Python Mocks: a gentle introduction - Part 2

In the first post I introduced you to Python mocks, objects that can imitate other objects and work as placeholders, replacing external systems during unit testing. I described the basic behaviour of mock objects, the return_value and side_effect attributes, and the assert_called_with() method.

In this post I will briefly review the remaining assert_* methods and some interesting attributes that allow to check the calls received by the mock object. Then I will introduce and exemplify patching, which is a very important topic in testing.

Other assertions and attributes

The official documentation of the mock library lists many other assertion, namely assert_called_once_with(), assert_any_call(), assert_has_calls(), assert_not_called(). If you ... more

Punch - Update your version while having a drink

So you completed your wonderful new project, all your test are successful (you test code, don't you?) and you just want to ship the new version and call it a day. Well, you just have to go and change the version number in your install script and save. Oh, right, you also have to open a feature branch, so that you may record the version update in your Git history. Well, easily done. Damn! You forgot to change the version number in the file...

Managing the version number of a project is not easy. Not only you need to think about the versioning scheme and what part of the version to increase (see this post for some tips on this matter), but you also need to remember in which files you put the actual version number, and, depending on your workflow, to correctly manage the version control system commits.

Punch is a small tool that aims to simplify the latter parts, that is ... more

Abstract Base Classes in Python

With the introduction of Abstract Base Classes, Python once again shows its nature of a very innovative and flexible language. It is interesting to see how such a remarkable feature has been introduced into the language by a pure Python module. This demonstrates that Python is built in a way that is very open to changes, thanks to its foundations in pure polymorphism based on delegation.

Many Python programmers overlooked Abstract Base Classes and the classes in the collections module, which are one of the simplest and useful applications of the concept. Sure enough, this is not a feature that you will use every day or that will change the way you are programming in Python. But neither is it something you shall discard before understanding what it brings into the language, and what sort of problems it can solve for you.

Level 1


Python is a dynamically-typed object-oriented language strongly based on delegation, so its approach to problems is intrinsically ... more

Python Mocks: a gentle introduction - Part 1

As already stressed in the two introductory posts on TDD (you can find them here) testing requires to write some code that uses the functions and objects you are going to develop. This means that you need to isolate a given (external) function that is part of your public API and demonstrate that it works with standard inputs and in edge cases.

For example, if you are going to develop an object that stores percentages (such as for example poll results), you should test the following conditions: the class can store a standard percentage such as 42%, the class shall give an error if you try to store a negative percentage, the class shall give an error if you store a percentage greater than 100%.

Tests shall be idempotent and isolated. Idempotent in mathematics and computer science identifies a process that can be run multiple times without changing the status of the system. Isolated means that a test shall not change its behaviour depending on ... more

Clojure sequential data types for Python programmers

I have been working with Python for more than fifteen years and I developed very big systems with this language, learning to know and love both its power and its weaknesses, admiring its gorgeous object-oriented system and exploring some of its darkest corners.

Despite being so committed to this language (both for personal choices and for business reasons) I never stopped learning new languages, trying to get a clear picture of new (or old) paradigms, to explore new solutions to old problems and in general to get my mind open.

Unfortunately introducing a new language in your business is always very risky, expensive and many times not a decision of yours only. You are writing software that other may have to maintain, so either you evangelize your team and persuade other to join you or you will be forced to stay with the languages shared by them. This is not bad in itself, but sometimes it is a big obstacle for the adoption of a new language.

One of the languages I fell in love (but ... more

A simple example of Python OOP development (with TDD) - Part 2

In the first part of this small series I introduced you to TDD with Python by means of the powerful py.test package. We developed together a simple library which provides a Binary class that is a bit more useful than the default binary representation that Python provides with the bin() builtin function.

In this part I'll go on with the development of the library, discussing the implementation of a binary number with a fixed size, which is a very interesting and useful matter, being the foundation of the computer we are working with. Fixed-size binaries may also represent negative numbers with the two's complement technique, and this will be an important point to test.

You may happen to dislike some decisions about the interface or the behaviour of the resulting class. Since this post is just a way to show you a concrete TDD session you are totally free to change the tests and to come up with a ... more

Using gitflow with GitHub: a simple procedure

Date Tags Git

Git is a very powerful version control system and much of its power comes from its very simple basic structures. Git is mostly a manager of blob trees and even the most complex operations are basically tree operations.

The power of Git brings also a great flexibility, which means that Git doesn't dictate a specific workflow, leaving the programmer or the team to come up with a reasonable procedure.


Two Git workflows are very widespread, for different reasons. The first is the GitHub model and the second is the gitflow one.

The GitHub model is widely used, because nowadays GitHub is the most used code management and collaboration website for open source projects. GitHub makes use of a workflow based on Pull Requests, and you can find some useful resources about it in the relative section at the end of the post.

Gitflow was proposed by Vincent Driessen in 2010 and quickly become one of the most used workflows, due to the fact that it covers most of the common ... more

A simple example of Python OOP development (with TDD) - Part 1

If you are eager to learn some Python and do not know how to start, this post may give you some hints. I will develop a very simple Python package from scratch, exemplifying some Object-oriented Programming (OOP) techniques and concepts, and using a Test-Driven Development (TDD) approach.

The package will provide some classes to deal with binary numbers (see the Rationale section), but remember that it is just a toy project. Nothing in this package has been designed with performance in mind: it wants to be as clear as possible.


Binary numbers are rather easy to understand, even if becoming familiar with them requires some time. I expect you to have knowledge of the binary numeral system. If you need to review them just take a look at the Wikipedia entry or one of the countless resources on Internet.

The package we are going to write will provide a class that represents binary numbers (Binary) and ... more

Python decorators: metaprogramming with style

This post is the result of a lot of personal research on Python decorators, meta- and functional programming. I want however to thank Bruce Eckel and the people behind the open source book "Python 3 Patterns, Recipes and Idioms" for a lot of precious information on the subject. See the Resources section at the end of the post to check their work.

Is Python functional?

Well, no. Python is a strong object-oriented programming language and is not really going to mix OOP and functional like, for example, Scala (which is a very good language, by the way).

However, Python provides some features taken from functional programming. Generators and iterators are one of them, and Python is not the only non pure functional programming language to have them in their toolbox.

Perhaps the most distinguishing feature of functional ... more