Data & Infrastructure
Web Scraping Data Pipelines: Schema Validation, De-duplication & DB Loading
Design resilient ETL scraping pipelines with Pydantic validation, hash-based de-duplication, and idempotent PostgreSQL upserts.
Idempotent Database Loading with SQL Upsert
Ensure scraped records do not create duplicates on repeated runs by using unique constraints and `ON CONFLICT (source_url) DO UPDATE` clauses.
Related Technical Guides
Deepen your understanding with these closely related production architectures and tutorials:
Supabase pgvector Guide: Vector Search, HNSW Indexing & Cosine Distance in PostgreSQL
Build enterprise semantic search directly inside PostgreSQL using Supabase pgvector, HNSW indexing, and cosine distance operators.
Hybrid Search with BM25 & Vector pgvector: Reciprocal Rank Fusion (RRF)
Combine the precision of full-text BM25 keyword matching with dense semantic embeddings using Reciprocal Rank Fusion (RRF).
RAG Chunking Strategies: Fixed Size, Semantic Chunking & Markdown Hierarchy
Master document chunking: character splitting, semantic boundary detection, and table/header-aware recursive splitting.