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Add scoring rubric to README
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README.md

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@@ -6,6 +6,8 @@ For the algorithms portion of the sprint challenge, you'll be answering the ques
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## Data Structures
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It is recommended that you allot about 2 hours for this portion of the sprint challenge.
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### Task 1. Implement Depth-First and Breadth-First Traversal on the Binary Search Tree Class
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Navigate into the `ex1` directory in the `data_structures` directory. Inside, you'll see the `binary-search-tree.py` file with a complete implementation of the binary search tree class. Your first task is to implement the methods `depth_first_for_each` and `breadth_first_for_each` on the `BinarySearchTree` class:
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Open up the `Data_Structures_Answers.md` file. This is where you'll jot down your answers for the runtimes of the functions you just implemented. Be sure to also answer any other questions posed in the `Data_Structures_Answers.md` file!
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## Algorithms
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It is recommended that you allot about 1 hour for this portion of the sprint challenge.
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For the algorithms portion of the sprint challenge, you'll be answering questions posed in the `Algorithms_Questions.md` document inside the `algorithms` directory. Add your answers to the questions in the `Algorithms_Answers.md` file.
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## Rubric
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Each test in the Data Structures portion is worth 2 points. Each runtime analysis question in the Data Structures portion is worth 1 point.
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Each question in the Algorithms portion is worth 2 points.
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In order to earn a score of 3, you'll need to score at least 90%, or 18 / 20 total possible points.
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In order to earn a score of 2, you'll need to score at least 70%, or 14 / 20 total possible points.
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Anything lower earns you a score of 1.

data_structures/ex1/test_binary_search_tree.py

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self.assertEqual(arr, [5, 3, 10, 4, 9, 11])
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if __name__ == '__main__':
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unittest.main()

data_structures/ex2/test_heap.py

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self.assertEqual(len(output), length)
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self.assertTrue(is_sorted(output))
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if __name__ == '__main__':
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unittest.main()

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