1) Missing main guard

Always use:

if __name__ == "__main__":
    pass

if __name__ == "__main__":
    pass

Without this, some environments will repeatedly spawn child processes.

2) Pickling errors

Multiprocessing needs to serialize (pickle) functions and data.

Avoid:

• lambdas
• nested functions
• open file handles
• database connections

Prefer:

• top-level functions
• simple data (numbers/strings/lists/dicts)

3) Oversubscribing CPUs

Creating too many processes can slow down your system.

Guidance:

• start with os.cpu_count()os.cpu_count()
• benchmark for your workloads

4) Returning huge data

Sending massive arrays through Queue can be slow.

Options:

• write output to files
• batch results
• aggregate inside workers

🧪 Try It Yourself

Exercise 1 – Start a Process

Exercise 2 – Process Pool map()

Exercise 3 – Multiprocessing Queue