Unable to send multiple arguments to concurrrent.futures.Executor.map()

Question

I am trying to combine the solutions provided in both of these SO answers - Using threading to slice an array into chunks and perform calculation on each chunk and reassemble th

Answer 1

Using the solution provided by user mkorvas as shown here - How to pass a function with more than one argument to python concurrent.futures.ProcessPoolExecutor.map()? I was able to solve my problem as shown in the solution here -

import psutil
import numpy as np
import sys
from concurrent.futures import ThreadPoolExecutor
from functools import partial

def main():
   testThread()

def testThread():

   minLat = -65.76892
   maxLat =  66.23587
   minLon =  -178.81404
   maxLon =  176.2949
   latGrid = np.arange(minLat,maxLat,0.05)
   lonGrid = np.arange(minLon,maxLon,0.05)
   print(latGrid.shape,lonGrid.shape)
   gridLon,gridLat = np.meshgrid(latGrid,lonGrid)
   grid_points = np.c_[gridLon.ravel(),gridLat.ravel()]
   print(grid_points.shape)
   n_jobs = psutil.cpu_count(logical=False)
   chunk = np.array_split(grid_points,n_jobs,axis=0)
   x = ThreadPoolExecutor(max_workers=n_jobs) 


  maxDistance = 4.3
  func = partial(performCalc,maxDistance)

  results = x.map(func,chunk)


 def performCalc(maxDistance,chunk):

     print(maxDistance)
     return chunk

main()

What apparently one needs to do(and I do not know why and maybe somebody can clarify in another answer) is you need to switch the order of input to the function performCalc()

as shown here -

      def performCalc(maxDistance,chunk):

          print(maxDistance)
          return chunk