Does `concurrent.futures.ProcessPoolExecutor()` have any restriction on number of processes? - python-3.x

Question

I wrote a simple code using concurrent.futures.ProcessPoolExecutor() whihc you can see in below. I'm using Python 3.7.4 on Windows 10 (64 bit) on a Core-i7 laptop.
import time
import concurrent.futures
def f(x):
lo = 0
for i in range(x):
lo += i
return(lo)
n = 7
if __name__ == '__main__':
t1 = time.perf_counter()
with concurrent.futures.ProcessPoolExecutor() as executor:
Ans = [executor.submit(f, 10**7-i) for i in range(n)]
for f in concurrent.futures.as_completed(Ans):
print(f.result())
t2 = time.perf_counter()
print('completed at', t2-t1, 'seconds')
The variable n determines how many processes is going to execute. When I set n to 1, 2, 4, 7 everything work fine. For example the output for n=7 is
49999995000000
49999955000010
49999965000006
49999985000001
49999975000003
49999945000015
49999935000021
completed at 2.0607623 seconds
However for n=10 it gives the following error!
49999945000015
49999955000010
49999965000006
concurrent.futures.process._RemoteTraceback:
"""
Traceback (most recent call last):
File "E:\Python37\lib\multiprocessing\queues.py", line 236, in _feed
obj = _ForkingPickler.dumps(obj)
File "E:\Python37\lib\multiprocessing\reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
_pickle.PicklingError: Can't pickle <function f at 0x00000285BFC4E0D8>: it's not the same object as __main__.f
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "e:/Python37/Python files/Parallel struggle/Python_20191219_parallel_3.py", line 23, in <module>
print(f.result())
File "E:\Python37\lib\concurrent\futures\_base.py", line 428, in result
return self.__get_result()
File "E:\Python37\lib\concurrent\futures\_base.py", line 384, in __get_result
raise self._exception
File "E:\Python37\lib\multiprocessing\queues.py", line 236, in _feed
obj = _ForkingPickler.dumps(obj)
File "E:\Python37\lib\multiprocessing\reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
_pickle.PicklingError: Can't pickle <function f at 0x00000285BFC4E0D8>: it's not the same object as __main__.f
Why some of the processes get done if something is wrong with the code? And what has happened that an error comes up? And is it specific to python on windows? Is it about the number of CPUs?