Lythonic
Compose Python functions into data-flow pipelines
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I was thinking about something like this for years, few trys before this. Started this repo last year and I think I got something that usable now.Async framework, mix sync/async python functions, compose them into DAGs, run them, schedule them, persist data between steps or let it flow just in memory.GitHub: https://github.com/walnutgeek/lythonicDocs: https://walnutgeek.github.io/lythonic/PyPI: pip install lythonicIt is dataflow. So theoretically you can compose it with pure functions only. Lythonic requires annotations for params and returns to wire up outputs with inputs. All data saved in sqlite as json for now, and it would work for some amount of data ok.You may use it as task flow keeping params and returns empty and maintaining all data outside of the flow.But practically you may do well with some middle ground, just flow metadata thru, enough to make your function calls reproducible and keep some system of records that you can query reliably.Anyway I will stop rambling ... soon.Python 3.11+ MIT License. Minimal dependencies: Pydantic, Pyyaml, CroniterPrepping for v0.1. Looking of feedback. v0.0.14 is out. Claude generated reasonable docs. Sorry, I would not be able to do it better. I am working on Web UI and practical E2E example app as well.Thank you. -Sergey
HN · launched Apr 13, 2026 · 5 upvotes (top 89%) · 0 views
Niche: data parsing libraries and tools · 71 launches, 1 in the last 7 days · Explore this niche →
Category and tags
- Horizontal
- Workflow automation
- Developer
- Not AI
- Hobby / open-source project
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More like this: all 71 launches in data parsing libraries and tools →
Could you build this?
Yes Writing an async/sync DAG pipeline runner in Python is a classic software pattern that AI assistants can readily generate using standard topological sort and asyncio constructs.
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Competitors
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Attention rank: #153 of 167 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 161 days after the earliest competitor.
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