Shell sort, also called shellsort, is similar to insertion sort. Insertion sort uses a fixed distance of 1 when comparing items in an unsorted list. Shell sort compares items over a greater distance so that big differences in disorder can be fixed before comparing at smaller distances. The goal is to increase performance by minimizing the number of shifts that would have been performed by using just insertion sort.

Read More**Cocktail sort** is a sorting algorithm, like comb sort, that attempts to improve the performance of bubble sort by eliminating turtles. Turtles are small numbers at the end of the unsorted list that slowly move to the front of the list one position at a time using bubble sort.

**Comb sort** is a sorting algorithm that improves upon bubble sort by comparing and swapping values farther apart to eliminate turtles, which are small values at the end of the unsorted list. By moving these turtles to the front of the list quickly, comb sort reduces the number of swaps that would normally occur in bubble sort. In this tutorial, I will discuss comb sort as compared to bubble sort and write an implementation of comb sort in Python.

Earlier I showed how to do depth-first search in C# and breadth-first search in C#. In this article I want to show depth-first search in Python, using both a recursive and non-recursive solution, because I want to show an example of topological sorting of a directed acyclic graph and the algorithm is based on depth-first search. I am also actively learning Python and it is best that I write Python code daily as much as possible.

Read MoreI built my first decorator in Python to provide caching on Python functions that can support memoization, like the well-known recursive Fibonacci algorithm. Turns out a decorator, called **lru_cache**, already exists in **functools** that does memoization. This article shows how to create a custom Python decorator for caching as well as use the **lru_cache** decorator in **functools** to speed up the recursive Fibonacci algorithm.

This weekend I completed the data structures portion of the **Cracking the Coding Interview Questions** on HackerRank. One of the programming challenges, **validating a binary search tree**, taught me how to verify a binary search tree is valid and I wanted to share my solution using Python.

I have been learning about **Binary Heaps** in my data structures class, and have been coding several examples in both Python and C#. In this article I want to introduce `heapq`

in the Python collections module, which provide min Binary Heap functionality. I also provide an example of how to write a custom min Binary Heap in Python to perform Heapsort!

Implementing a Queue Data Structure in Python and C#. In Python, I will describe how to use `deque`

in the collections module as well as how to develop your own custom Queue using a Link List. In C#, I describe how to implement a Queue using an Array as well as using the `Queue`

and `Queue<T>`

Classes in System.Collections and System.Collections.Generic. I will also discuss abstraction in computer science to help hide the implementation details.

Using memoization in the naieve, recursive algorithm for solving Fibonacci numbers makes a huge performance impact by reducing the number of recursive calls to re-solve Fibonacci numbers already calculated. In this case I will be using a Python dictionary and local functions ( nested functions ) to improve the recursive, naieve algorithm.

Read MoreThis article first shows how to use the `List`

Type in Python as a Stack data structure. It then provides an example of a custom `Stack`

Class built in Python that still leverages the `List`

Type in Python but uses abstraction to hide the underlying storage and its non-Stack methods. The article also shows how to use the `deque`

in Python, `Stack<T>`

in C# from `System.Collections.Generic`

, and how to code the Stack data structure using a link list!

In a recent programming challenge I was asked to code an inorder traversal of a binary search tree to print the values of its keys in the correct order. An order traversal of a binary search tree will print the keys of the node's left sub-tree, followed by the node's key, followed by the keys of the node's right sub-tree. I also show how to create a binary search tree in Python using level order traversal (like breadth-first search) and a list of ordered keys.

Read MoreDay 20 of HackerRank's 30 Days of Code was to write **Bubble sort**. I enjoy coding sorting algorithms (merge sort, insertion sort, selection sort, quicksort), so I was excited for the opportunity to write Bubble sort in Python, which I have done for fun in the past.

The Quickselect Algorithm is a selection algorithm based on the Quicksort sorting algorithm that provides a best case runtime of O(n) when finding the k-th smallest item in an unordered list. Quickselect achieves a better best case runtime compared to Quicksort, because it only has to recursively partition one side of the current partition. Here is an example of the Quickselect Algorithm using Python.

Read MoreToday, in one of my algorithms design and analysis classes I learned about **Quicksort**. Much like Merge Sort, Quicksort is a divide and conquer sorting algorithm that sorts the items in O(nlogn). In this article I will be writing a Quicksort function in Python.

I mentioned learning about generating Fibonacci numbers using Python in my computer science and algorithm courses using recursive functions and Dynamic Programming. I wrote an article about the differences: Fibonacci Numbers - Tale of Two Algorithms using Python. In this article I show a Fibonacci Number Generator using Python generators. I also talk more about Python generators as well as mention the differences between `range`

and `xrange`

in Python 2.7.

Making change is another classic example of **Dynamic Programming** I learned in my algorithms classes. In this example, I use Python to make change for a certain dollar amount given a list of dollars in U.S. currency. The goal is to make change using the least number of bills. Dynamic Programming is a great solution for this, since the problem involves overlapping sub-problems.

Using Dynamic Programming in Python to solve the Knapsack Problem in Clash of Clans. The goal is to find the best troop composition to hide the maximum amount of elixir and dark elixir in my barracks!

Read MoreTaking the example code I wrote with Entity Framework Core and C# and performing the same O/R Mapping and SQL Commands using SQLAlchemy and Python to perform CRUD operation on a SQLite Database.

Read MoreA solution to insertion sort using Python that I wrote with Pythonista on my iPad Pro. I have also included several Doctests to verify it is sorting a list of integers correctly using insertion sort. If you are attending computer science and algorithms courses like myself, I hope you find the code useful!

Read MoreMy computer science assignment was to develop a class in Python that encrypts and decrypts messages using the Caesar Cipher. I chose this solution, because it was the most creative by using **Python string constants**, the **zip** function to create a tuple from 2 iterable lists, **dictionaries** for constant lookup, and **list comprehensions** for doing the actual encryption and decryption.