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Abstract: While it's technically possible to use multithreading in Python CGI scripts, it's generally not recommended and can lead to unexpected behavior.  Here's why: Challenges: Global Interpreter Lock (GIL): Python's GIL prevents multiple threads from executing Python bytecode simultaneously. This means that true parallelism can't be achieved for CPU-bound tasks. CGI Environment: The CGI environment is designed for short-lived processes. Using threads can introduce complexities in managing the lifecycle of threads within the CGI request-response cycle. Resource Contention: Multiple threads accessing shared resources (like files or databases) can lead to race conditions and data corruption. Alternatives: Multiprocessing: If your task is CPU-bound, consider using the multiprocessing module, which creates separate processes that can truly execute in parallel. Asynchronous Programming: For I/O-bound tasks, consider using asynchronous libraries like asynci...