PODCAST

Test & Code

Brian Okken

The Python Test Podcast hosted by Brian Okken

technology how to

All Episodes

9:00

The Five Factors of Automated Software Testing

Test & Code ·

2022/01/31

"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:Verify the code is working correctlyPrevent future regressionsSupport refactoringProvide design

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21:40

Unit Test vs Integration Test and The Testing Trophy

Test & Code ·

2022/01/28

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.Full TranscriptLinks:Simon Willison's Twitter ThreadThe Testing Trophy and Testing Classifications — Kent C DoddsWrite tests. Not too many. Mostly integration. — Kent C DoddsOn the Diverse And Fantastical Shapes of Testing — Martin

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26:09

SaaS Side Projects

Test & Code ·

2022/01/18

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 customer is non-trivial. Especially as a side hustle. This episode discusses some of the hurdles from idea

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13:07

Who Should Do QA?

Test & Code ·

2022/01/12

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.Full TranscriptLinks:Test Automation - Who Should be Involved? | Thoughtworks

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39:25

pseudo-TDD - Paul Ganssle

Test & Code ·

2021/12/22

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 defectwrite the source code to get the test to passrefactor if necessaryrepeatIn reality, at least for me,

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23:31

Why NOT unittest?

Test & Code ·

2021/12/17

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 broadly, "What are the fatal flaws of xUnit?"Full TranscriptLinks:Python Testing with pytest, Second

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6:54

Designing Better Software with a Prototype Mindset

Test & Code ·

2021/11/30

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.Full TranscriptLinks:Selecting a programming language can be a form of premature optimization — Brett Cannon's blog post

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38:27

How and why I use pytest's xfail - Paul Ganssle

Test & Code ·

2021/11/22

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. Full TranscriptSpecial Guest: Paul Ganssle.Links:How and why I use pytest's xfail — Paul's blog post mentioned in the episodeCraft Minimal Bug Reports — Matthew

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45:13

pytest for Data Science and Machine Learning -...

Test & Code ·

2021/11/18

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.Full TranscriptSpecial Guest: Prayson Daniel.Links:Python Bytes 250, with Prayson Daniel — Listen to this for more of an introduction to Prayson

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30:15

Service and Microservice Performance Monitoring -...

Test & Code ·

2021/11/11

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. Full TranscriptSpecial Guest: Omri Sass.

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11:20

Understanding Complex Code by Refactoring into Larger...

Test & Code ·

2021/11/02

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.Full Transcript

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36:53

React, TypeScript, and the Joy of Testing - Paul Everitt

Test & Code ·

2021/10/22

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.Full TranscriptSpecial Guest: Paul Everitt.Links:React, TypeScript, and TDD — Paul Everitt's tutorialReact Testing Library

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6:24

unittest expectedFailure and xfail

Test & Code ·

2021/10/14

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-failuresSome sample code. unittest only:import unittest class ExpectedFailureTestCase(unittest.TestCase):

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9:45

pytest xfail policy and workflow

Test & Code ·

2021/10/07

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 communicationFull Transcript

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13:18

Debugging Python Test Failures with pytest

Test & Code ·

2021/09/14

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 last.-ff / --failed-failed: Runs all the tests, starting with the last failed.-x / --exitfirst: Stops the

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29:40

pip install ./local_directory - Stéphane Bidoul

Test & Code ·

2021/08/20

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 Stéphane Bidoul. The way pip installs from a local directory is about to change, and the story is

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22:45

162: Flavors of TDD

Test & Code ·

2021/08/03

What flavor of TDD do you practice? In this episode we talk about: Classical vs Mockist TDD Detroit vs London (I actually refer to it in the episode as Chicago instead of Detroit. Oh well.) Static vs Behavior Inside Out vs Outside In Double Loop TDD BDD FDD Tracer Bullets Rules of TDD Team Structure Lean TDD This is definitely an episode I'd like feedback on. Reach out to me @brianokken or via the contact form for further questions or if I missed some crucial variant of TDD that you

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18:50

161: Waste in Software Development

Test & Code ·

2021/07/20

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 look at software processes critically, see the value chain, and try to reduce waste. Lean

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14:41

160: DRY, WET, DAMP, AHA, and removing duplication...

Test & Code ·

2021/07/08

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. Full TranscriptSponsored By:Datadog: Modern end-to-end monitoring & security. See inside any stack, any app, at any scale, anywhere. Get started with a free trial at testandcode.com/datadog and

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47:52

159: Python, pandas, and Twitter Analytics - Matt...

Test & Code ·

2021/07/02

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, pandas, Jupyter for data cleaning and exploratory analysis Data visualization Machine learning,

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