black fixes and Travis CI fixes (#2160)

* black format

* updating DIRECTORY.md

* fixes

* fixup! Format Python code with psf/black push

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
This commit is contained in:
vinayak 2020-07-02 20:02:15 +05:30 committed by GitHub
parent c534e77cb1
commit 2d3d660155
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7 changed files with 11 additions and 43 deletions

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@ -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)

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@ -102,4 +102,4 @@ if __name__ == "__main__":
import doctest
doctest.testmod()
main()
# main()

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@ -4,7 +4,7 @@ from typing import List
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])):

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@ -5,24 +5,9 @@ Finding connected components in graph
"""
test_graph_1 = {
0: [1, 2],
1: [0, 3],
2: [0],
3: [1],
4: [5, 6],
5: [4, 6],
6: [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: [],
}
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:

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@ -5,22 +5,9 @@ Finding strongly connected components in directed graph
"""
test_graph_1 = {
0: [2, 3],
1: [0],
2: [1],
3: [4],
4: [],
}
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_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:

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@ -35,9 +35,7 @@ class TestClass(unittest.TestCase):
# 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):
"""

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@ -80,10 +80,7 @@ the third document in the corpus.")
) # 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: