docker that there Free Team organization no longer exists, and that we have until April 14 to upgrade to a paid tier. We only use Docker to support Gitpod. Gitpod builds have been broken in main for quite a while (see https://github.com/numpy/numpy/actions/workflows/gitpod.yml <https://github.com/numpy/numpy/actions/workflows/gitpod.yml>). Since it's a cron job that doesn't show up on PRs, but I get the notifications.
Overall, Gitpod has been useful during some sprints, but it has proven to be too much maintenance effort. Maintaining a Docker team, CI jobs for building 2 Docker images, and a nontrivial amount of code and docs is no longer a good tradeoff.
Here is what we have related to Gitpod: https://github.com/numpy/numpy/tree/main/tools/gitpod <https://github.com/numpy/numpy/tree/main/tools/gitpod> https://github.com/numpy/numpy/blob/main/.github/workflows/docker.yml <https://github.com/numpy/numpy/blob/main/.github/workflows/docker.yml> https://github.com/numpy/numpy/blob/main/.github/workflows/gitpod.yml <https://github.com/numpy/numpy/blob/main/.github/workflows/gitpod.yml>
https://github.com/numpy/numpy/blob/main/doc/source/dev/development_gitpod.r... < https://github.com/numpy/numpy/blob/main/doc/source/dev/development_gitpod.r...
https://hub.docker.com/u/numpy <https://hub.docker.com/u/numpy>
We have a reasonable alternative, which is GitHub Codespaces. All it currently requires is ~lines of simple to understand code (https://github.com/numpy/numpy/tree/main/.devcontainer <https://github.com/numpy/numpy/tree/main/.devcontainer>) and no CI jobs. We have one tracking issue for feedback in case you try it and find gaps: https://github.com/numpy/numpy/issues/23134 <https://github.com/numpy/numpy/issues/23134>. It doesn't pre-build NumPy locally, but that's only 1-2 minutes of wait time and is something a new contributor anyway has to learn about. The dev environment is reproducible, so this isn't much of a hurdle. We need replacement docs for that, but they can be much simpler I'd say. It's basically "go to https://github.com/codespaces/ <https://github.com/codespaces/>, hit
the
green button, and select the numpy repo, then it'll drop you into a VSCode IDE with a ready to go dev env".
So my proposal is to drop all the Docker Hub and Gitpod related code and docs. I have already discussed this with Tania Allard, who did most of the heavy lifting on the initial creation of the Gitpod machinery (for SciPy, which was then synced to NumPy).
Thoughts?
Cheers, Ralf
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