It is impossible nowadays to not hear about microservices. It’s so “buzzy” word that everyone is talking, writing and thinking about it – either developers and managers. In this blogpost I’d like to focus on some useful cases concerning Python & Microservices altogether.
In this article I'd like to show you how to test your API with Spock Framework. Spock is a testing framework for Java and Groovy applications. It extends JUnit runner and let us write shorter and more readable code. Spock supports unit testing, BDD and Mocking. It is also great for Data Driven Testing.
We all in principle try to perfect our app. Choosing best architecture and frameworks, meticulously planning classes and utilizing design patterns to make best of our work. But with nearly every line written, functionalities become replicated once more.
There are many ways to write code in order to achieve same results. This article will show you how different approaches affect the code execution in the scope of time duration. This should give you a hint on what choices should be made but mostly to encourage you to always consider time execution as a substantial matter.
Maintaining large-scale CSS codebase is a demanding task. In the era of complex component systems and unspecified requirements, this gets even harder – what solves many possible problems, is well-organized, clearly defined architecture.
I would like to share with you some useful ways of working with Jenkins, as well as methods of coping with various issues that I (and probably a lot of you) faced during my career in QA scope. It is also worth to mention some reliable plugins. I’ve found them helpful and time-saving, so it pays to get them together in this short blogpost.
While reading top-shelf Python books, you probably might have bumped into the sentence "be pythonic". But what exactly does it mean and how to use it in real life examples? This article presents some practical cases where pythonic approach should be used and shows you some code snippets, where this approach was implemented.
Machine learning is widely and successfully used nowadays. We think that computers know, but actually, they do not know - they compute. All they do is just operating on numbers. We teach them how to know by telling them what to compute.