Pipelines are used a lot in software projects to automated much of the work around build, test, deployment and more. Thomas Eckert talks with me about pipelines, specifically Azure Pipelines. Some of the history, and how we can use pipelines for modern Python projects.Special Guest: Thomas Eckert.Sponsored By:PyCharm Professional: Try PyCharm Pro with a 4 month free trial. Promo Code: TESTANDCODE22Links:click repoAzure Pipelines Action · Actions · GitHub Marketplace ★ Support this podcast on Patreon ★

Data science and machine learning are affecting more of our lives every day. Decisions based on data science and machine learning are heavily dependent on the quality of the data, and the quality of the data pipeline. Some of the software in the pipeline can be tested to some extent with traditional testing tools, like pytest. But what about the data? The data entering the pipeline, and at various stages along the pipeline, should be validated. That's where pipeline tests come in. Pipeline tests are applied to data. Pipeline tests help you guard against upstream data changes and monitor data quality. Abe Gong and Superconductive are building an open source project called Great Expectations. It's a tool to help you build pipeline tests. This is quite an interesting idea, and I hope it gains traction and takes off.Special Guest: Abe Gong.Sponsored By:Raygun: Detect, diagnose, and destroy Python errors that are affecting your customers. With smart Python error monitoring software from Raygun.com, you can be alerted to issues affecting your users the second they happen.Links:Great Expectations ★ Support this podcast on Patreon ★

You've applied for a job, maybe lots of jobs. Depending on the company, you've gotta get through: a resume review a coding challange a phone screen maybe another code example an in person interview If you get the job, and you enjoy the work, awesome, congratulations. If you don't get the job, it'd be really great to know why. Sometimes it isn't because you aren't a skilled engineer. What other reasons are there? Well, that's what we're talking about today. Charity Majors is the cofounder and CTO of Honeycomb.io, and we're going to talk about reasons for not hiring someone. This is a very informative episode both for people who job hunt in the future and for hiring managers and people on the interview team.Special Guest: Charity Majors.Sponsored By:PyCharm Professional: Try PyCharm Pro with a 4 month free trial. Promo Code: TESTANDCODE22Links:The (Real) 11 Reasons I Don’t Hire You — The article ★ Support this podcast on Patreon ★

Andy Knight is the Automation Panda. Andy Knight is passionate about software testing, and shares his passion through public speaking, writing on automationpanda.com, teaching as an adjunct professor, and now also through writing a book and organizing a new regional Python conference. Topics of this episode include: Andy's book on software testing Being an adjunct professor Public speaking and preparing talk proposals including tips from Andy about proposals and preparing for talks PyCarolinas Special Guest: Andy Knight.Sponsored By:Raygun: Detect, diagnose, and destroy Python errors that are affecting your customers. With smart Python error monitoring software from Raygun.com, you can be alerted to issues affecting your users the second they happen.Links:Automation PandaAndy's Speaking eventsPyCarolinas 2020 ★ Support this podcast on Patreon ★

Cristian Medina wrote an article recently called "Test Engineering Anti-Patterns: Destroy Your Customer Satisfaction and Crater Your Quality By Using These 9 Easy Organizational Practices" Of course, it's sarcastic, and aims to highlight many problems with organizational practices that reduce software quality. The article doesn't go out of character, and only promotes the anti-patterns. However, in this interview, we discuss each point, and the corollary of what you really should do. At least, our perspectives. Here's the list of all the points discussed in the article and in this episode: Make the Test teams solely responsible for quality Require all tests to be automated before releasing Require 100% code coverage Isolate the Test organization from Development Measure the success of the process, not the product. Metrics, if rewarded, will always be gamed. Require granular projections from engineers Reward quick patching instead of solving Plan for today instead of tomorrow Special Guest: Cristian Medina.Sponsored By:Azure Pipelines: Automate your builds and deployments with pipelines so you spend less time with the nuts and bolts and more time being creative. Many organizations and open source projects are using Azure Pipelines already. Get started for free at azure.com/pipelinesLinks:Test Engineering Anti-Patterns: Destroy Your Customer Satisfaction and Crater Your Quality By Using These 9 Easy Organizational Practices — The article we discuss in the show.tryexceptpass — Cris's blog ★ Support this podcast on Patreon ★

