Kedro VS Prefect

Interesting, thanks for sharing. I'll definitely take a look, although at this point I am so comfortable with Snakemake, it is a bit hard to imagine what would convince me to move to another tool. But I like the idea of composable pipelines: I am building a tool (too early to share) that would allow to lay Snakemake pipelines on top of each other using semi-automatic data annotations similar to how it is done in kedro (https://github.com/kedro-org/kedro).

# pyproject.toml [project] dependencies = [ "kedro @ git+https://github.com/kedro-org/kedro@3ea7231", "kedro-datasets[pandas.CSVDataSet,polars.CSVDataSet] @ git+https://github.com/kedro-org/kedro-plugins@3b42fae#subdirectory=kedro-datasets", ]

So there's 2 sides to pipeline management: the actual definition of the pipelines (in code) and how/when/where you run them. Some tools like prefect or airflow do both of them at once, but for the actual pipeline definition I'm a fan of https://kedro.org. You can then use most available orchestrators to run those pipelines on whatever schedule and architecture you want.

We have set up a milestone on GitHub so you can check in on our progress and contribute if you want to. To suggest features to us, report bugs, or just see what we're working on right now, visit the Kedro projects on GitHub.

you could use a project framework like kedro to force you to be more disciplined about how you structure your projects. I'd also recommend checking out this book: Edna Ridge - Guerrilla Analytics: A Practical Approach to Working with Data

Recently I started a position as Developer Advocate for Kedro, an opinionated data science framework, and one of the things we're doing is exploring what are the best open source tools we can use to create our documentation.

You can also check out Kedro, it’s like the Flask for data science projects and helps apply clean code principles to data science code.

An often overlooked framework used by NASA among others is Kedro https://github.com/kedro-org/kedro. Kedro is probably the simplest set of abstractions for building pipelines but it doesn't attempt to kill Airflow. It even has an Airflow plugin that allows it to be used as a DSL for building Airflow pipelines or plug into whichever production orchestration system is needed.

If I was answering this question but for python, I'd recommend something like prefect, boto3, or tortoise-orm -- not extremely complex and with a pretty comprehensible featureset.

However, if you are looking for something like this, but much more mature and something of a bloat to be frank, there's Prefect. Honestly, woflo borrows a lot from Prefect conceptually.

Disclaimer: I work for Prefect.

It looks like we added cron and other schedule types to the deployment CLI just under a month ago[1].

Over the last couple of releases, we've also made it easier to pull deployments from GitHub or bake your flow code into Docker images instead of needing S3-like storage.

As with any product, there's always more to do, so I appreciate you sharing your thoughts. More than anywhere else I've worked, community feedback is a huge driver of product enhancements and feature development. Feel free to join our Slack community[2] if you'd like to share more feedback or ask questions.

[1] https://github.com/PrefectHQ/prefect/blob/main/RELEASE-NOTES...

GitHub Action for running Prefect commands using the Prefect CLI.