Automated Python Testing

Going into my future projects, especially those for my summer fellowship, I have taken a distinct interest in Python. Throughout this course I have learned a great deal of how to test for object oriented compiler languages, using Java as our learning tool. I have wondered how testing might differ across different languages. And with a large project in Python coming up, I’d like to prioritize doing this the right way. I would like to practice in python testing to prepare. Luckily, recently posted last week, there was an article on the home page of Stickyminds surrounding python testing. The article’s title is Ensuring Reliable Cloud Applications: A Guide to Testing State Machines with Python by Konstantin Sakhchinskiy

Testing state machines in cloud applications involves heavy use of APIs. Python scripting is effective to help to ensure reliability, performance, and resilience. This is one way that an efficient library-heavy scripting language like Python would be useful for cloud applications. It is very effective at being implemented for many applications now utilizing the language itself, if only as an effective testing language. In the case of a cloud app for example, managing external browser profiles for automation and web scraping, users interact via API to execute their needed functions. Python can be used to expedite this process, as a way to manage state machines necessary to operate this cloud app. General approaches to testing on these state machines include separating output generation from state transition logic, focusing on individual states and transitions, testing each possible state transition, exploring boundary conditions, testing resilience to invalid input or disruptions, and checking system interaction within the broader context. The article also mentions some key tactics for mastering state machine testing, including testing for race conditions, assessing external disruptions and network challenges, handling heavy loads, and understanding technical details such as hidden states. Python scripting can automate testing processes. Using asyncio and httpx, scripts can simulate user interactions with the cloud service, testing responsiveness. Tailoring tests to specific needs and monitoring system performance using tools like Grafana and Kibana are essentia, and made more efficient with Python’s wide variety of usable systems. Overall, testing state machines is crucial for ensuring application reliability, and Python scripting offers effective ways to automate and simulate real-world scenarios for comprehensive testing.

My view on testing applications was expanded greatly by this article. The prevalence of automated testing libraries throughout other languages to enforce scripting was a surprise to me. And this article has helped me to understand the real role of specific and intentional testing of software. I was also surprised to find that state machines were very important to understanding how to test and break down code, as this is something I learned a lot about in the fall. I am not working with external applications or languages outside of Python for this project, so I will not utilize these libraries to automate my testing, but going forward this knowledge is imperative.

Source:

https://www.stickyminds.com/article/ensuring-reliable-cloud-applications-guide-testing-state-machines-python