Test & Code in Python Brian Okken

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.
Sponsored By:
PyCharm Professional: Try PyCharm Pro for 4 months and learn how PyCharm will save you time. Promo Code: TESTANDCODE22Support Test & Code in Python
Links:
How and why I use pytest's xfail — Paul's blog post mentioned in the episodeCraft Minimal Bug Reports — Matthew Rocklin's articleepisode 111: Subtests in Python with unittest and pytest - Paul Ganssleepisode 165: pytest xfail policy and workflowepisode 166: unittest expectedFailure and xfail

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.
Special Guest: Prayson Daniel.
Sponsored By:
PyCharm Professional: Try PyCharm Pro for 4 months and learn how PyCharm will save you time. Promo Code: TESTANDCODE22Support Test & Code in Python
Links:
Python Bytes 250, with Prayson Daniel — Listen to this for more of an introduction to Prayson

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.
Sponsored By:
PyCharm Professional: Try PyCharm Pro for 4 months and learn how PyCharm will save you time. Promo Code: TESTANDCODE22Support Test & Code in Python

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.
Sponsored By:
PyCharm Professional: Try PyCharm Pro for 4 months and learn how PyCharm will save you time. Promo Code: TESTANDCODE22Support Test & Code in Python

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.
Sponsored By:
Patreon Supporters: Help support the show with as little as $1 per month and be the first to know when new episodes come out.Support Test & Code in Python
Links:
React, TypeScript, and TDD — Paul Everitt's tutorialReact Testing Library

xfail isn't just for pytest tests. Python's unittest has @unittest.expectedFailure.


In this episode, we cover:



using @unittest.expectedFailure
the results of passing and failing tests with expectedFailure
using pytest as a test runner for unittest
using pytest markers on unittest tests


Docs for expectedFailure:
https://docs.python.org/3/library/unittest.html#skipping-tests-and-expected-failures


Some sample code.
unittest only:


import unittest

class ExpectedFailureTestCase(unittest.TestCase):

@unittest.expectedFailure
def test_fail(self):
self.assertEqual(1, 0, "broken")

@unittest.expectedFailure
def test_pass(self):
self.assertEqual(1, 1, "not broken")


unittest with pytest markers:


import unittest
import pytest


class ExpectedFailureTestCase(unittest.TestCase):

@pytest.mark.xfail
def test_fail(self):
self.assertEqual(1, 0, "broken")

@pytest.mark.xfail
def test_pass(self):
self.assertEqual(1, 1, "not broken")
Sponsored By:
Patreon Supporters: Help support the show with as little as $1 per month and be the first to know when new episodes come out.Support Test & Code in Python