Clean architectures in Python: a step-by-step example

One year ago I was introduced by my friend Roberto Ciatti to the concept of Clean Architecture, as it is called by Robert Martin. The well-known Uncle Bob talks a lot about this concept at conferences and wrote some very interesting posts about it. What he calls "Clean Architecture" is a way of structuring a software system, a set of consideration (more than strict rules) about the different layers and the role of the actors in it.

As he clearly states in a post aptly titled The Clean Architecture, the idea behind this design is not new, being built on a set of concepts that have been pushed by many software engineers over the last 3 decades. One of the first implementations may be found in the Boundary-Control-Entity model proposed by Ivar Jacobson in his masterpiece "Object-Oriented Software Engineering: A Use Case Driven Approach" published in 1992, but Martin lists ... more

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

OOP concepts in Python 2.x - Part 3


Welcome to the third installment of this little series of posts about Python 2.x OOP implementation. The first and second issues introduced the most important concepts at the basis of Python as an object-oriented language.

This post will continue the discussion about metaclasses, introducing Abstract Base Classes, and give some insights on callable objects.

This post refers to the internals of Python 2.x - please note that Python 3.x changes (improves!) some of the features shown here. You can find the updated version here.

The Inspection Club

As you know, Python leverages polymorphism at its maximum by dealing only with generic references to objects. This makes OOP not an addition to the language but part of its structure from the ground up. Moreover, Python pushes the ... more

OOP concepts in Python 2.x - Part 2


This post continues the analysis of the Python OOP implementation started with this post, which I recommend reading before taking on this new one.

This second post discusses the following OOP features in Python:

  • Polymorphism
  • Classes and instances (again)
  • Metaclasses
  • Object creation

This post refers to the internals of Python 2.x - please note that Python 3.x changes (improves!) some of the features shown here. You can find the updated version here.

Good Morning, Polymorphism

The term polymorphism, in the OOP lingo, refers to the ability of an object to adapt the code to the type of the data it is processing.

Polymorphism has two major applications in an OOP language. The first is that an object may provide different implementations of one of its methods depending on the type of ... more

OOP concepts in Python 2.x - Part 1


Object-oriented programming (OOP) has been the leading programming paradigm for several decades now, starting from the initial attempts back in the 60s to some of the most important languages used nowadays. Being a set of programming concepts and design methodologies, OOP can never be said to be "correctly" or "fully" implemented by a language: indeed there are as many implementations as languages.

So one of the most interesting aspects of OOP languages is to understand how they implement those concepts. In this post I am going to try and start analyzing the OOP implementation of the Python language. Due to the richness of the topic, however, I consider this attempt just like a set of thoughts for Python beginners trying to find their way into this beautiful (and sometimes peculiar) language.

This first post covers the following topics:

  • Objects and types
  • Classes and instances
  • Object members: methods and attributes
  • Delegation: ... more