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Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>

dynamic_programming/fractional_knapsack.py

@@ -1,5 +1,5 @@
-from itertools import accumulate
 from bisect import bisect
+from itertools import accumulate
 
 
 def fracKnapsack(vl, wt, W, n):

dynamic_programming/max_sub_array.py

@@ -73,9 +73,10 @@ if __name__ == "__main__":
     A random simulation of this algorithm.
     """
     import time
-    import matplotlib.pyplot as plt
     from random import randint
 
+    from matplotlib import pyplot as plt
+
     inputs = [10, 100, 1000, 10000, 50000, 100000, 200000, 300000, 400000, 500000]
     tim = []
     for i in inputs:

dynamic_programming/optimal_binary_search_tree.py

@@ -16,9 +16,7 @@
 # frequencies will be placed near the root of the tree while the nodes
 # with low frequencies will be placed near the leaves of the tree thus
 # reducing search time in the most frequent instances.
-
 import sys
-
 from random import randint