For a first version of my sports-data bot, I need a Python script that continuously polls seven or more REST APIs, normalises every response into a common JSON schema, then applies a simple surebet check (sum of 1/odds < 1). Whenever the condition is true, the bot must push a real-time alert to a specified Telegram chat. No scraping or machine-learning logic is required—just deterministic maths and robust data streaming. The flow I have in mind is: • Scheduled or event-driven calls to each public or key-secured endpoint, with sensible back-off to respect rate limits. • Fast in-memory merge of the markets returned (odds, scores, shots, etc.) so the algorithm can compare equivalent selections across bookmakers. • Calculation of the surebet metric on every update and, if it triggers, immediate Telegram notification that includes the bookmakers involved, the exact odds, and the timestamp. • Lightweight summary report—daily or on demand—containing the list of alerts sent, the markets concerned and a short performance log. A simple CSV or JSON file saved locally is sufficient for this first cut. The stack should stay pure Python; I am already comfortable running Docker but it is not mandatory. Asyncio, requests, httpx or any similar library is fine as long as latency stays low and error handling is graceful. Before you start coding, I would like a short call to be sure we both picture the same data model, naming conventions and alert format. Let me know your earliest availability and a rough outline of how you would structure the modules so we can lock the scope quickly.