Data Pipeline Tutorial: CSV to JSON to Database in 30 Minutes
Build a simple end-to-end data pipeline: read a CSV, convert to JSON, validate records, and load into SQLite or PostgreSQL with Python.
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Data Pipeline Tutorial: CSV to JSON to Database in 30 Minutes This is a hands-on tutorial. You'll start with a raw CSV file, validate it, convert it to JSON, and upsert the data into PostgreSQL — with full working code you can run locally. The whole pipeline fits in a single Python script and a Makefile. No Airflow, no Spark, no infrastructure overhead. What you'll build: CSV validation with csvkit CSV → JSON conversion with type inference and null handling PostgreSQL upsert (insert-or-update) with conflict resolution Verification query to confirm the load Step 1: Get the Sample Data We'll use a realistic dataset: a CSV of product catalog data with 1000 rows, some null values, and inconsistent formatting. Create : Key messiness to handle: is missing on row 4 is missing on row 4 is a…
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