Comment by therediterator

Thanks for your comment !

When you are doing parallelism, don't forget to protect the 'entry point' of the program by using "if __name__ == '__main__'", and also avoid the __main__.py file [1]

  # this file isn't `__main__.py` !
  from asyncpal import ProcessPool

  def square(x):
      return x**2

  if __name__ == "__main__":  # very important !
      with ProcessPool(4) as pool:
          numbers = range(1000)
          # note that 'map_all' isn't lazy
          iterator = pool.map(square, numbers)  # map is lazy
          result = tuple(iterator)
          assert result == tuple(map(square, numbers))

[1] https://discuss.python.org/t/why-does-multiprocessing-not-wo...