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I don't know if it's a coincidence but we just released a major new feature in Metaflow a few days ago - composing flows with custom decorators: https://docs.metaflow.org/metaflow/composing-flows/introduct...

A big deal is that they get packaged automatically for remote execution. And you can attach them on the command line without touching code, which makes it easy to build pipelines with pluggable functionality - think e.g. switching an LLM provider on the fly.

If you haven't looked into Metaflow recently, configuration management is another big feature that was contributed by the team at Netflix: https://netflixtechblog.com/introducing-configurable-metaflo...

Many folks love the new native support for uv too: https://docs.metaflow.org/scaling/dependencies/uv

I'm happy to answer any questions here



Is it common to see Metaflow used alongside MLflow if a team wants to track experiment data?


Metaflow tracks all artifacts and allows you to build dashboards with them, so there’s no need to use MLFlow per se. There’s a Metaflow integration in Weights and Biases, CometML etc, if you want pretty off-the-shelf dashboards




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