Test & Code

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 best.

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:FastAPI CloudFastAPISQLModelTyperOpenAPIPydanticSequoia Open Source Fellowship

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 can be used to determine which tests need to be run"git bisect" for efficiently pinpointing bugs. This conversation offers valuable strategies for developers at any skill level to enhance their Git proficiency and optimize their coding workflows.Links:Boost Your Git DX - Adam's book

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 guide for developers looking to enhance their testing strategies with pytest-django.Links:pytest-django - a plugin for pytest that provides a set of useful tools for testing Django applications and projects.

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 - The plugin we're talking about in this episodepytest-base-url - Adds the base URL to the metadata.pytest-html - Displays the metadata at the start of each report. See S2:E6: pytest-html - a plugin that generates HTML reports for test resultspytest-reporter-html1 - Presents metadata as part of the report.pytest-selenium - Adds the driver, capabilities, and remote server to the metadata.If you've got other plugins that work well with pytest-metadata, please let me know.

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 multiple failed "checks" per test function, so you can see the whole picture of what's going wrong.Links:pytest-checkTop pytest plugins

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 writing tests yourselfBad ways to generate testsGood ways to ask AI for help in writing testsTricks to get better results while using copilot and other AI toolsLinks:The cards projectA video version of this discussion: Should AI write tests?

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

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-repeatNext episode: pytest-repeat - works fine on Python 3.14

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

Markdown reports as either text or markdown tables.Two fun plugins discussed.Links:pytest-md-reportpytest-mdTop pytest Plugins

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 is just a small peek at his influence. In this episodeIntroduction to Michael FoordThe Mock Library OriginsMocking and Testing PhilosophyCareer Path and ConsultingUnderstanding MockingThe Power of PatchTesting Strategies and DesignMocking External DependenciesTeaching Testing and Mockingpython.org has put up an "In memoriam" page for Michael Foord, and many people have shared stories and memories.Links:In memoriam: Michael Foord 1974-202530 best practices for software development and testing

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.object with autospecusing these as context managerspytest-mock:The mocker fixture Cleanup in teardownUsing mocker.patch, mocker.spy, and mocker.stubWhy it's awesome and why you might want to use it over straight unittest.mockLinks:top pytest plugins listpytest-mock documentationunittest.mockPodcast episode discussing unittest.mock with Michael Foordmonkeypatch

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 PluginsErrata:I mentioned that Coverage has the ability to show context (which line is covered by which test) for the past year or so.However, that feature was released in Oct 2018. coverage 5.0 alpha That's over 6 years. Oops. Sorry Ned.

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 at pythontest.com/top-pytest-plugins

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 blog posts and books

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?

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/package`.Using the pythonpath pytest setting.

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 community.I recorded this interview as an episode for one of my other podcasts, Python People. But I think it's got some great pre-conference advice, so I'm sharing it here on Python Test as well.We talk about: - Juggling at PyCon- How to get the most out of PyCon - Watching talks - Hallway track - Open spaces - Lightening talks - Expo hall / vendor space - Poster sessions - Job fair - A welcoming community - Tutorials - Sprints - But mostly about the people of Python and PyCon."Python enables smart people to work faster" - Rob Ludwick

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 database to use, probably PostgreSQLAuthentication choises, probably AllauthDocker, Docker for development, Docker for deploymentDeployment targets / hosting services. Render, Heroku, Fly.io, for PaaS options.Front end frameworks. Bootstrap, Tailwind, DaisyUI, TailwindUIHTMX vs React vs straight Django templatesRocketsFont Awesomeand of course, SaaS Pegasus

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 to just monitor?API drift and autospecMitigating riskDeciding what to test and what not to testFocus testing on key money-making features If there's a bug in this part of the code, how much business impact is there?Performance testing needs to approximately match real world workloadsCost of a service breaking vs the cost of creating, maintaining, and running testsKeeping test suites quick to minimize getting distractedLinks:Too much of a good thing: the trade-off we make with tests Load testing is hard, and the tools are... not great. But why?Yet Another Rust Resource (YARR!)Goodhart's law - "When a measure becomes a target, it ceases to be a good measure"

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 snowboard in British ColumbiaBTW. Links from the show:Transistor.fm - excellent podcast hosting, Justin is a co-founderHow to start a podcast in 2024Podcasts from JustinBuild your SaaS - currentBuild & Launch - an older one, but greatMegaMaker - from 2021 / 2022

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:ruffAstraluv

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 relationship channels.

