Systems | Development | Analytics | API | Testing

When you use loops in Python, there are a lot of times when you don’t just want the item from a list, you also want to know where that item is in the list. For example, going through a list of names and needing to show their position, like “1. Alice”, “2. Bob”, and so on, or you could be building a menu where each option needs a number next to it. In these situations, Python’s enumerate() function is very helpful.

Do you ever feel like you need a superpower to get the information you need? Especially when you’re really into Python? APIs are pretty much that superpower! APIs (Application Programming Interfaces) let your code "talk" to other systems and get exactly what you need. They can help you come up with a new app, find the next big market trend, or even automate your morning weather report. This guide?

To be honest, most Python developers are not using list comprehensions. Even I, who is writing this blog, never used list comprehensions before. But when I saw some examples, I felt I had to try and use them in my Python code. The reason for this change of mind is that there are a few advantages we get if we implement list comprehensions. Let’s see what these are in this blog today.

Doing things manually on GitLab is okay, but it can get repetitive and time-consuming. That’s where the GitLab Python API comes to the rescue! With it, you can automate tasks like creating projects, branches, or merge requests using just a few lines of Python code. It’s incredibly handy for DevOps, scripting, or personal projects! In this blog, we’ll dive into setting up and using the GitLab Python API step by step.

By optimizing Python code, you improve performance, reduce resource consumption, and enhance scalability. While Python is known for its simplicity and readability, these characteristics can sometimes come at the cost of efficiency. In this article, we'll explore four ways to optimize your Python project and improve performance. First, we'll look at how best to use data structures.

APIs (Application Programming Interfaces) are like bridges that let different software systems talk to each other. Among the many types of APIs, REST APIs are the most popular because they follow a simple and well-defined architecture. In this blog, we’ll explore what REST APIs are, how they work in Python, and how you can build and test them easily.

When you’re building something in Python—whether it’s a personal project, an API, or a startup idea—one thing is certain: bugs happen. And while debugging can be fun (sometimes), wouldn’t it be better to catch issues before they cause problems? That’s where testing comes in. In today’s blog, we’ll explore how to test and run your Python applications using Pytest, one of the most popular and beginner-friendly testing tools out there.

When it comes to testing in Python, two popular frameworks often come into play: unittest vs pytest. Choosing the right one can make a big difference in how you write, run, and maintain your tests. In this blog, we’ll explore what sets these two apart and help you understand which one might be better suited for your project. We’ll look at the features and differences between unittest and pytest, so you can make an informed decision.

When you write code, how do you know it actually works? You could run the program and click around manually—but that quickly becomes tedious, unreliable, and error-prone, especially as your codebase grows. That’s where unit testing comes in. Unit testing lets you verify that individual pieces of your code—like functions or methods—behave exactly the way you expect.

JSON Web Tokens (JWTs) secure communication between parties over the internet by authenticating users and transmitting information securely, without requiring a centralized storage system. In this article, we'll explain what JWTs are and give a high-level overview of how they work. We'll also implement a JWT-based authentication system by creating a to-do list API using Flask.