Test & Code is a podcast about software testing and development, hosted by Brian Okken. It focuses primarily on Python testing practices, tools, and techniques for writing reliable code. Episodes feature discussions with developers and testers about real-world engineering workflows. The show is aimed at programmers who want to improve how they test and maintain their software.
Episodes
238: So Long, and Thanks for All the Fish
A farewell to a fun 10 years.Also, I should have tested it better. :)In the audio I got the numbers wrong. Doh!This is episode 238, not 237. Oh well.I'll still be around, of course, at:pythontest.com - where I write about developing software with testspythonbytes.fm - Python news and headlines, delivered directly to your earbudsThanks for all the fun over the last 10 years.I wish you the
237: FastAPI Cloud - Sebastián Ramírez
In this episode, Brian interviews Sebastián Ramírez, creator of FastAPI, about its rapid rise in developer popularity and the launch of FastAPI Cloud. Sebastian explains how FastAPI Cloud addresses deployment challenges small teams face. He shares his transition from open-source to startup founder, focusing on simplifying deployment against the complexity of tools like Kubernetes.Links:Fa
236: Git Tips for Testing - Adam Johnson
In this episode, host Brian Okken and guest Adam Johnson explore essential Git features, highlighted by Adam's updated book, "Boost Your Git DX." Key topics include "cherry picking" for selective commits"git stash" for managing in-progress work"git diff", and specifically its `--name-only` flag, which provides a streamlined method for developers to identify which files have changed, which
235: pytest-django - Adam Johnson
In this episode, special guest Adam Johnson joins the show and examines pytest-django, a popular plugin among Django developers. He highlights its advantages over the built-in unittest framework, including improved test management and debugging. Adam addresses transition challenges, evolving fixture practices, and offers tips for optimizing test performance. This episode is a concise guid
234: pytest-metadata - provides access to test session metadata
pytest-metadata is described as a plugin for pytest that provides access to test session metadata. That is such a humble description for such a massively useful plugin. If you're already using pytest-html, you have pytest-metadata already installed, as pytest-metadata is one of the dependencies for pytest-html.However, pytest-metadata is very useful even on its own.Links:pytest-metadata -
233: pytest-check - allow multiple failures per test
pytest-check is a pytest plugin that allows multiple failures per test.Normally, a test function will fail and stop running with the first failed assert. That's totally fine for tons of kinds of software tests. However, there are times where you'd like to check more than one thing, and you'd really like to know the results of each check, even if one of them fails.pytest-check allows multi
232: The role of AI in software testing - Anthony Shaw
AI is helping people write code. Tests are one of those things that some people don't like to write. Can AI play a role in creating automated software tests? Well, yes. But it's a nuanced yes. Anthony Shaw comes on the show to discuss the topic and try to get AI to write some test for my very own cards project.We discuss:The promise of AI writing your tests for youDownsides to not wr
231: pytest-repeat - works fine on Python 3.14
pytest-repeat is a pytest plugin that makes it easy to repeat a single test, or multiple tests, a specific number of times. works fine on Python 3.14is tested on Python 3.9-3.14probably works fine still on 3.7 & 3.8This episode also discusses the attempted April Fools episode.Links:pytest-repeatThe April Fools episode: Python 3.14 won't repeat with pytest-repeat
230: Python 3.14 won't repeat with pytest-repeat
pytest-repeat is a pytest plugin that makes it easy to repeat a single test, or multiple tests, a specific number of times. Note: This was an April Fools attempt, so the statement ..."Unfortunately, it doesn't seem to work with Python 3.14, even though there is no rational reason why it shouldn't work." ... is NOT true.Listen to the NEXT episode to get an explanationLinks:pytest-repeatNe
229: pytest-html - a plugin that generates HTML reports for test results
pytest-html has got to be one of my all time favorite plugins. pytest-html is a plugin for pytest that generates a HTML report for test results. This episode digs into some of the super coolness of pytest-html.pytest-htmlrepo readme with screenshotenhancing reportspytest-metadata
228: pytest-md and pytest-md-report: Markdown reports for pytest
Markdown reports as either text or markdown tables.Two fun plugins discussed.Links:pytest-md-reportpytest-mdTop pytest Plugins
227: Mocking in Python with unittest.mock - Michael Foord
