Shortly after our initial release, we are proud to announce the next milestone for our workflow library Bandsaw. With our today’s release of version 0.2, we provide now the first advice that is capable of transferring tasks to remote machines and running them there. This enables our users to use bandsaw in real world processes that depend on platforms that are not the development workstations of developers.
Bandsaw allows defining multiple different remote interpreters in its configuration and provides an easy way of distributing tasks to these remote machines. The tasks and their data including the necessary code to run them are distributed using the SSH command line tools underneath, so bandsaw doesn’t require new python dependencies. This allows bandsaw to automate parts of the process that would previously be done manually, such as:
- Packaging and transferring code to remote machine
- Manually logging in to remote system and running the task
- Copying input and output data of the task between developer machine and computation platform
The new version has been published on PyPI, so running
pip install bandsaw should give you the latest version. We updated the latest
documentation and included some
instructions for how to use the new SSH feature.
With SSH support being ready we continue now with our next two milestones:
- 0.3: Track computation resource metrics.
- 0.5: Run tasks asynchronously using a scheduler.
Besides, we are currently working on an additional product that we plan to deliver by the end of the year. Stay tuned! As always, feel free to reach out by opening feature request, sending us emails or drop by for support or a talk in discord.
Cheers,
Christoph
References
- PyPI: https://pypi.org/project/bandsaw/
- Documentation: https://docs.kant.ai/bandsaw/latest/
- Documentation SSH support: https://docs.kant.ai/bandsaw/latest/advices/remote/
- Changelog: https://docs.kant.ai/bandsaw/latest/changelog/
- GitLab: https://gitlab.com/kantai/bandsaw
