Non maskable interrupt

Python 3 has been in existence for 7 years now, yet some still prefer to use Python 2 instead of the newer version. This is a problem especially for neophytes that are approaching Python for the first time. I realized this at my previous workplace with colleagues in the exact same situation. Not only were they unaware of the differences between the two versions, they were not even aware of the version that they had installed. Inevitably, different colleagues had installed different versions of the interpreter. That was a recipe for disaster if they would’ve then tried to blindly share the scripts between them. This wasn’t quite their fault, on the contrary. A greater effort for documenting and raising awareness is needed to dispel that veil of FUD (fear, uncertainty and doubt) that sometimes affects our choices. This post is thus thought for them, or for those who already use Python 2 but aren’t sure about moving to the next version, maybe because they tried version 3 only at the b

More often than not, the software we write directly interacts with what we would label as “dirty” services. In layman’s terms: services that are crucial to our application, but whose interactions have intended but undesired side-effects—that is, undesired in the context of an autonomous test run. For example: perhaps we’re writing a social app and want to test out our new ‘Post to Facebook feature’, but don’t want to actually post to Facebook every time we run our test suite. The Python unittest library includes a subpackage named unittest.mock —or if you declare it as a dependency, simply mock —which provides extremely powerful and useful means by which to mock and stub out these undesired side-effects. Note: mock is newly included in the standard library as of Python 3.3; prior distributions will have to use the Mock library downloadable via PyPI . Fear System Calls To give you another example, and one that we’ll run with for the rest of the article, consider system

If you like whales, or are simply interested in quick and painless continuous delivery of your software to production, then I invite you to read this introductory Docker Tutorial. Everything seems to indicate that software containers are the future of IT, so let’s go for a quick dip with the container whales Moby Dock and Molly . Docker, represented by a logo with a friendly looking whale, is an open source project that facilitates deployment of applications inside of software containers. Its basic functionality is enabled by resource isolation features of the Linux kernel, but it provides a user-friendly API on top of it. The first version was released in 2013, and it has since become extremely popular and is being widely used by many big players such as eBay, Spotify, Baidu, and more . In the last funding round, Docker has landed a huge $95 million . Transporting Goods Analogy The philosophy behind Docker could be illustrated with a following simple analogy. In the internat