Seven crypto exchanges, one normalized schema, ~700 lines of Python
📰 Dev.to · FoxyyyBusiness
Unify funding-rate data from 7 crypto exchanges into a single SQLite table using Python, and learn from the challenges of working with different exchange APIs
Action Steps
- Collect API documentation for Binance, Bybit, OKX, Bitget, MEXC, Hyperliquid, and Gate.io
- Create a Python script to fetch funding-rate data from each exchange using their respective APIs
- Handle API rate limits, errors, and inconsistencies for each exchange
- Design a normalized schema to store funding-rate data in a single SQLite table
- Implement data transformation and loading into the SQLite table using Python
- Test and validate the unified data for consistency and accuracy
Who Needs to Know This
Data engineers and cryptocurrency traders can benefit from this tutorial to streamline their data collection and analysis processes, and developers can learn from the experiences of working with various exchange APIs
Key Insight
💡 Normalizing data from multiple sources can be challenging due to API inconsistencies, but a unified schema can simplify analysis and decision-making
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📊 Unify crypto funding-rate data from 7 exchanges into 1 SQLite table using Python! 💻
Key Takeaways
Unify funding-rate data from 7 crypto exchanges into a single SQLite table using Python, and learn from the challenges of working with different exchange APIs
Full Article
A walkthrough of how I unified funding-rate data across Binance, Bybit, OKX, Bitget, MEXC, Hyperliquid, and Gate.io into a single SQLite table — and why each exchange API made me lose a little more faith in industry.
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