clean up repo.

add more notes

chapter9/README.md

@@ -2,4 +2,4 @@
 
 -   Dijkstra's algorithm works when all weights are non-negative
     -   If there are negative weights use Bellman-Ford.
--   Priority queue + min heap is optimal when compared to a function that operates on a list.
+-   The book demonstrates a function that operates on a list. Priority queue + min heap added for completeness.

chapter9/examples/heaptest.py

@@ -1,10 +0,0 @@
-import heapq
-
-customers = []
-heapq.heappush(customers, (2, "Harry"))
-heapq.heappush(customers, (3, "Charles"))
-heapq.heappush(customers, (1, "Riya"))
-heapq.heappush(customers, (4, "Stacy"))
-
-while customers:
-    print(heapq.heappop(customers))

chapter9/examples/list.py

@@ -1,14 +0,0 @@
-customers = []
-customers.append((2, "Harry"))  # no sort needed here because 1 item.
-customers.append((3, "Charles"))
-customers.sort(reverse=True)
-# Need to sort to maintain order
-customers.append((1, "Riya"))
-customers.sort(reverse=True)
-# Need to sort to maintain order
-customers.append((4, "Stacy"))
-customers.sort(reverse=True)
-
-while customers:
-    print(customers.pop(0))
-# Will print names in the order: Stacy, Charles, Harry, Riya.

chapter9/examples/priorityqueuetest.py

@@ -1,12 +0,0 @@
-from queue import PriorityQueue
-
-customers = (
-    PriorityQueue()
-)  # we initialise the PQ class instead of using a function to operate upon a list.
-customers.put((2, "Harry"))
-customers.put((3, "Charles"))
-customers.put((1, "Riya"))
-customers.put((4, "Stacy"))
-
-while customers:
-    print(customers.get())