A collection of algorithms for competitive programming
Project description
Competitive Programming Algorithm Library in Python
competitivepython is a library of algorithms and data structures implemented in Python. It is designed to be a useful resource for developers who need to implement common algorithms and data structures in their projects.
Features
- Implements a wide range of algorithms and data structures, including:
- Searches: Binary Search, Linear Search, KMP Pattern Search
- Graphs: BFS, DFS, Dijkstra
- Sorting: Bubble Sort, Insertion Sort, Shell Sort, Selection Sort, Bucket Sort, Merge Sort, Tim Sort, Quick Sort, Heap Sort, Radix Sort
- Trees: Binary Search Tree
- Easy to use and understand, with well-documented code
- Portable and compatible with Python 3
- Open source and available under the MIT license
Installation
To install competitivepython library, simply run the following command:
pip install competitivepython
Usage
To use PyPy in your project, simply import the desired algorithm or data structure and use it as needed. For example:
-
searches implementation example
from competitivepython import searches result = searches.binary_search([1, 2, 3, 4, 5], 3) result2 = searches.linear_search([5, 7, 9, 2, 4, 10], 4) txt = "ABABDABACDABABCABAB" pat = "ABABCABAB" result3 = searches.kmp_search(pat,txt) print(result) # Output: 2 print(result2) # Output: 4 print(result3) # Output: [10]
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sorting implementation example
from competitivepython import sorting arr = [112, 6, 7, 12, 15] res = sorting.bubble_sort(arr) res1 = sorting.bucket_sort(arr) res2 = sorting.heap_sort(arr) res3 = sorting.insertion_sort(arr) res4 = sorting.merge_sort(arr) res5 = sorting.quick_sort(arr) res6 = sorting.radix_sort(arr) res7 = sorting.selection_sort(arr) res8 = sorting.shell_sort(arr) res9 = sorting.tim_sort(arr) print('bubble sort:', res, 'bucket sort:', res1, 'heap sort:', res2, 'insertion sort:', res3, 'merge sort:', res4, 'quick sort:', res5, 'radix sort:', res6, 'selection sort:', res7, 'shell sort:', res8, 'tim sort:', res9) ''' Output --- bubble sort: [6, 7, 12, 15, 112] bucket sort: [6, 7, 12, 15, 112] heap sort: [6, 7, 12, 15, 112] insertion sort: [6, 7, 12, 15, 112] merge sort: [6, 7, 12, 15, 112] quick sort: [6, 7, 12, 15, 112] radix sort: [6, 7, 12, # 15, 112] selection sort: [6, 7, 12, 15, 112] shell sort: [6, 7, 12, 15, 112] tim sort: [6, 7, 12, 15, 112] '''
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graphs implementation example
from competitivepython import graphs graph = { 'A': {'B': 1, 'C': 4}, 'B': {'A': 1, 'C': 2, 'D': 5}, 'C': {'A': 4, 'B': 2, 'D': 1}, 'D': {'B': 5, 'C': 1}, } start = 'A' end = 'D' result = graphs.breadth_first_search(graph, 'C') result2 = graphs.depth_first_search(graph, 'C') result3 = graphs.dijkstra(graph, start, end) print("bfs:",result) print("dfs:",result2) print("dijikstra:",result3) ''' Output-- bfs: {'B', 'D', 'C', 'A'} dfs: {'B', 'D', 'C', 'A'} dijikstra: {'distance': 4, 'path': ['B', 'C', 'D']} '''
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trees implementation example
from competitivepython import trees # Create an instance of the BinarySearchTree bst = trees.BinarySearchTree() # Insert some values into the tree bst.insert(50) bst.insert(30) bst.insert(20) bst.insert(40) bst.insert(70) bst.insert(60) bst.insert(80) # Check if a value is present in the tree print(bst.search(50)) # Output: True print(bst.search(35)) # Output: False # Get the values in the tree in in-order traversal order print(bst.get_in_order_traversal()) # Output: [20, 30, 40, 50, 60, 70, 80]
Contributing
If you would like to contribute to the competitivepython project, please refer to the contributing guidelines. We welcome contributions of all types, including bug reports, feature requests, and code contributions.
License
competitivepython is open source software released under the MIT license. Refer to the LICENSE file for more information.
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