Move your Python ingestion scripts to dltHub

Python scripts → dltHub is the most common migration we see now, driven by the rise of Claude, Cursor, and Codex. Raw Python scripts are infinitely flexible, and nobody wants to maintain them, especially now that agents generate them by the thousand.

You keep your custom logic and gain schema evolution, observability, and a runtime that ships to production. dlt is the match between standardization and customization: it has standardized 90% of data engineering tasks in Python code, in a way LLMs can understand and humans can still maintain.

The work that used to require senior engineers, reading the old scripts, mapping the schemas, rebuilding the logic, and validating the output, is codified into skills an agent runs, overseen by the engineers you already have. A senior-only, multi-month project becomes weeks of work at a fraction of the cost.

On dltHub, a persistent context layer captures schemas, lineage, traces, and runtime state in one place your coding agent reads from and writes to, ingest to deploy. It ships with agent configs for Claude, Codex, and Cursor.