I am a software engineer with a strong focus on Cloud Computing and CI/CD, but also with experience in both mobile and web development. Designing and building efficient, resilient, and cost-effective software solutions excites me.
To learn advanced Computer Science techniques for building software which is equally a joy to create and use, I will be joining the University of California, Davis, as a graduate student in Fall 2021.
In my spare time, you’ll find me reading about anything that stimulates my brain, be it coding practices, human psychology, or the latest Murakami novel. I also enjoy mentoring new developers and blogging about topics that they will find helpful as they step into their tech careers.
I am interested in internship opportunities for Summer 2022. Please feel free to contact me at firstname.lastname@example.org.
Download my resumé.
One of the easiest ways to extract a subset of elements from an iterable in Python is by applying the concept of slicing. In this post, let’s understand how we can slice through any iterable, i.e, strings, lists or tuples in order to carve out a subset!
In this post, let’s understand how we can automate the process of extracting data from an HTML document with the help of Python’s Beautiful Soup library.
Let’s understand what is web scraping and when can we use it to parse, search and reformat large amount of data into relevant information.
One of the simplest ways of making Python code more readable is by replacing positional arguments in function calls with named or keyword arguments. Let’s explore how we can do that in this post!
Python comes with a lot of built-in data types like lists, sets, tuples, and dictionaries and because of its simplicity, Python makes it very easy to work with these data types. In this post, I will discuss how to nest these data types to create sophisticated types for managing data.