[Core] Job summary report with notification
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- Dominant language
- Python
- Stars
- 5
- Forks
- 4
- Avg merge
- 9h 49m
- Merged PRs (30d)
- 55
Description
About
When invoked unattended in headless environments, we would like omniload to provide excellent reports about job outcomes, and to submit them using traditional and contemporary communication paths. A traditional way for cron jobs is to emit ASCII output to stdout, which will mostly be delivered to the system administrator per email, possibly using MIME and SMTP. A modern way is to format a report using Markdown, then publish it to a Slack channel as a notification, or to a GitHub issue in case of an error.
Details
In the same polyglot spirit like omniload, we propose to use apprise for the job as a universal notification package. We would also like to highlight ntfy for people who don't want to use 3rd-party services at all. Other than job statistics collection, the feature should go into omniload unobtrusive, possibly like an add-on.
Tests
We would like to be able to automatically test this end-to-end on both our workstations and on an off-the-shelf CI environment, optimally GitHub Actions.
Documentation
The feature/outcome should be documented well and easy for users to follow and exercise. Currently, there is no corresponding place in the documentation, so let's start a new section to bundle all relevant information.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No implementation file, entry point, or test file is named. Start by locating the job execution and documentation entry points, then determine how reporting, Apprise or ntfy notifications, and GitHub Actions testing would fit without disrupting existing jobs. Done should include an agreed scope, end-to-end tests, and a documented user workflow.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- github-actions, python
- Domain
- data-engineering
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100