Python

Airflow 3.0 isn’t just an upgrade; it’s a rewrite. From the new Execution API to the renaming of Datasets to Assets, here is what matters for the modern Data Engineer.

🔗 GitHub Repository: prashant-fintech/risklab 🚀 Live Demo: risklab.streamlit.app In quantitative finance, the quality of your risk engine is only as good as the data feeding it. Before we can calculate Value at Risk (VaR) or run stress tests, we need a robust, standardized way to ingest, align, and clean financial time series. Post 01 establishes the Market Data Core for RiskLab. Instead of writing ad-hoc pandas scripts for every new model, we have built a reusable “kernel” that enforces strict data contracts and handles the messy reality of financial data—missing observations, different time zones, and market holidays. ...