pymatch — live order book

A real simulated session through the pymatch matching engine: background market flow plus an inventory-skewed market maker, 500 µs exchange latency, maker/taker fees. Depth is the top 10 levels per side. Code on GitHub

–midprice (ticks)
–spread (ticks)
–maker P&L (ticks)
–sim time
1×

Trade tape (most recent first)

What am I looking at?

Green bars are resting bid (buy) liquidity, red bars are ask (sell) liquidity, centered on the midprice. Every frame is a real snapshot from the Python engine — no mock data. The market maker's P&L is marked to the midprice each frame. Trades marked MM are the strategy's fills.

Run it yourself

pip install pymatch
python -c "
from pymatch import MarketConfig, MarketMaker, run_backtest
r = run_backtest(MarketMaker, MarketConfig(steps=3000, seed=7))
print('P&L:', r.final_cash_ticks, 'ticks | Sharpe:', round(r.sharpe(), 2))
"