Closed unkcpz closed 1 year ago
The test failed as expected, it rely on https://github.com/aiidalab/aiidalab-docker-stack/pull/333
I wonder was there a specific reason for this constraint? nbconvert <6
Do you know @yakutovicha? Are we risking breakage when nbconvert
is updated?
I wonder was there a specific reason for this constraint?
nbconvert <6
Do you know @yakutovicha? Are we risking breakage whennbconvert
is updated?
I remember nothing about this package. One needs to test...
I wonder was there a specific reason for this constraint?
nbconvert <6
Do you know @yakutovicha? Are we risking breakage whennbconvert
is updated?I remember nothing about this package. One needs to test...
btw, there is also https://github.com/aiidalab/aiidalab-widgets-base/issues/384.
Thanks @yakutovicha, I was not aware of that issue. Couple days ago I also opened #392 which is related.
@unkcpz could you open a new PR which would only fix the dependencies for the current Docker stack, listed above? aiida-core[atomic_tools] is a separate discussion.
Sure, updated. I add PyCifRW
explicitly since it is required by this package.
The firefox tests are expected to fail and PR #397 is for it, there are two chrome tests that also fail but I think if there are two passes then the implementation is correct.. I'll merge this and if anything happened I'll fix it afterward.
Sorry, I am late to the party.
aiidalab>=21.11.2
is already pinned in the stack
I am not 100% sure this is a good thing to do. AiiDAlab could be setup outside of the stack, and AWB does require aiidalab package to function.
You are right, and I find the doc build always lack the necessary packages if aiidalab
package is not explicitly installed. I add aiidalab>=21.11.2
back in https://github.com/aiidalab/aiidalab-widgets-base/pull/397 to fix the doc build test.
The principle of my cleaning process is the packages in the list do not conflict with each other and do not duplicate. For example, if the package is installed by aiida-core dep, it should not be specified again in the list. As for the jupyter backend packages, there is no need to install then, since
aiida-core
> 2 will lead to installnumpy~=1.19
thereforenumpy~=1.23
is installed.The following packages are even in conflict and will override the deps which causes the Jupyter engine to fail, we need to pining version when we find future confliction.
jupyter-client<7
nbconvert<6
aiidalab>=21.11.2
is already pinned in the stack