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Michele De Vita
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‎.gitignore‎

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# PyBuilder
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target/
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.idea/

‎README.rst‎

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pip3 install pygorithm
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- | It's that easy. If you are using Python 2.7 use pip instead. Depending on your
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| permissions, you might need to ``sudo`` before installing
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| permissions, you might need to use ``pip install --user pygorithm`` to install.
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* Or you can download the source code from `here <https://github.com/OmkarPathak/pygorithm>`_, and then just install the package using
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::
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python setup.py install
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Quick Start Guide
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from pygorithm.sorting import bubble_sort
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time_complexity = bubble_sort.time_complexities()
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print(time_complexity)
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* To see all the available functions in a module. For example, if you want to see what all sorts are available in the sorting module, then just do
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.. code:: python
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>>> from pygorithm.sorting import modules
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>>> modules()
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['bubble_sort', 'bucket_sort', 'counting_sort', 'heap_sort', 'insertion_sort', 'merge_sort', 'quick_sort', 'selection_sort', 'shell_sort']
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Tests
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~~~~~
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* Just type in the following command to run the tests
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::
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python3 -m unittest
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* This will run all the tests defined in the files of the ``tests/`` directory
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Donation
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~~~~~~~~
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If you have found my softwares to be of any use to you, do consider helping me pay my internet bills. This would encourage me to create many such softwares :)
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- `PayPal <https://paypal.me/omkarpathak27>`_
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- `₹ (INR) <https://www.instamojo.com/@omkarpathak/>`_

‎TODO.md‎

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# TODO
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### Tree
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- [x] Binary Tree
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- [x] Binary Search Tree
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- [ ] Inorder to Preorder
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- [ ] Count Leaf Nodes
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### Graph
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- [x] Graph implementation
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- [x] Detect cycle in Graph
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- [x] Topological Sort
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- [ ] Prim's Algorithm
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- [ ] Kruskal's Algorithm
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### Dynamic Programming
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- [ ] Fibonacci
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- [ ] Longest Increasing Subsequence
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### Heap
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- [x] Heap implementation
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- [x] Heap Sort

‎docs/Data_Structure.rst‎

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===============
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Data Structures
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===============
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Implementing Data Structures purely in Python.
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Quick Start Guide
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-----------------
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.. code-block:: python
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# import the required data structure
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from pygorithm.data_structures import stack
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# create a stack with default stack size 10
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myStack = stack.Stack()
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myStack.push(2)
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# print the contents of stack
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print(myStack)
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Features
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--------
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* Data Structures implementations available:
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- **Stack**
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- Stack (data_structures.stack.Stack)
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- Infix to Postfix conversion (data_structures.stack.InfixToPostfix)
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- **Queue**
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- Queue (data_structures.queue.Queue)
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- Deque (data_structures.queue.Deque)
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- **Linked List**
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- Singly Linked List (data_structures.linked_list.SinglyLinkedList)
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- Doubly Linked List (data_structures.linked_list.DoublyLinkedList)
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- **Tree**
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- Binary Tree (data_structures.tree.BinaryTree)
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- Binary Seach Tree (data_structures.tree.BinarySearchTree)
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- **Graph**
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- Graph (data_structures.graph.Graph)
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- Topological Sort (data_structures.graph.TopologicalSort)
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- Check cycle in Directed Graph (data_structures.graph.CheckCycleDirectedGraph)
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- Check cycle in Undirected Graph (data_structures.graph.CheckCycleUndirectedGraph)
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- **Heap**
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- Heap (data_structures.heap.Heap)
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* Get the code used for any of the implementation
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.. code:: python
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from pygorithm.data_structures.stack import Stack
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myStack = Stack()
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print(myStack.get_code())
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* To see all the available functions in a module there is a `modules()` function available. For example,
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.. code:: python
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>>> from pygorithm.data_structures import modules
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>>> modules()
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['graph', 'heap', 'linked_list', 'queue', 'stack', 'tree']
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Stack
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-----
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.. automodule:: pygorithm.data_structures.stack
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Stack
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-----
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.. autoclass:: Stack
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:members:
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.. automodule:: pygorithm.data_structures.stack
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Stack
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-----
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.. autoclass:: InfixToPostfix
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:members:

