When an application runs, it performs a tremendous number of tasks, with many happening behind the scenes. Even a simple to-do application has more than you'd expect. The app will at a bare minimum have tons of tasks like user logins, creating to-dos, updating to-dos, deleting to-dos, and duplicating to-dos. These tasks the application performs can result in success or potentially result in some errors.

Python’s subprocess module stands as one of the most powerful tools in a developer’s toolkit. The module lets you spawn new processes, connect to their input/output/error pipes, and get return codes. Think of the subprocess module as your bridge between Python scripts and system commands, replacing older modules like os.system and os.spawn and providing a better, unified way to handle external processes.

Regular expressions, commonly known as regex, are a tool for text processing and pattern matching. In Python, the re module offers a robust implementation of regex, allowing developers to handle complex text manipulation efficiently. In this article, we'll get to grips with regular expressions and provide practical code examples — from the basic to more advanced — so you can understand how to use regex in Python.

Debugging is a vital part of software development, ensuring that code behaves as intended, identifying errors early, and preventing small fixes from escalating into larger problems. Developers risk releasing unreliable, inefficient, or even unusable code without proper debugging techniques. This tutorial covers the fundamentals of Python’s assert statement, practical ways to use assertions for testing and debugging, and best practices for using assertions effectively while avoiding common pitfalls.

Microservices are now the architecture of choice for many developers when crafting cloud-native applications. A microservices application is a collection of loosely coupled services that communicate with each other, enhancing collaboration, maintainability, scalability, and deployment. There are several options for enabling this communication between microservices. When it comes to Python, gRPC and REST are two extremely popular directions to go.

It would be amazing if everything in the digital world happened instantly. Unfortunately, we don’t live in an ideal world, and most of the time we need to wait for things to happen. From loading a dynamic web page to processing data, even the best implementations can have delays. Some delays happen because of the time it takes to process and transfer data. Other delays are intentional and enable applications to present visuals or data more elegantly.

When writing test automation scripts in Selenium Python, verifying that the actual outcomes match the expected results is crucial. This is where assertions come into play. Assertions help ensure that your application is working as intended by checking specific conditions and halting execution if they fail. In this blog, we’ll break down the concept of assertions in Selenium Python, provide some easy-to-follow code examples, and explain how they can make your test scripts more robust.

Is your program throwing a fit but those error messages are lost somewhere in the avalanche of print statements? Let's fix that! Enter stderr - Python's built-in solution for separating your normal program output from your "everything is on fire" messages. Think of your Python program as having two voices: stdout (its inside voice) and stderr (its "EVERYONE PANIC" voice).

When working with Python, lists are one of the most versatile data structures you’ll come across. It works majorly like Arrays, as seen in other programming languages. The lists allow you to store collections of items, such as integers, strings, or even other lists, and provide numerous ways to access and manipulate the data stored in them.

Many developers focus on developing core application functionalities and pay little or no attention to memory management until they run out of memory, and their apps start crashing, freezing, or experiencing random performance downgrades.