Competitive Python
1.0.0
competitivepython is an open-source library of algorithms and data structures implemented in Python. It offers a collection of frequently used algorithms and data structures that can be directly used in any Python-based project.
To install competitivepython library, simply run the following command:
pip install competitivepython
To use competitivepython in your project, import the desired algorithm or data structure and use it as needed. Below are some example use cases:
Implementing searches:
from competitivepython import searches
arr = [1, 2, 3, 4, 5]
target = 3
result = searches.binary_search(arr, target)
print("Binary Search:",result)
'''Output:
Binary Search: 2
'''
from competitivepython import searches
arr = [5, 7, 9, 2, 4, 10]
target = 4
result = searches.linear_search(arr, target)
print("Linear Search:",result)
'''Output:
Linear Search: 4
'''
from competitivepython import searches
txt = "ABABDABACDABABCABAB"
pat = "ABABCABAB"
result = searches.kmp_search(pat,txt)
print("KMP Search:",result)
'''Output:
KMP Search: [10]
'''
Implementing sorting:
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.bubble_sort(arr)
print('bubble sort:', result)
''' Output ---
bubble sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.bucket_sort(arr)
print('bucket sort:', result)
''' Output ---
bucket sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.heap_sort(arr)
print('heap sort:', result)
''' Output ---
heap sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.insertion_sort(arr)
print('insertion sort:', result)
''' Output ---
insertion sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.merge_sort(arr)
print('merge sort:', result)
''' Output ---
merge sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.quick_sort(arr)
print('quick sort:', result)
''' Output ---
quick sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.radix_sort(arr)
print('radix sort:', result)
''' Output ---
radix sort: [6, 7, 12, # 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.selection_sort(arr)
print('selection sort:', result)
''' Output ---
selection sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.shell_sort(arr)
print('shell sort:', result)
''' Output ---
shell sort: [6, 7, 12, 15, 112]
'''
from competitivepython import sorting
arr = [112, 6, 7, 12, 15]
result = sorting.tim_sort(arr)
print('tim sort:', result)
''' Output ---
tim sort: [6, 7, 12, 15, 112]
'''
Implementing graphs:
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')
print("bfs:",result)
''' Output--
bfs: {'B', 'D', 'C', 'A'}
'''
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.depth_first_search(graph, 'C')
print("dfs:",result)
''' Output--
dfs: {'B', 'D', 'C', 'A'}
'''
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.dijkstra(graph, start, end)
print("dijikstra:",result)
''' Output--
dijikstra: {'distance': 4, 'path': ['B', 'C', 'D']}
'''
Implementing trees:
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]
If you would like to contribute to the competitivepython project, please refer to the contributing guidelines in CONTRIBUTING.md. We welcome contributions of all types, including bug reports, feature requests, and code contributions.
competitivepython is open source software released under the MIT license. Refer to the LICENSE file for more information.