‎docs/Fibonacci.rst‎

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=========
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Fibonacci
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=========
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Learning fibonacci implementations in few ways!
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Quick Start Guide
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-----------------
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.. code-block:: python
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from pygorithm.fibonacci import recursion as fib_recursion
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sequence = fib_recursion.get_sequence(10)
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print(sequence) # [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
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Features
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--------
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* Fibonacci implementations available:
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- Recursion
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- Cache (which saves some recursions to avoid computation of same series again and again)
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* Get the code used for any of the implementation
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.. code:: python
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from pygorithm.fibonacci import recursion as fib_recursion
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code = fib_recursion.get_code()
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print(code)
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* To see all the available functions in a module there is a `modules()` function available. For example,
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.. code:: python
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>>> from pygorithm.fibonacci import modules
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>>> modules()
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['cache', 'recursion']
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Implementations API
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-------------------
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* Functions and their uses
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.. function:: get_sequence(number)
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- **number** : arbitrary integer, that need to be calculated in Fibonacci number type
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- **Return Value** : return Fibonacci value by specified number as integer
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.. function:: get_code()
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- **Return Value** : returns the code for the ``get_sequence()`` function

‎docs/Minumum spanning tree.rst‎

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‎docs/Searching.rst‎

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Learning searching algorithms easily!
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-----------------
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Quick Start Guide
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-----------------
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# pre-requisite for binary search is that the list should be sorted
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myList.sort()
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# to search en element in the above list
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# to search an element in the above list
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index = binary_search.search(myList, 7)
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print(index)
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- Breadth First Search (breadth_first_search)
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- Depth First Search (depth_first_search)
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* To see all the available functions in a module there is a `modules()` function available. For example,
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.. code:: python
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>>> from pygorithm.searching import modules
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>>> modules()
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['binary_search', 'breadth_first_search', 'depth_first_search', 'linear_search', 'quick_select']
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* For Searching:
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Remember search() function takes two parameters as a sorted list and the target element to be searched.
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Remember ``search()`` function in `binary_search` module takes two parameters as a sorted list and the target element to be searched.
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# for printing the source code of bubble_sort
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Binary Search
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-------------
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* Functions and their uses
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.. function:: binary_search.search(List, key)
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:module: pygorithm.searching
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- **List** : *Sorted* list in which the key is to be searched
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- **key** : key to be searched in the list
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- **Return Value** : returns the position (index) of the key if key found, else returns -1
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.. function:: binary_search.time_complexities()
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- **Return Value** : returns time complexities (Best, Average, Worst)
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.. function:: binary_search.get_code()
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- **Return Value** : returns the code for the ``binary_search.search()`` function
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Linear Search
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-------------
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* Functions and their uses
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.. function:: linear_search.search(List, key)
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- **List** : the list in which item is to searched
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- **key** : key to be searched in the list
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- **Return Value** : returns the position (index) of the key if key found, else returns -1
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.. function:: linear_search.time_complexities()
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- **Return value** : returns time complexities (Best, Average, Worst)
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.. function:: linear_search.get_code()
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- **Return Value** : returns the code for the ``linear_search.search()`` function
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Breadth First Search
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--------------------
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* Functions and their uses
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.. function:: breadth_first_search.search(graph, startVertex)
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- **graph** : takes the graph data structures with edges and vertices
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- **startVertex** : it tells the function the vertex to start with
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- **Return Value** : returns the `set` of bfs for the ``graph``
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.. function:: breadth_first_search.time_complexities()
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- **Return Value** : returns time complexities
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.. function:: breadth_first_search.get_code()
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- **Return Value** : returns the code for the ``breadth_first_search.search()`` function
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Depth First Search
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------------------
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* Functions and their uses
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.. function:: breadth_first_search.search(graph, start, path)
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- **graph** : takes the graph data structures with edges and vertices
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- **start** : it tells the function the vertex to start with
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- **path** : returns the list containing the required dfs
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- **Return Value** : returns the `list` of dfs for the ``graph``
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.. function:: breadth_first_search.time_complexities()
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- **Return Value** : returns time complexities
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.. function:: breadth_first_search.get_code()
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- **Return Value** : returns the code for the ``depth_first_search.search()`` function
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Quick Select Search
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------------------
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* Functions and their uses
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.. function:: quick_select.search(array, n)
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- **array** : an unsorted array
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- **n** : nth number to be searched in the given `array`
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- **Return Value** : returns the nth element
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.. function:: quick_select.time_complexities()
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- **Return Value** : returns time complexities
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.. function:: quick_select.get_code()
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- **Return Value** : returns the code for the ``quick_select.search()`` function

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