black fixes and Travis CI fixes

DIRECTORY.md

@@ -205,6 +205,7 @@
   * [Max Non Adjacent Sum](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_non_adjacent_sum.py)
   * [Max Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sub_array.py)
   * [Max Sum Contiguous Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sum_contiguous_subsequence.py)
+  * [Minimum Cost Path](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_cost_path.py)
   * [Minimum Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_partition.py)
   * [Optimal Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/optimal_binary_search_tree.py)
   * [Rod Cutting](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/rod_cutting.py)
@@ -230,11 +231,11 @@
   * [Articulation Points](https://github.com/TheAlgorithms/Python/blob/master/graphs/articulation_points.py)
   * [Basic Graphs](https://github.com/TheAlgorithms/Python/blob/master/graphs/basic_graphs.py)
   * [Bellman Ford](https://github.com/TheAlgorithms/Python/blob/master/graphs/bellman_ford.py)
-  * [Bfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs.py)
   * [Bfs Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_shortest_path.py)
   * [Bidirectional A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_a_star.py)
   * [Bidirectional Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_breadth_first_search.py)
   * [Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search.py)
+  * [Breadth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_2.py)
   * [Breadth First Search Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_shortest_path.py)
   * [Check Bipartite Graph Bfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_bfs.py)
   * [Check Bipartite Graph Dfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_dfs.py)

ciphers/affine_cipher.py

@@ -102,4 +102,4 @@ def get_random_key():
     import doctest
 
     doctest.testmod()
-    main()
+    # main()

dynamic_programming/minimum_cost_path.py

@@ -4,7 +4,7 @@
 
 
 def minimum_cost_path(matrix: List[List[int]]) -> int:
-    '''
+    """
     Find the minimum cost traced by all possible paths from top left to bottom right in
     a given matrix
 
@@ -13,7 +13,7 @@ def minimum_cost_path(matrix: List[List[int]]) -> int:
 
     >>> minimum_cost_path([[2, 1, 4], [2, 1, 3], [3, 2, 1]])
     7
-    '''
+    """
 
     # preprocessing the first row
     for i in range(1, len(matrix[0])):

graphs/connected_components.py

@@ -5,24 +5,9 @@
 
 """
 
-test_graph_1 = {
-    0: [1, 2],
-    1: [0, 3],
-    2: [0],
-    3: [1],
-    4: [5, 6],
-    5: [4, 6],
-    6: [4, 5],
-}
-
-test_graph_2 = {
-    0: [1, 2, 3],
-    1: [0, 3],
-    2: [0],
-    3: [0, 1],
-    4: [],
-    5: [],
-}
+test_graph_1 = {0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}
+
+test_graph_2 = {0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}
 
 
 def dfs(graph: dict, vert: int, visited: list) -> list:

graphs/strongly_connected_components.py

@@ -5,22 +5,9 @@
 
 """
 
-test_graph_1 = {
-    0: [2, 3],
-    1: [0],
-    2: [1],
-    3: [4],
-    4: [],
-}
-
-test_graph_2 = {
-    0: [1, 2, 3],
-    1: [2],
-    2: [0],
-    3: [4],
-    4: [5],
-    5: [3],
-}
+test_graph_1 = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
+
+test_graph_2 = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
 
 
 def topology_sort(graph: dict, vert: int, visited: list) -> list:

greedy_method/test_knapsack.py

@@ -35,9 +35,7 @@ def test_negative_profit_value(self):
         # profit = [10, -20, 30, 40, 50, 60]
         # weight = [2, 4, 6, 8, 10, 12]
         # max_weight = 15
-        self.assertRaisesRegex(
-            ValueError, "Weight can not be negative.",
-        )
+        self.assertRaisesRegex(ValueError, "Weight can not be negative.")
 
     def test_negative_weight_value(self):
         """

machine_learning/word_frequency_functions.py

@@ -80,10 +80,7 @@ def document_frequency(term: str, corpus: str) -> int:
     )  # strip all punctuation and replace it with ''
     docs = corpus_without_punctuation.split("\n")
     term = term.lower()
-    return (
-        len([doc for doc in docs if term in doc]),
-        len(docs),
-    )
+    return (len([doc for doc in docs if term in doc]), len(docs))
 
 
 def inverse_document_frequency(df: int, N: int) -> float: