DuckLake in Python: The DuckDB Lakehouse Format (2026)
DuckLake 1.0 keeps table metadata in a real SQL database and data as Parquet on S3. A practical Python guide covering pyducklake, time travel, deployment, and where it beats Iceberg.
Python backend developer who came to data work via FastAPI. Bridges the messy world between APIs and pipelines.
DuckLake 1.0 keeps table metadata in a real SQL database and data as Parquet on S3. A practical Python guide covering pyducklake, time travel, deployment, and where it beats Iceberg.
A hands-on guide to FastAPI streaming in 2026 using native SSE, WebSockets, and NDJSON. Real production patterns for LLM APIs: disconnects, heartbeats, Nginx and Cloudflare buffering, and testing with httpx and k6.
IBM's open-source Docling library turns PDFs, DOCX, PPTX, XLSX, and HTML into clean Markdown or JSON for RAG. This 2026 guide covers install, table extraction, HybridChunker, LangChain and LlamaIndex integrations, plus how it stacks up to Unstructured and LlamaParse.
Instructor, Outlines, and Pydantic AI each solve structured LLM outputs a different way. Here is how to choose in 2026, with working code and FastAPI patterns.
PyIceberg 0.9 makes Apache Iceberg tables fully usable from pure Python. Walk through catalog setup, reads, appends, upserts, schema evolution, and time travel, plus how PyIceberg compares with Spark, Delta Lake, and Hudi for 2026 lakehouse work.
Build async ETL pipelines in Python using httpx and asyncio.TaskGroup with Pydantic V2 validation. Working code, retry policy, rate-limit handling, and the pitfalls that bite in production.