Python 3.8.0 final is live and ready to download. On todays episode, we're going to run through what's new, picking out the bits that I think are the most interesting and affect the most people, including new language features standard library changes optimizations in 3.8 Not just the big stuff everyone's already talking about. But also some little things that will make programming Python even more fun and easy. I'm excited about Python 3.8. And really, this episode is to my way to try to get you excited about it too.Sponsored By:PyCharm Professional: Try PyCharm Pro with a 4 month free trial. Promo Code: TESTANDCODE22Links:What’s New In Python 3.8 - at docs.python.orgDownload Python 3.8 at Python.org ★ Support this podcast on Patreon ★

pytest 5.2 was just released, and with it, a cool fun feature called dynamic scope fixtures. Anthony Sottile so tilly is one of the pytest core developers, so I thought it be fun to have Anthony describe this new feature for us. We also talk about parametrized testing and really what is fixture scope and then what is dynamic scope.Special Guest: Anthony Sottile.Sponsored By:Raygun: Detect, diagnose, and destroy Python errors that are affecting your customers. With smart Python error monitoring software from Raygun.com, you can be alerted to issues affecting your users the second they happen.Links:pytest changelogpytest fixturesdynamic scope fixturesepisode 82: pytest - favorite features since 3.0 the pytest book — Python Testing with pytest ★ Support this podcast on Patreon ★

Nicholas Tollervey is working toward better ways of teaching programming. His projects include the Mu Editor, PyperCard, and CodeGrades. Many of us talk about problems with software education. Nicholas is doing something about it.Special Guest: Nicholas Tollervey.Sponsored By:Azure Pipelines: Automate your builds and deployments with pipelines so you spend less time with the nuts and bolts and more time being creative. Many organizations and open source projects are using Azure Pipelines already. Get started for free at azure.com/pipelinesLinks:Code With Mu — a simple Python editor for beginner programmersMade With Mu — A blog to celebrate projects that use the Mu Python code editor to create cool stuff.PyperCard — Easy GUIs for AllCodeGrades ★ Support this podcast on Patreon ★

Tools like error monitoring, crash reporting, and performance monitoring are tools to help you create a better user experience and are fast becoming crucial tools for web development and site reliability. But really what are they? And when do you need them? You've built a cool web app or service, and you want to make sure your customers have a great experience. You know I advocate for utilizing automated tests so you find bugs before your customers do. However, fast development lifecycles, and quickly reacting to customer needs is a good thing, and we all know that complete testing is not possible. That's why I firmly believe that site monitoring tools like logging, crash reporting, performance monitoring, etc are awesome for maintaining and improving user experience. John-Daniel Trask, JD, the CEO of Raygun, agreed to come on the show and let me ask all my questions about this whole field.Special Guest: John-Daniel Trask.Sponsored By:Raygun: Detect, diagnose, and destroy Python errors that are affecting your customers. With smart Python error monitoring software from Raygun.com, you can be alerted to issues affecting your users the second they happen. ★ Support this podcast on Patreon ★

There's a cool feature of pytest called parametrization. It's totally one of the superpowers of pytest. It's actually a handful of features, and there are a few ways to approach it. Parametrization is the ability to take one test, and send lots of different input datasets into the code under test, and maybe even have different output checks, all within the same test that you developed in the simple test case. Super powerful, but something since there's a few approaches to it, a tad tricky to get the hang of.Sponsored By:PyCharm Professional: Try PyCharm Pro with a 4 month free trial. Promo Code: TESTANDCODE22Links:git branch — -a : list all branches, -r : just remotespytest changelogpytest deprecations and removalsPython Testing with pytest — Test function parametrization is in chapter 2. Fixture parametrization is in chapter 3.Parametrizing test functions — pytest documentationpytest fixtures — pytest documentation ★ Support this podcast on Patreon ★