Python based automated trading-analysis solution, using live-historical data from Indian brokers' APIs -- 2

Hi, Thanks for showing interest in this work. (I have revised scope of this assignment; have cancelled earlier posted project.) I need proper working codes (with appropriate comments) for below-mentioned, for multiple scrips, across exchanges....(Brokers provide Python standard SDKs) Stage 1. - Automate establishing connection thru API keys/ available means - Getting live feed from brokers api thru Websocket. - storing the live data - convert feed data into diff timeframes to store/ analyse - store historical data across timeframes given by broker. -- Entire data to be stored on desktop (No paid storage pls.). 2. - Execute automated trades (market- limit- SL orders) using 2 sample trade setups, within set time period window. Both setups can run simultaneously across selected scrips. - Position sizing trades. - Trail SLs, part book profits - Option to set limit on max no. of open orders/ exposure - Auto sq off all open trades, at predefined time - Continuous monitoring and adjustments of the orders. - Error to be thrown if there is disconnection from broker/ exchange/ any glitch. Provision to send alert (thru either telegram/ wsap/ messg), once orders are placed/squared off/ glitches. Please note: - You need not create any trading strategy. We shall use 2 sample strategies e.g. based price-volume-oi or inter scrip price action. - I need proper efficient solution (best practices), workable across brokers having Rest APIs n Websocket data feed. We shall check with 2 brokers, who provide Python SDKs. - You should write code on your pc and share, which I shall run & test. I can not share my API keys/ OTP/ pwd. Thanks Pankaj