Binance Order Book API for Python Backtesting
A Python-focused guide to using Binance order book data for BTC/USDT backtests and Polymarket cross-market strategy research.
Binance order book API for Python is a common search from developers who want to move beyond OHLCV candles. For backtesting, the important step is not only fetching a current depth snapshot, but working with historical depth that can be replayed beside strategy signals.
Python Backtest Workflow
- Choose a BTC Up/Down market or a BTCUSDT time window.
- Load historical Binance spot and futures order book depth.
- Compute spread, mid price, and depth imbalance features.
- Align those features with Polymarket order book snapshots.
- Simulate fills using bid/ask depth instead of midpoint prices.
Useful Columns
- timestamp
- symbol
- venue or market type
- best bid and best ask
- bid levels and ask levels
- spread, mid price, and depth imbalance
Why Historical Depth Beats Current Depth
Current order book endpoints are useful for live systems, but they cannot backfill yesterday's book. For backtesting, you need a historical series that lets Python replay the exact book state around each signal.