pip-tools has more functionality than this, but compile alone is quite useful. Start with a loose list of dependencies in requirements.in: typer rich The requirements.in file can have things like >= and such if you have some restrictions on your dependencies. Now install pip-tools: pip install pip-tools Then, in create a requirements.txt file with compile: pip-compile requirements.in or: python -m piptools compile requirements.in The output will be shown on stdout, but also in requirements.txt: ...

Michael Kennedy from Talk Python to Me and I have launched a new podcast, called Python Bytes, “Python headlines delivered directly to your earbuds”. It’s a weekly short format podcast. Please check it out. The first few weeks of a podcast can really make a difference if we can get a bunch of listeners to try it right away. Please consider leaving a review on iTunes. Even if you don’t use iTunes to listen, early reviews can really help with visibility. ...

This is the transcript for Test and Code Podcast episode 2 Hello everyone. My name is Brian Okken. Welcome to the Python Test Podcast (Now called “Test & Code”). Today I want to talk about choosing a test framework. When I went to look at the different frameworks, I noticed that unittest and doctest are part of the standard library, but nose and pytest were used quite a bit also, so I figured those four were good things to look into. Really what I was looking for was not a unittest framework, but a functional test framework. They are really the same thing. I didn’t know if it was complete list so I put a post up on my website with a poll asking other people if they were interested in those, and if there is anything else. And predominantly those four came back as things that people wanted to hear about. ...

PragPub April 2016 featuring Python (and me) PragPub is the digital magazine put out by Pragmatic Bookshelf, Michael Swaine, and Nancy Groth. I’m especially excited about it because I have two articles featured. I mostly know Michael from the many years of reading Dr Dobb’s. And I respect Pragmatic Bookshelf for their work in technical publishing. So I was thrilled to be asked to contribute. ...

Designing your test methods using a simple structure such as given-when-then will help you: Communicate the purpose of your test more clearly Focus your thinking while writing the test Make test writing faster Make it easier to re-use parts of your test Highlight the assumptions you are making about the test preconditions Highlight what outcomes you are expecting and testing against. In this post I’ll be talking about designing your test cases/test methods using given-when-then. It doesn’t matter if you are using pytest, unittest, nose, or something completely different, this post will help you write better tests. Note: This was originally a writeup done after the Python Test Podcast episode 10. However, I think it stands pretty good on it’s own as a post. ...

I’ve made a few changes to the pytest-expect fixture plugin. I’ve put the plugin code on github, https://github.com/okken/pytest-expect. It is re-arranged to be a plugin installable with pip. Although I don’t have it in pypi yet. I’ve modified the code to use pytest 2.7.0 @pytest.mark.hookwrapper. I incorporated Bruno’s feedback from the last post to allow both assert failures and expect failures to be reported in the same test. There’s a tests directory to test the plugin. There’s still lots to do. But this is a decent start. ...

This is the first iteration that implements ‘expect’ as a fixture. This is really the third attempt at an ‘expect()’ implementation that allows multiple failures per test. First attempt was a general solution that works with any test framework, but with a slightly clunky API. The main problem with it was that it required the test to call a final ‘assert_expectations()’ from the test code. If you forgot to call that function, the failures weren’t reported. Second attempt was a pytest plugin implementation that eliminated the need for the ‘assert_expectations()’ call in the test because it was called automatically. I wasn’t thrilled with this solution. But it works. In the solution I’m presenting in this post, I’m moving all of the code into one file and implementing ‘expect’ as a pytest fixture. ...

Occasionally referred to as Test First Development, Test First Programming is a beautiful concept that radically changed the way I approach software development. The ideas of Test First Programming and Test Driven Development are often muddled together. However, Test First is powerful enough to stand on it’s own. I think it’s important to present the concepts separately. TDD and many other agile practices build on Test First. This isn’t just about remembering the past. The lessons learned from Test First are still very important. ...

In Delayed assert / multiple failures per test, I presented a first attempt at writing an ‘expect()’ function that will allow a test function to collect multiple failures and not stop execution until the end of the test. There’s one big thing about that method that I don’t like. I don’t like having to call ‘assert_expectations()’ within the test. It would be cool to push that part into a plugin. So, even though this isn’t the prettiest code, here’s a first attempt at making this a plugin. Test code that uses expect() Local conftest.py plugin for delayed assert Changes to delayed_assert.py Seeing it in action Possible issues and things I don’t like Alternative solutions Next Steps ...

A test stops execution once it hits a failing assert statement. That’s kinda the point of an assert statement, though, so that’s not surprising. However, sometimes it’s useful to continue with the test even with a failing assert. I’m going to present one method for getting around this restriction, to test multiple things, allow multiple failures per test, and continue execution after a failure. I’m not really going to describe the code in detail, but I will give the full source so that you can take it and run with it. Reasons for multiple assert statements and not stop execution Using a failure list to keep track of failures within a test Example test code that uses the delayedAssert module And an example for unittest The output for unittest The output for pytest The output for nose The delayedAssert.py module Feedback welcome ...