This episode is a replay of a 2021 interview I did with Michael Foord.We lost Michael in January, and I'd like to revisit this interview as a tribute. Michael Foord was a pivotal figure in the Python community and the creator of the mock library that's now unittest.mock. But he did so much more as well. His contributions continue to resonate within the developer community. This interview
226: pytest-mock : Mocking in pytest
pytest-mock is currently the #3 pytest plugin. pytest-mock is a wrapper around unittest.mock.In this episode:Why the pytest-mock plugin is awesomeWhat is mocking, patching, and monkey patchingWhat, if any, is the difference between mock, fake, spy, stub. Why we might need these in testingSome history of mock in Python and how mock became unittest.mockFrom unittest.mockpatch.objectpatch.ob
225: pytest-cov : The pytest plugin for measuring coverage
pytest-cov is a pytest plugin that helps produce coverage reports using Coverage.py.In this episode, we'll discuss:what Coverage.py iswhy you should measure code coverage on both your source and test codewhat pytest-cov isextra features pytest-cov gives you over and above coverage.pyand generally why using both is awesomeLinks:coverage.pypytest-covhow to set up context reportsTop pytest P
224: pytest plugins - a full series
This episode kicks off a series on pytest plugins.In this episode:Introduction to pytest pluginsThe pytest.org pytest plugin listFinding pytest related packages on PyPIThe Top pytest plugins list on pythontest.comExploring popular pluginsLearning from plugin examplesLinks:Top pytest plugins listpytest.org plugin listTop PyPI PackagesAnd links to plugins mentioned in the show can be found
223: Writing Stuff Down is a Super Power
Taking notes well can help to listen better, remember things, show respect, be more accountable, free up mind space to solve problems.This episode discussesthe benefits of writing things downpreparing for a meetingtaking notes in meetingsreviewing notes for action items, todo items, things to follow up on, etc.taking notes to allow for better focuswriting well structured emailswriting blo
222: Import within a Python package
In this episode we're talking about importing part of a package into another part of the same package.We'll look at: `from . import module` and `from .module import something`and also: `import package` to access the external API from with the package.Why would we use `import package` if `from . import api` would work fine?
221: How to get pytest to import your code under test
We've got some code we want to test, and some tests.The tests need to be able to import the code under test, or at least the API to it, in order to run tests against it.How do we do that? How do we set things up so that our tests can import our code?In this episode, we discuss two options:Installing the code under test as a pip installable package with `pip install -e /path/to/local/packa
220: Getting the most out of PyCon, including juggling - Rob Ludwick
PyCon US is just around the corner. I've asked Rob Ludwick to come on the show to discuss how to get the most out of your PyCon experience. There's a lot to do. A lot of activities to juggle, including actual juggling, which is where we start the conversation.Even if you never get a chance to go to PyCon, I hope this interview helps you get a feel for the welcoming aspect of the Python c
219: Building Django Apps & SaaS Pegasus - Cory Zue
I'm starting a SaaS project using Django, and there are tons of decisions right out of the gate. To help me navigate these decisions, I've brought on Cory Zue. Cory is the creator of SaaS Pegasus, and has tons of experience with Django.Some of the topics discussed:Building Django applicationsSaaS Pegasusplacecard.meWhat boilerplate projects areDjango cookiecutterCookiecutterWhich databa
218: Balancing test coverage with test costs - Nicole Tietz-Sokolskaya
Nicole is a software engineer and writer, and recently wrote about the trade-offs we make when deciding which tests to write and how much testing is enough.We talk about:Balancing schedule vs testingHow much testing is the right about of testingShould code coverage be measured and trackedGood refactoring can reduce code coverageIs it worth testing error conditions?Are rare error codes ok
217: Podcasting / SaaS / Work Life Balance - Justin Jackson
If you've ever thought about starting a podcast or a SaaS project, you'll want to listen to this episode. Justin is one of the people who motivated me to get started podcasting. He's also running a successful SaaS company, transistor.fm, which hosts this podcast.Topics:PodcastingBuilding new SaaS (software as a service) productsBalancing work, side hustle, and familyGreat places to snowbo
216: ruff, uv, and Astral: Python tooling, much faster, with Rust
