Python Test

Practical automated testing for software engineers using Python. Mostly. But also so much more.

https://podcast.pythontest.com

Eine durchschnittliche Folge dieses Podcasts dauert 32m. Bisher sind 221 Folge(n) erschienen. Dieser Podcast erscheint alle 9 Tage.

Gesamtlänge aller Episoden: 4 days 23 hours 47 minutes

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episode 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.

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 February 9, 2022  10m
 
 

episode 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 Mei

This episode discusses the factors...


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 January 31, 2022  9m
 
 

episode 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.

Full Transcript


Links:

  • Simon Willison's Twitter Thread
  • The Testing Trophy and Testing Classifications — Kent C Dodds
  • Write tests. Not too many. Mostly integration...


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 January 28, 2022  21m
 
 

episode 176: SaaS Side Projects


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...


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 January 18, 2022  26m
 
 

episode 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.

Full Transcript


Links:

  • Test Automation - Who Should be Involved? | Thoughtworks


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 January 12, 2022  13m
 
 

episode 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...


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 December 22, 2021  39m
 
 

episode 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...


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 December 17, 2021  23m
 
 

episode 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...


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 November 30, 2021  6m
 
 

episode 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. 

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Special Guest: Paul Ganssle...


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 November 22, 2021  38m
 
 

episode 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 course
  • testing pipeline stages
  • counterfactual testing
  • performance testing

All with pytest. So cool.

Full Transcript

Special Guest: Prayson Daniel...


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 November 18, 2021  45m