K3D lets you create 3D plots backed by WebGL with high-level API (surfaces, isosurfaces, voxels, mesh, cloud points, vtk objects, volume renderer, colormaps, etc). The primary aim of K3D-jupyter is to be easy for use as stand alone package like matplotlib, but also to allow interoperation with existing libraries as VTK.
Because I found it difficult to run the travis tests for my fork for #386, this PR adds a minimal GitHub actions setup to replace travis. It adds uploading of the result comparison ongs as artefacts, which isn't possible out-of-the-box with travis and necessitated the bencode-to-log workaround. I've also added wheel building as a separate job.
I've also added optional dependencies to pyproject.toml that make installing the necessary dependencies easy and documented. I did not touch the tests themselves in this PR.
This PR is based on #386 and only makes sense to review/merge after #386 is merged (and this PR rebased).
Because I found it difficult to run the travis tests for my fork for #386, this PR adds a minimal GitHub actions setup to replace travis. It adds uploading of the result comparison ongs as artefacts, which isn't possible out-of-the-box with travis and necessitated the bencode-to-log workaround. I've also added wheel building as a separate job. I've also added optional dependencies to
pyproject.toml
that make installing the necessary dependencies easy and documented. I did not touch the tests themselves in this PR. This PR is based on #386 and only makes sense to review/merge after #386 is merged (and this PR rebased).