Charlie Marsh and team are using Rust to make Python tooling faster.Ruff can take the place of Flake8, isort, and Black, and so much more.uv can take the place of pip, pip-tools, and virtualenvAstral is Charlie's venture backed company, and what they have with `ruff` and `uv` is just the start.Since uv is the newest tool, there's quite a bit of the discussion diving into uv.Links:ruffAstr
215: Staying Technical as a Manager
Software engineers that move into leadership roles have a struggle between learning leadership skills, maintaining technical skills, and learning new leadership and technical skills. Matt Makai went from individual contributor to developer relations to leadership in devrel. We discuss how to stay technical, as well as dive into some results of his studies in how companies use developer re
214: Python Testing in VS Code
If you haven't tried running automated tests, especially with pytest, in VS Code recently, you should take another look.The Python for VS Code interface for testing, especially for pytest, has changed recently. On this episode we discuss the change with the software engineer working on the pytest changes, Eleanor Boyd, and the product manager, Courtney Webster. Links from the episode:Blo
213: Repeating Tests
If a test fails in a test suite, I'm going to want to re-run the test. I may even want to re-run a test, or a subset of the suite, a bunch of times. There are a few pytest plugins that help with this:pytest-repeatpytest-rerunfailurespytest-flakefinderpytest-instafailWe talk about each of these in this episode.
212: Canon TDD - by Kent Beck
In 2002, Kent Beck released a book called "Test Driven Development by Example".In December of 2023, Kent wrote an article called "Canon TDD".With Kent's permission, this episode contains the full content of the article.Brian's commentary is saved for a followup episode.Links:Canon TDDTest Driven Development by Example
211: Stamp out test dependencies with pytest plugins
We want to be able to run tests in a suite, and debug them in isolation, and have the behavior be the same. If the behavior is different in isolation vs in a suite, it's a nightmare to debug. In this episode, we'll talk about:Causes of dependenceTesting for dependencies using pluginsDebugging test dependenciesPlugins discussed:pytest-randomlypytest-reversepytest-random-order
210: TDD - Refactor while green
Test Driven Development. Red, Green, Refactor. Do we have to do the refactor part? Does the refactor at the end include tests? Or can I refactor the tests at any time?Why is refactor at the end? This episode is to talk about this with a an example.
209: Testing argparse Applications
How do you test the argument parsing bit of an application that uses argparse?This episode covers:Design for Test: Structuring your app or script so it's easier to test.pytest & capsys for testing stdoutAdding debug and preview flags for debugging and testingAnd reverting to subprocess.run if you can't modify the code under testAlso, there's a full writeup and code samples available:B
208: Tests with no assert statements
Why on earth would you want to write a test with no assert statements?After all, aren't assert statements how you decide wether a test passes or fails?In this episode, we walk through a handful of useful examples of test code without asserts.We also talk about how these types of tests are a great way to dip your toe into testing.
207: pytest course, pytest-repeat and pytest-flakefinder
New course: "The Complete pytest Course"pytest-repeat, which I'm starting to contribute toGive `--repeat-scope` a try. You can use it to change from repeating every test to repeating the session, module, or class.pytest-flakefinder, which is an alternative to pytest-repeatpytest-check is completely unrelated, but mentioned in the show
206: TDD in Context
TDD (Test Driven Development) started from Test First Programming, and has been around at least since the 90's. However, software tools and available CI systems have changed quite a bit since then. Maybe it's time to re-examine the assumptions, practices, processes, and principles of TDD. At least in the context of my software engineering career, modifications to TDD, at least the versio
205: pytest autouse fixtures
On a recent episode of PythonBytes, I suggested it's hard to come up with good examples for pytest autouse fixtures, as there aren't very many good reasons to use them. James Falcon was kind enough to reach out and correct me. In this episode, we describe:what fixtures arewhat autouse fixtures aregreat reasons to use them
204: Free Your Inner Nonfiction Writer - Johanna Rothman
Learn how to write nonfiction fast and well.Johanna Rothman joins the show to discuss writing nonfiction.Johanna's book: Free Your Inner Nonfiction Writer
203: Open Source at Intel
Open Source is important to Intel and has been for a very long time.Joe Curley, vice president and general manager of software products and ecosystem, and Arun Gupta, vice president and general manager for open ecosystems, join the show to discuss open source, OneAPI, and open ecosystems at Intel.
