Add an example for a chasing distributable

examples/chase_example.py

@@ -0,0 +1,52 @@
+from os import path
+import sys
+# Append to path so that this script can access the dipla package
+sys.path.append(path.abspath('../dipla'))
+
+from dipla.api import Dipla
+
+# This example finds the number of rows away from the bottom that a
+# one exists in a grid. Normally this would require processing a whole
+# row before the program can start on the next row, using the
+# information from the previous row. This one sends the first half of a
+# row as soon as it finds it so that the a worker can start on the next
+# stage of processing
+
+@Dipla.chasing_distributable(count=2, chasers=5)
+def rows_since_found(row, last_calculated, index, count):
+    interval = len(row)//count
+    # If we are in the first row, return 1 if we found a 1 and zero
+    # otherwise
+    if last_calculated == None:
+       if interval*index + interval >= len(row):
+           return row[index*interval:]
+       else:
+           return row[index*interval:index*interval+interval]
+    # If we're not on the first row, increase each number by 1 so that
+    # in the end we'll have values for how far away from the bottom each
+    # one was
+    else:
+        last = last_calculated
+        out = []
+        for i in range(len(last)):
+            if last_calculated[i] == 0:
+                out.append(row[i+interval*index])
+            else:
+                out.append(last[i] + 1)
+
+        return out
+
+grid = [
+  [1, 0, 0, 0, 0, 0],
+  [0, 1, 0, 0, 0, 0],
+  [0, 0, 1, 0, 0, 0],
+  [0, 0, 0, 1, 0, 0],
+  [0, 0, 0, 0, 1, 0]
+]
+
+results = Dipla.apply_distributable(rows_since_found, grid)
+out = Dipla.get(results)
+outlist = []
+for o in out:
+    outlist = outlist + o
+print(outlist)