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:Blog post announcing the rewrite Code repo for questions, comments, issues etc

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.

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

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

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.

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:Blog post: Testing argparse Applications Code Repo

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.

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

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 version of TDD as it's frequently taught, have been necessary. This is the start of a series focused on examining TDD and related lightweight practices and processes.Links from the show:From XPTest FirstUnit TestsAcceptance TestsTest-Driven Development (wikipedia)

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

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

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.

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 keepachangelog.com and Olivier Lacan In 201 we had Ned Batchelder discussing scriv.Special Guest: Hynek Schlawack.Links:Towncrier docsHow to Keep a Changelog in Markdown - Towncrier docsKeep a Changelogstructlog/CHANGELOG.md — Example of manually edited changelog.hatch-fancy-pypi-readmeMyST Markdown hatchling

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

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.Links:Shields.ioKeep a Changelog"The Changelog" Podcast interview with Olivier LacanAn Open Source Rage Diamond

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 projectsDeploy a Python (Django or Flask) web app to AzureHosting Python Web Apps on Azure: A Price-OffDeploying a containerized FastAPI app to Azure Container AppsGetting started with hosting Python apps on AzurePricing Calculator for AzureApp Service Pricing pamelafox/flask-db-quiz-exampleTutorial: Deploy a Python Django or Flask web app with PostgreSQLPamela Fox on Mastodon

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.

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 an example, from pytest-crayons:[project] ... classifiers = [ "License :: OSI Approved :: MIT License", "Framework :: Pytest" ] Links:Classifiers · PyPIPEP 621 – Storing project metadata in pyproject.toml | peps.python.orgPackaging Python Projects — Python Packaging User Guide — Configuring metadataPEP 639 – Improving License Clarity with Better Package Metadata | peps.python.orgSPDX

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

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 class inheritanceBrian's list: Extend assert rewriting for custom rewriting, like checkpytester matchers available for all testsThrow out nose and unittest compatibility pluginsThrow out setup_module, teardown_module and other xunit style functionsRemove a bunch of the hook functionsDocumentation improvement of remaining hook functions which include examples of how to use itStart running tests before collection is doneSplit collection and running into two processesHave the fixtures be able to know the result of the test during teardownLinks:anthonywritescode - YouTubeanthonywritescode - Twitchpytest-asyncio · PyPIasync test patterns for pytestfuture-fstrings · PyPIre-assert · PyPInumpy.testingSourcegraph

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?Patrick Mineault has written "The Good Research Code Handbook". It's a website. It's concise. And it will put you on the right path to writing better software. Even if you don't write science based software, and even if you already have a CS degree, there's some good information worth reading.Special Guest: Patrick Mineault.Links:The Good Research Code Handbookgame-wrath-jam: A game jam game, theme: WrathRobotron 2084 - Arcade - YouTubeThe Book of Why: The New Science of Cause and Effect

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 episode and we talk about PursuedPyBear, learning to code, and learning CS concepts with game development. PursuedPyBear, ppb, is a game framework great for learning with, with goals of being fun, education friendly, an example of idiomatic Python, hardware library agnostic, and built on event driven and object oriented concepts.Special Guest: Piper Thunstrom.Links:PursuedPyBear | Unbearably Fun Game DevelopmentPiper's BlogMaking Games With PPB - PyTexasShooter Game by Piper Thunstromshootergame on GitHubBriefcase— BeeWaregame-blink: A tiny emergent behavior toy.Combat (Atari 2600) — The tank game I didn't remember the name of.Lunar Lander

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

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

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:attrs documentationHistory of attrs and introduction to attrs namespacecattrs: Complex custom class converters for attrs. — python-attrsPEP 557 – Data ClassesPEP 681 – Data Class Transforms

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