202: Using Towncrier to Keep a Changelog - Hynek Schlawack
Hynek joins the show to discuss towncrier. At the top of the towncrier documentation, it says "towncrier is a utility to produce useful, summarized news files (also known as changelogs) for your project."Towncrier is used by "Twisted, pytest, pip, BuildBot, and attrs, among others."This is the last of 3 episodes focused on keeping a CHANGELOG. Episode 200 kicked off the series with keepac
201: Avoid merge conflicts on your CHANGELOG with scriv - Ned Batchelder
Last week we talked about the importance of keeping a changelog. This week we talk with Ned Batchelder about scriv, a tool to help maintain that changelog.Scriv "is a command-line tool for helping developers maintain useful changelogs. It manages a directory of changelog fragments. It aggregates them into entries in a CHANGELOG file."Links:nedbat/scriv: Changelog management tool
200: Keep a CHANGELOG
A changelog is a file which contains a curated, chronologically ordered list of notable changes for each version of a project. This episode is about what a changelog is, with an interview with Olivier Lacan, creator of keepachangelog.com. The next two episodes talk about some tools to help software project teams keep changelogs while avoiding merge conflicts. Special Guest: Olivier Lacan.
199: Is Azure Right for a Side Project? - Pamela Fox
For a web side project to go from "working on desktop" to "live in the cloud", one decision that needs to be made is where to host everything. One option is Microsoft Azure. Lots of corporate sites use it. Is it right for side projects? Pamela Fox, a Cloud Advocate for Python at Microsoft, joins the show to help us with that question.Links:Python Bytes Episode #323pamelafox gitHub project
198: Testing Django Web Applications - Carlton Gibson, Will Vincent
Django has some built in ways to test your application. There's also pytest-django and other plugins that help with testing. Carlton Gibson and Will Vincent from the Django Chat Podcast join the show to discuss how to get started testing your Django application.
197: Python project trove classifiers - Do you need this bit of pyproject.toml metadata? - Brett Cannon
Classifiers are one bit of Python project metadata that predates PyPI. Classifiers are weird. They were around in setuptools days, and are still here with pyproject.toml. What are they? Why do we need them? Do we need them?Which classifiers should I include?Why are they called "trove classifiers" in the Python docsBrett Cannon joins the show to discuss these wacky bits of metadata.Here's
196: I am not a supplier - Thomas Depierre
Should we think of open source components the same way we think of physical parts for manufactured goods? There are problems with supply chain analogy when applied to software. Thomas Depierre discusses some of those issues in this episode. Links:I am not a supplier - article
195: What would you change about pytest? - Anthony Sottile
Anthony Sottile and Brian discuss changes that would be cool for pytest, even unrealistic changes. These are changes we'd make to pytest if we didn't ahve to care about backwards compatibilty.Anthony's list:The import systemMulti-process support out of the boxAsync supportChanges to the fixture systemExtend the assert rewriting to make it modularAdd matchers to assert mechanismBan test cl
193: The Good Research Code Handbook - Patrick Mineault
I don't think it's too much of a stretch to say that software is part of most scientific research now. From astronomy, to neuroscience, to chemistry, to climate models. If you work in research that hasn't been affected by software yet, just wait.But how good is that software? How much of common best practices in software development are making it to those writing software in the sciences
192: Learn to code through game development with PursuedPyBear - Piper Thunstrom
The first game I remember coding, or at least copying from a magazine, was in Basic. It was Lunar Lander. Learning to code a game is a way that a lot of people get started and excited about programming. Of course, I don't recommend Basic. Now we've got Python. And one of the game engines available for Python is PursuedPyBear, a project started by Piper Thunstrom. Piper joins us this episo
191: Running your own site for fun and absolutely no profit whatsoever - Brian Wisti
Having a personal site is a great playground for learning tons of skills. Brian Wisti discusses the benefits of running a his own blog over the years.Links:Random GeekeryJamstackEleventyNetlifyPlausible AnalyticspytestBeautiful Souppyinvoke - Invoke!rsyncInternet Archive : archive.orgRichStatamicjamstack.orgA static site generator should be your next language learning project
190: Testing PyPy - Carl Friedrich Bolz-Tereick
