My tool generates 3D objects composed of separate, functional parts
Generates editable Blender scripts instead of monolithic mesh blobs.
Lightweight pythonic toolkit for building complex workflows.
Type-annotation wiring for DAGs when Prefect requires more setup.
Python developers building data pipelines and workflows
Prefect · Dagster · Airflow
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/lythonic
Docs: https://walnutgeek.github.io/lythonic/
PyPI: pip install lythonic
It 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, Croniter
Prepping 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
Generates editable Blender scripts instead of monolithic mesh blobs.
Tower-style middleware stacking for inference guardrails beats bolted-on if-statements.
Nine years of predicate logic distilled into a zero-dependency Python DSL.
Compile-time pipeline maps for Rust, but author says don't ship it yet.
Python port of Pts.js with visual composability as the core hypothesis.
Polished ecosystem but 'self-improving' claim is marketing, not architecture.