pathway
by pathwaycomPython ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
In simple words: mara-pipelines is a tool made for people who build software, for moving data automatically from one place to another. It is completely free and open source — its code is public on GitHub, where 2,091 people have bookmarked it as worth using.
💡 A real-life example: A shop's messy sales spreadsheet goes into a tool like this, and comes out as one clear chart showing which product actually makes money.
RepoEasy wrote this simple explanation from the project's public data — its category, topics and description — so a beginner can understand it before downloading anything. For exact technical details, the project's own README (linked below) is the final word.
A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
This is the project's own description from GitHub — we show it as-is rather than inventing details.
This project is listed under Data Pipelines in Data & Analytics, a category made for analysts, businesses, researchers and data-curious users.
Do I need coding knowledge? Coding Knowledge Recommended. (Estimate based on project type: A developer tool/library — setup usually follows the README with basic coding skills. Always confirm from the repo's README.)
The source code is released under the MIT license. Open-source licenses like this usually allow free use, including commercial use — but always read the actual license file in the repository before relying on it. Note: the code being free does not mean hosted services, APIs or infrastructure around it are free.
Activity level: Quiet · Last code update: 15 Dec 2023 · Created: 31 Mar 2018 · Open issues: 26
Official links: Releases ↗ · Documentation (README) ↗
We never publish installation steps we have not verified — the README above is the source of truth.
⭐ 2091 stars · 🍴 99 forks · 🐛 26 open issues · 💻 Language: Python · 📄 License: MIT · Default branch: main
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
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