PyPy is a fast, compliant alternative implementation of Python. cPython is implemented in C. PyPy is implemented in Python. What does that mean? And how do you test something as huge as an alternative implementation of Python?Special Guest: Carl Friedrich Bolz-Tereick.Links:PyPyHow is PyPy Tested? PyPy SpeedPython Speed Center
189: attrs and dataclasses - Hynek Schlawack
In Python, before dataclasses, we had attrs. Before attrs, it wasn't pretty.The story of attrs and dataclasses is actually intertwined. They've built on each other. And in the middle of it all, Hynek.Hynek joins the show today to discuss some history of attrs and dataclasses, and some differences.If you ever need to create a custom class in Python, you should listen to this episode.Links
188: Python's Rich, Textual, and Textualize - Innovating the CLI
Will McGugan has brought a lot of color to CLIs within Python due to Rich. Then Textual started rethinking full command line applications, including layout with CSS. And now Textualize, a new startup, is bringing CLI apps to the web.Links:richrich-clitextualTextualize.ioRich GalleryTextualize GalleryPython Bytes Podcast
187: Teaching Web Development, including Front End Testing
When you are teaching someone web development skills, when is the right time to start teaching code quality and testing practices?Karl Stolley believes it's never too early. Let's hear how he incorporates code quality in his courses.Our discussion includes:starting people off with good dev practices and toolslintinghtml and css validationvisual regression testingusing local dev servers, i
186: Developer and Team Productivity
Being productive is obviously a good thing. Can we measure it? Should we measure it? There's been failed attempts, like lines of code, etc. in the past. Currently, there are new tools to measure productivity, like using git metrics.Nick Hodges joins the show to discuss the good and the bad of developer and team productivity, including how we can improve productivity.
185: Python + Django + Rich + Testing == Awesome
Django has a handful of console commands to help manage and develop sites. django-rich adds color and nice formatting. Super cool. In a recent release, django-rich also adds nice colorized tracebacks to the Django test runner. Links:django-rich · PyPIepisode 181: Boost Your Django DX - Adam Johnsondjango-crispy-formsPython Developers Survey 2020 Results
184: Twisted and Testing Event Driven / Asynchronous Applications - Glyph
Twisted has been supporting asynchronous / event driven applications way before asyncio. Twisted, and Glyph, have also been encouraging automated tests for a very long time.Twisted uses a technique that should be usable by other applications, even those using asyncio or other event driven architectures.Links:Community Service Award Recipient Glyph Lefkowitz — The PSF article I was referri
183: Managing Software Teams - Ryan Cheley
Ryan Cheley joins me today to talk about some challenges of managing software teams, and how to handle them. We end up talking about a lot of skills that are excellent for software engineers as well as managers.Some topics discussed:handling code reviewsasking good questionsbeing honest about what you can't do with current resources and datadiscussing tradeoffs and offering solutions that
182: An Unorthodox Technical Interview and Hiring Process - Nathan Aschbacher
Don't you just love technical interviews, with someone who just saw your resume or CV 5 minutes ago asking you to write some code on a whiteboard. Probably code that has nothing to do with anything you've done before or anything you will do at the company.No? Neither does Nathan Aschbacher. So when he started building the team at his company, he decided to do things differently.Hiring is
181: Boost Your Django DX - Adam Johnson
We talk with Adam Johnson about his new book, "Boost Your Django DX". Developer experience includes tools and practices to make developers more effective and efficient, and just plain make software development more fun and satisfying. One of the things I love about this book is that it's not just for Django devs. I'd guess that about half the book is about topics that all Python develop
180: Lean TDD
Lean TDD is an attempt to reconcile some conflicting aspects of Test Driven Development and Lean Software Development.I've mentioned Lean TDD on the podcast a few times and even tried to do a quick outline at the end of episode 162.This episode is a more complete outline, or at least a first draft.If you feel you've got a good understanding of TDD, and it's working awesome for you, that's
179: Exploratory Testing
Exploratory testing is absolutely an essential part of a testing strategy. This episode discusses what exploratory testing is, its benefits, and how it fits within a framework of relying on automated tests for most of our testing.
