Python NSE Scalping Algorithm

I need a Python-driven trading system that scalps equities and derivatives on the National Stock Exchange (NSE). The core logic will blend market-making techniques with price-action signals, working exclusively from live market data pulled through a low-latency feed or broker API.

The algorithm must:
• Subscribe to real-time order-book depth, trades and tick data.
• Calculate fair value and micro-price shifts to quote two-sided markets (market making) while simultaneously scanning candlestick patterns, breakouts and momentum cues (price action).
• Place, amend and cancel orders in milliseconds, respecting exchange throttles and broker limits.
• Apply position sizing, max-loss stops, and session P&L caps to keep risk tight.
• Log every decision and fill to a local database or flat files for later analysis.

Code in modern, well-commented Python 3, using popular libraries such as asyncio, websockets, pandas and NumPy. Wrap broker connectivity (e.g., Kite Connect, IIFL, Fyers or similar) behind clean interfaces so I can swap providers if needed. Unit tests and a short README should be included so I can spin the bot up quickly on my VPS or local machine.