We write tests to make sure that our code is correct, but how do you make sure the tests are correct? This week Ned Batchelder explains how coverage.py fills that need, how he became the maintainer, and how it works under the hood.
The venerable ‘if’ statement is a cornerstone of program flow and busines logic, but sometimes it can grow unwieldy and lead to unmaintainable software. One alternative that can result in cleaner and easier to understand code is a state machine. This week Glyph explains how Automat was created and how it has been used to upgrade portions of the Twisted project.
We all know that testing is an important part of software and systems development. The problem is that as our systems and applications grow, the amount of testing necessary increases at an exponential rate. Cris Medina joins us this week to talk about some of the problems and approaches associated with testing these complex systems and some of the ways that Python can help.
As Python developers we are fond of the dynamic nature of the language. Sometimes, though, it can get a bit too dynamic and that’s where having some type information would come in handy. Mypy is a project that aims to add that missing level of detail to function and variable definitions so that you don’t have to go hunting 5 levels deep in the stack to understand what shape that data structure is supposed to be. This week we spoke with David Fisher and Greg Price about their work on Mypy and its use within Dropbox and the broader community. They explained how it got started, how it works under the covers, and why you should consider adding it to your projects.
When you have good tools it makes the work you do even more enjoyable. Russel Keith-Magee has been building up a set of tools that are aiming to let you write graphical interfaces in Python and run them across all of your target platforms. Most recently he has been working on a capstone project called Toga that targets the Android and iOS platforms with the same set of code. In this episode we explored his journey through programming and how he has built and designed the Beeware suite. Give it a listen and then try out some or all of his excellent projects!
Making sure that your code is secure is a difficult task. In this episode we spoke to Eric Brown, Travis McPeak, and Tim Kelsey about their work on the Bandit library, which is a static analysis engine to help you find potential vulnerabilities before your application reaches production. We discussed how it works, how to make it fit your use case, and why it was created. Give the show a listen and then go start scanning your projects!
As technology professionals, we need to make sure that the software we write is reliably bug free and the best way to do that is with a continuous integration and continuous deployment pipeline. This week we spoke with Pierre Tardy about Buildbot, which is a Python framework for building and maintaining CI/CD workflows to keep our software projects on track.
Writing tests is important for the stability of our projects and our confidence when making changes. One issue that we must all contend with when crafting these tests is whether or not we are properly exercising all of the edge cases. Property based testing is a method that attempts to find all of those edge cases by generating randomized inputs to your functions until a failing combination is found. This approach has been popularized by libraries such as Quickcheck in Haskell, but now Python has an offering in this space in the form of Hypothesis. This week, the creator and maintainer of Hypothesis, David MacIver, joins us to tell us about his work on it and how it works to improve our confidence in the stability of our code.
We got the opportunity to speak with Al Sweigart about his work on books like ‘Automate The Boring Stuff With Python’ and ‘Invent With Python’. We discussed how Python can be useful to people who don’t work as software engineers, why coding literacy is important for the general populace and how that will affect the ways in which we interact with software.
In this episode we talked to Holger Krekel about the py.test library. We discussed the various styles of testing that it supports, the plugin system and how it compares to the unittest library. We also reviewed some of the challenges around packaging and releasing Python software and our thoughts on some ways that they can be improved.