178: The Five Factors of Automated Software Testing
"There are five practical reasons that we write tests. Whether we realize it or not, our personal testing philosophy is based on how we judge the relative importance of these reasons." - Sarah MeiThis episode discusses the factors.Sarah's order:Verify the code is working correctlyPrevent future regressionsDocument the code’s behaviorProvide design guidanceSupport refactoringBrian's order:
177: Unit Test vs Integration Test and The Testing Trophy
A recent Twitter thread by Simon Willison reminded me that I've been meaning to do an episode on the testing trophy. This discussion is about the distinction between unit and integration tests, what those terms mean, and where we should spend our testing time.Links:Simon Willison's Twitter ThreadThe Testing Trophy and Testing Classifications — Kent C DoddsWrite tests. Not too many. Mostly
176: SaaS Side Projects - Brandon Braner
The idea of having a software as a service product sound great, doesn't it? Solve a problem with software. Have a nice looking landing page and website. Get paying customers. Eventually have it make enough revenue so you can turn it into your primary source of income. There's a lot of software talent out there. We could solve lots of problems. But going from idea to product to first cust
175: Who Should Do QA?
Who should do QA?How does that change with different projects and teams?What does "doing QA" mean, anyway?Answering these questions are the goals of this episode.Links:Test Automation - Who Should be Involved? | Thoughtworks
174: pseudo-TDD - Paul Ganssle
In this episode, I talk with Paul Ganssle about a fun workflow that he calls pseudo-TDD. Pseudo-TDD is a way to keep your commit history clean and your tests passing with each commit. This workflow includes using pytest xfail and some semi-advanced version control features.Some strict forms of TDD include something like this:write a failing test that demonstrates a lacking feature or defe
173: Why NOT unittest?
In the preface of "Python Testing with pytest" I list some reasons to use pytest, under a section called "why pytest?". Someone asked me recently, a different but related question "why NOT unittest?".unittest is an xUnit style framework. For me, xUnit style frameworks are fatally flawed for software testing.That's what this episode is about, my opinion of "Why NOT unittest?", or more broa
172: Designing Better Software with a Prototype Mindset
A prototype is a a preliminary model of something, from which other forms are developed or copied. In software, we think of prototypes as early things, or a proof of concept. We don't often think of prototyping during daily software development or maintenance. I think we should. This episode is about growing better designed software with the help of a prototype mindset.Links:Selecting a p
171: How and why I use pytest's xfail - Paul Ganssle
Paul Ganssle, is a software developer at Google, core Python dev, and open source maintainer for many projects, has some thoughts about pytest's xfail. He was an early skeptic of using xfail, and is now an proponent of the feature. In this episode, we talk about some open source workflows that are possible because of xfail. Special Guest: Paul Ganssle.Links:How and why I use pytest's xfai
170: pytest for Data Science and Machine Learning - Prayson Daniel
Prayson Daniel, a principle data scientist, discusses testing machine learning pipelines with pytest.Prayson is using pytest for some pretty cool stuff, including:unit tests, of coursetesting pipeline stagescounterfactual testingperformance testingAll with pytest. So cool.Special Guest: Prayson Daniel.Links:Python Bytes 250, with Prayson Daniel — Listen to this for more of an introduction
169: Service and Microservice Performance Monitoring - Omri Sass
Performance monitoring and error detection is just as important with services and microservices as with any system, but with added complexity. Omri Sass joins the show to explain telemetry and monitoring of services and of systems with services. Special Guest: Omri Sass.
