pytest is awesome by itself. pytest + plugins is even better.

Some of the plugins discussed (we also mention a few plugins related to some on this list):

Honorable mention:

Special Guest: Anthony Sottile.

Sponsored By:

• Oxylabs: Visit oxylabs.io/testandcode to find out more about their services and to apply for a free trial of their Next-Generation Residential Proxies.
• Springboard: Check out Springboards machine learning engineering career track. Promo Code: AISPRINGBOARD

Links:

• PyPI Download Stats
• Top PyPI Packages: A monthly dump of the 4,000 most-downloaded packages from PyPI
• Test & Code 25: Selenium, pytest, Mozilla – Dave Hunt
• pre-commit

Django is without a doubt one of the most used web frameworks for Python. Lacey Williams Henschel is a Django consultant and has joined me to talk about Django, the Django community, and so much more.

Topics:

Special Guest: Lacey Williams Henschel.

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:

• Django
• Django Girls
• Django Girls Tutorial
• DjangoCon US 2020
• Django: Under the Hood
• PyData
• PyCascades
• Django REST framework
• pytest-django
• Wagtail CMS - Django Content Management System

Harry Percival has completed his second book, "Architecture Patterns with Python".
 So of course we talk about the book, also known as "Cosmic Python".
 We also discuss lots of testing topics, especially related to larger systems and systems involving third party interfaces and APIs.

Topics 

• Harry's new book, "Architecture Patterns with Python". a.k.a. Cosmic Python 
• TDD : Test Driven Development
• Test Pyramid
• Tradeoffs of different architectural choices
• Mocks and their pitfalls
• Avoiding mocks
• Separating conceptual business logic
• Dependency injection
• Dependency inversion
• Identifying external dependencies
• Interface adapters to mimize the exposed surface area of external dependencies
• London School vs Classic/Detroit School of TDD
• Testing strategies for testing external REST APIs

Links:

• Cosmic Python - Simple Patterns for Building Complex Applications
• Architecture Patterns with Python - on Amazon
• Harry Percival (@hjwp) / Twitter
• Bob Gregory (@bob_the_mighty) / Twitter
• vcrpy · PyPI
• Writing tests for external API calls
• Stop Using Mocks (for a while) - Harry's PyCon talk

Application security is best designed into a system from the start.

On today's Test & Code, Anthony and I discuss his security plugin, but also application security in general, as well as other security components you need to consider.

Security is something every team needs to think about, whether you are a single person team, a small startup, or a large corporation.

Anthony and I also discuss where to start if it's just a few of you, or even just one of you.

Topics include:

Special Guest: Anthony Shaw.

Sponsored By:

• Oxylabs: Visit oxylabs.io/testandcode to find out more about their services and to apply for a free trial of their Next-Generation Residential Proxies.

Links:

• Python Security - plugin for PyCharm
• Bandit
• Hack The Box

Let's say you have a web application and you want to make some changes to improve it.

But really what is A/B testing?

That's what we'll find out on this episode with Leemay Nassery.

Special Guest: Leemay Nassery.

Sponsored By:

• Oxylabs: Visit oxylabs.io/testandcode to find out more about their services and to apply for a free trial of their Next-Generation Residential Proxies.

I play a form of group chess that has some interesting analogies to software development and maintenance of existing systems. This episode explains group chess and explores a few of those analogies.

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.

pytest-testmon is a pytest plugin which selects and executes only tests you need to run. It does this by collecting dependencies between tests and all executed code (internally using Coverage.py) and comparing the dependencies against changes. testmon updates its database on each test execution, so it works independently of version control.

In this episode, I talk with testmon creator Tibor Arpas about testmon, about it's use and how it works.

Special Guest: Tibor Arpas.

Sponsored By:

• PyCharm Professional: Try PyCharm Pro with a 4 month free trial. Promo Code: TESTANDCODE22

Links:

• testmon.org
• Determining affected tests
• Tibor's post on using pytest in PyCharm
• runtime-info plugin for PyCharm

This episode is not just a look back on 2019, and a look forward to 2020.

top 10 episodes of 2019

Looking back on the last decade

Looking forward to 2020 and beyond

A closing quote

That's why I promote and teach automated testing.

I hope you had an amazing decade.

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:

• Thanks, 201X! — Mahmoud Hashemi's blog

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: TESTANDCODE22

Links:

• click repo
• Azure Pipelines Action · Actions · GitHub Marketplace

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