I want my existing scalping ideas turned into a production-ready Python algorithm that runs 24/7 on an AWS EC2 instance. The code must pull real-time market data through Dhan’s WebSocket feed, place and manage orders via the Dhan API Gateway / Order Router pipeline, and reach NSE servers with minimal latency. Here is the full flow I need you to wire together: live data → strategy logic (kept private for now) → order execution with dynamic stop-loss and target management → detailed logging → performance reporting pushed to Excel/Google Sheets and instant Telegram alerts. Robust error handling, reconnect logic, and latency monitoring are essential so the bot can trade unattended. Deliverables: • Clean, well-documented Python code packaged for one-click deployment on my EC2 instance • Configuration files or environment variables for API keys, symbols, quantity, SL/target ratios, etc. • Logging system that stores raw ticks, order responses, and P&L in timestamped files • Lightweight dashboard or scripts that export session stats to a spreadsheet and fire Telegram messages in real time • A brief hand-off session walking me through setup, parameters, and how to tweak the private scalping rules without touching the core infrastructure I work exclusively with a scalping style, so every millisecond matters. If you have prior experience building low-latency trading bots on Dhan (or similar brokers) and can demonstrate solid WebSocket handling, let’s talk.