168: Understanding Complex Code by Refactoring into Larger Functions
To understand complex code, it can be helpful to remove abstractions, even if it results in larger functions. This episode walks through a process I use to refactor code that I need to debug and fix, but don't completely understand.
167: React, TypeScript, and the Joy of Testing - Paul Everitt
Paul has a tutorial on testing and TDD with React and TypeScript. We discuss workflow and the differences, similarities between testing with React/TypeScript and Python. We also discuss what lessons that we can bring from front end testing to Python testing.Special Guest: Paul Everitt.Links:React, TypeScript, and TDD — Paul Everitt's tutorialReact Testing Library
166: unittest expectedFailure and xfail
xfail isn't just for pytest tests. Python's unittest has @unittest.expectedFailure.In this episode, we cover:using @unittest.expectedFailurethe results of passing and failing tests with expectedFailureusing pytest as a test runner for unittestusing pytest markers on unittest testsDocs for expectedFailure: https://docs.python.org/3/library/unittest.html#skipping-tests-and-expected-failure
165: pytest xfail policy and workflow
A discussion of how to use the xfail feature of pytest to help with communication on software projects.The episode covers:What is xfailWhy I use itUsing reason effectively by including issue tracking numbersUsing xfail_strictAdding --runxfail when transitioning from development to feature freezeWhat to do about test failuresHow all of this might help with team communication
164: Debugging Python Test Failures with pytest
An overview of the pytest flags that help with debugging. From Chapter 13, Debugging Test Failures, of Python Testing with pytest, 2nd edition.pytest includes quite a few command-line flags that are useful for debugging. We talk about thes flags in this episode.Flags for selecting which tests to run, in which order, and when to stop:-lf / --last-failed: Runs just the tests that failed las
163: pip install ./local_directory - Stéphane Bidoul
pip : "pip installs packages" or maybe "Package Installer for Python" pip is an invaluable tool when developing with Python. A lot of people know pip as a way to install third party packages from pypi.org You can also use pip to install from other indexes (or is it indices?)You can also use pip to install a package in a local directory. That's the part I want to jump in and explore with S
162: Flavors of TDD
What flavor of TDD do you practice? In this episode we talk about:Classical vs Mockist TDDDetroit vs London (I actually refer to it in the episode as Chicago instead of Detroit. Oh well.)Static vs BehaviorInside Out vs Outside InDouble Loop TDDBDDFDDTracer BulletsRules of TDDTeam StructureLean TDD This is definitely an episode I'd like feedback on. Reach out to me for further questions or
161: Waste in Software Development
Software development processes create value, and have waste, in the Lean sense of the word waste. Lean manufacturing and lean software development changed the way we look at value and waste. This episode looks at lean definitions of waste, so we can see it clearly when we encounter it.I'm going to use the term waste and value in future episodes. I'm using waste in a Lean sense, so we can
160: DRY, WET, DAMP, AHA, and removing duplication from production code and test code
Should your code be DRY or DAMP or something completely different? How about your test code? Do different rules apply? Wait, what do all of these acronyms mean?We'll get to all of these definitions, and then talk about how it applies to both production code and test code in this episode. Links:The Pragmatic Programmer, 20th Anniversary EditionDon't repeat yourself - Wikipediaa-ha - Take O
159: Python, pandas, and Twitter Analytics - Matt Harrison
When learning data science and machine learning techniques, you need to work on a data set. Matt Harrison had a great idea: Why not use your own Twitter analytics data? So, he did that with his own data, and shares what he learned in this episode, including some of his secrets to gaining followers.In this episode we talk about:Looking at your own Twitter analytics data.Using Python, panda
158: TDD in Swift - Gio Lodi
Iterative processes that include writing test code and production code together, such as TDD, help make coding fun. All of us that care about developing quality code with the help of testing can learn from each other, regardless of programming language.Today we step outside our normal Python comfort zone and talk with Gio about TDD in Swift.Gio Lodi, author of TDD in Swift, joins the show
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