Python Expert Needed to Stabilize High-Speed SMTP Proxy & Parallel Worker System

I need an experienced Python developer with very strong knowledge of proxies, SMTP connections, and parallel/concurrent workers to fix and stabilize my existing bulk.py script. The script is already designed to send as fast as possible, so the current speed and performance must be preserved. I do not want a solution that simply reduces concurrency or slows everything down to hide the problem. At the moment, workers can fail for different reasons, including: * 421 - No more parallel connections from your address allowed * Your IP address is blocked * SMTP / connection timeouts * Proxy disconnected * Proxy connection failure * SMTP connection failure * Other network-related worker failures I need someone who can analyze the whole connection/proxy architecture, not just patch one specific error. Main requirements * You must understand proxies 100%, especially proxy assignment, rotation and lifecycle with parallel workers. * Strong experience with SMTP connections, SMTP limits, IP restrictions and connection management. * Strong understanding of parallelism / concurrency / workers in Python. * The script must continue sending as fast as possible. * I do not want workers randomly dying because of proxy/network problems. * Timeouts must be handled correctly. * Disconnected or blocked proxies must be detected and handled properly. * Proxy/IP usage must be coordinated correctly between parallel workers. * SMTP connections, retries, cleanup and worker recovery must be handled properly. * The solution must distinguish between SMTP/account problems, proxy problems, IP blocks and temporary network errors. Very important Once an SMTP account successfully connects, its sending quota is used during that run. Because of that, a bad proxy, timeout, disconnected proxy, blocked IP, unnecessary reconnect or worker crash can waste the SMTP account/quota. I need the script to handle these situations intelligently without sacrificing sending speed. Before we start I will first send you the existing bulk.py script. Before making any changes, I want you to review the complete script and give me your technical assessment first. Your review must explain: * What problems you see in the current implementation * What is causing the worker failures * How the proxies are currently being managed * Whether proxy assignment/rotation is correct * Whether the parallel/concurrency logic is correct * Whether SMTP connections are being managed correctly * Why IP-blocked, timeout and proxy-disconnected errors are happening * What exactly needs to be changed * Whether the current high-speed sending approach can be preserved I also want your proposed solution Do not only tell me what is wrong. After reviewing the script, explain exactly how you would fix it before you start coding. I want to know: * How you would redesign/fix the proxy handling * How a worker should react when its proxy disconnects * How a worker should react when an IP becomes blocked * How you would handle connection timeouts * How you would prevent multiple workers from conflicting on the same proxy/IP * How you would manage retries without wasting SMTP accounts * How you would recover a failed worker instead of simply terminating it * How you would manage SMTP reconnects and cleanup * What parts of the existing code you would modify * Why your approach will solve the problem * How you will keep the script running at maximum possible speed I want a clear technical plan, not just “I can fix it.” Do not rewrite or modify the script before giving me this review and proposed solution. Testing workflow After we agree on the approach, you will update the existing script and send me the updated version. I will test every version on my own server/environment and send you the results/errors. You will continue updating the script based on the real test results until it is stable. Please do not apply if you only have basic Python knowledge. I need someone experienced with: Python + SMTP + Proxies + Proxy Rotation + Parallel Workers + High-Speed Sending + Networking + Connection Management + Error Handling The final goal is a fast and stable bulk.py where workers recover properly from blocked IPs, proxy disconnections, timeouts and other network failures instead of randomly failing.