Use map and views to streamline the workflow

multiprocessing/work-distribution/solution/pool-of-workers.py

@@ -17,14 +17,11 @@ def average(chunk):
 # split into tasks
 tasks = []
 for i in range(0, len(pdb), n):
-    chunk = pdb.coordinates[i:i+n].copy()
+    chunk = pdb.coordinates[i:i+n]
     tasks.append(chunk)
 
-# submit each task to the pool
-results = []
-for chunk in tasks:
-    res = pool.apply_async(average, [chunk])
-    results.append(res)
+# submit tasks to the pool
+result = pool.map(average, tasks)
 
 # wait for all tasks to finish
 pool.close()
@@ -33,14 +30,13 @@ def average(chunk):
 # collect results
 averages = []
 weights = []
-for res in results:
-    avg, w = res.get()
+for avg, w in result:
     averages.append(avg)
     weights.append(w)
 averages = array(averages)
 weights = array(weights, ndmin=2)
 
 # calculate the center of coordinates
 origo = sum(averages * weights.T) / len(pdb)
-print origo
+print(origo)