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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.

APIs are transforming how manufacturers achieve ESG (Environmental, Social, and Governance) goals by simplifying data collection, real-time monitoring, and reporting. Here's how they help: For example, companies using REST APIs have cut compliance costs by up to $45,719 per implementation and reduced risks by 99%. Whether you're monitoring carbon emissions or ensuring supply chain accountability, APIs make ESG integration seamless and efficient.

While quantum computers promise to solve many problems that cannot be solved (efficiently) on a classical computer, they are a serious threat to security at the same time. We describe why this is the case, how broad this threat is, and how this threat is currently countered. This implies making quantum-safeness an integral aspect of an organization’s IT strategy.

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 exploring common types of software architecture, it’s important to understand the foundational patterns that drive modern application development. Software architecture patterns like MVC, client-server, microservices, and event-driven models help teams build scalable, maintainable, and robust applications. Software architects have built a broad range of options with varying features.

As organizations continue to adopt AI-driven applications, managing usage and costs becomes more critical. Large language models (LLMs), such as those provided by OpenAI, Google, Anthropic, and Mistral, can incur significant expenses when overused. This blog will explore how you can streamline your AI workloads by leveraging Kong’s token rate-limiting and tiered access features.

Jacob Kaplan-Moss, one of the leading developers and co-creators of the Django Python framework, said: In this article, we are going to discuss Unit Testing. Firstly, software testing, in general, is an important part of software engineering that involves evaluating an application to identify issues before it is released to users. This ensures that the application or software meets the specified requirements and performs as expected.

API latency slows down data transfers, disrupts operations, and hurts user experiences. Want faster APIs? Here’s how you can reduce latency right now: These steps work together to cut delays and improve API performance. Whether you're dealing with real-time data streams or heavy traffic, these tips can help ensure smoother, faster data transfers.

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.