Using Python’s multiprocessing module inside Jupyter Notebook often results in errors like:

AttributeError: Can't get attribute 'function_name' on <module '__main__'>

This happens because Jupyter runs code in an interactive environment - iPython that does not behave the same way as a standard Python script.

Below are the most reliable ways to fix this issue.

The most stable fix is to define your worker functions in a separate Python file and import them into your notebook.

Step 1: Create a Python file (worker.py)

# worker.py
def worker_func(x):
    return x * 2

Step 2: Import and use in Jupyter

from multiprocessing import Process, Queue
import worker

if __name__ == "__main__":
    q = Queue()
    p = Process(target=worker.worker_func, args=(5,))
    p.start()
    p.join()

This makes the function importable and avoids the AttributeError.

Solution 2: Use if name == "main"

Always guard multiprocessing code with:

if __name__ == "__main__":
    ...

This is required so child processes can safely import the main module.

Alternative: Use Threading or Joblib

For notebook-friendly parallelism, consider library: joblib:

  • concurrent.futures.ThreadPoolExecutor
  • joblib.Parallel
  • Running multiprocessing code from a standalone .py script

first install it by:

pip install joblib

Example:

from joblib import Parallel, delayed


def f(x):
    return x + x

res = Parallel(
    n_jobs=5
)(
    delayed(f)(x) for x in [1, 2, 3, 4, 5]
)

Why multiprocessing Fails in Jupyter

Jupyter notebooks execute code in a dynamic __main__ context. On platforms like Windows (and sometimes macOS), the spawn start method is used, which requires functions to be importable from a module. Functions defined directly in notebook cells cannot always be pickled and imported by worker processes.

Tips

For production or heavy multiprocessing:

  • Run code as a normal Python script, not inside Jupyter
  • Keep worker functions in importable modules
  • Use Jupyter mainly for prototyping and analysis

Summary

  • Jupyter + multiprocessing can cause AttributeError
  • Define worker functions in a separate .py file
  • Always use if name == "main"
  • Prefer standalone scripts for reliable multiprocessing

This approach avoids common pickling and import issues and ensures consistent multiprocessing behavior across platforms.

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