Description
I would like to make a simple cli tool to communicate with the OpenQA API
Goals
- OpenQA has a ton of information that is hard to get via the UI. A tool like this would make my life easier :)
- Would potentially make it easier in the future to make UI changes without Perl.
- Improve my Golang skills
Resources
- https://go.dev/doc/
- https://openqa.opensuse.org/api
This project is part of:
Hack Week 24
Activity
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Description
In the openQA test framework, to identify the status of a target SUT image, a screenshots of GUI or CLI-terminal images,
the needles framework scans the many pictures in its repository, having associated a given set of tags (strings), selecting specific smaller parts of each available image. For the needles management actually we need to keep stored many screenshots, variants of GUI and CLI-terminal images, eachone accompanied by a dedicated set of data references (json).
A smarter framework, using image recognition based on AI or other image elaborations tools, nowadays widely available, could improve the matching process and hopefully reduce time and errors, during the images verification and detection process.
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Main scope of this idea is to match a non-text status of a running openQA test, an image of a shell console or application-GUI screenshot, using less time and resources and with less errors in data preparation and use, than the actual openQA needles framework; that is:
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- possibly able to identify also object not present in the archive, i.e. by means of AI/ML mechanisms.
- the matching result should be then adapted to continue working in the openQA test, likewise and in place of the same result that would have been produced by the original openQA needles framework.
- We expect an improvement of the matching-time(less time), reliability of the expected result(less error) and simplification of archive maintenance in adding/removing objects(smaller DB and less actions).
Hackweek step
POC:
- study the available tools
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- prepare the data archive from a subset of needles
- initialize/pre-train the base archive
- select a screenshot from the subset, removing/changing some part
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- expect the image type is identified in a good %.
Resources
first step of this project is quite identification of useful resources for the scope; some possibilities are:
- SUSE AI and other ML tools (i.e. Tensorflow)
- Tools able to manage images
- RPA test tools (like i.e. Robot framework)
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Description
*** Warning: Are You at Risk for VOMIT? ***
Do you find yourself staring at a screen, your eyes glossing over as thousands of lines of text scroll by? Do you feel a wave of text-based nausea when someone asks you to "just check the logs"?
You may be suffering from VOMIT (Verbose Output Mental Irritation Toxicity).
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