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Update README.md #6
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Signed-off-by: Software Developer <[email protected]>
Signed-off-by: Software Developer <[email protected]>
Signed-off-by: Software Developer <[email protected]>
Signed-off-by: Software Developer <[email protected]>
Signed-off-by: Software Developer <[email protected]>
Signed-off-by: Software Developer <[email protected]>
Signed-off-by: Software Developer <[email protected]>
I'm assuming you want to rename |
correct! I just want to keep both so it will be easier to compare. also Im waiting for feedback from Fabio. |
Signed-off-by: Software Developer <[email protected]>
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Tested inside a dev container, everything seems to work fine, maybe it would be nice to say somewhere that the use of a Dev Container is recommended.
Signed-off-by: Software Developer <[email protected]>
Signed-off-by: Software Developer <[email protected]>
CONTRIBUTING.md
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I don't think this technical stuff belongs in CONTRIBUTING.md, see for example: https://github.com/armadaproject/armada/blob/master/CONTRIBUTING.md
I'd suggest moving the installation to README and referring users to the configure magefile if they want more information about each step rather than recapping them here.
I do, however, love days when my job requires reading things like "install the dreaded psycho"
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I don't think it should be in README -- this is the installation process for a developer, not the run-time user (I think).
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@dave-gantenbein details could be really different. In our case since we have 2 in system, overall process looks a bit complex: to run, to test, etc. I think we will simplify it, when all the endpoints will be moved to Go MLFlow so we won't need to support much Python stuff in that case. So my vote to keep all of that in CONTRIBUTING.md
and see.
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I think this is fine for now, and we can revisit it later.
What Dave is probably hinting at is that we should answer the higher-level question of how people can contribute. Adding endpoints is one way, but we also welcome other contributions such as reporting bugs, improving the onboarding experience, and adding production benchmarks to see whether this is faster than vanilla MLflow.
Overall, my two cents would be to move forward with this PR and improve things later on.
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