Wow this book is a goldmine for architecture patterns. I love how easy it is to get into a topic and quickly grasp it.
Having said that, from a practical and experience standpoint, using some of these patterns can really spiral out into an increased complexity and performance issues in Python, specially when you use already opinionated frameworks like Django which already uses the ActiveRecord pattern.
I’ve been in companies big and small using Python, both using and ignoring architectural patterns. Turns out all the big ones with strict architectural (n=3) pattern usage, although “clean”, the code is waaaay to complex and unnecessarily slow in tasks that at first glance should had been simple.
Whereas the big companies that didn’t care for these although the code was REALLY ugly in some places (huge if-else files/functions, huge Django models with all business logic implemented in them), I was most productive because although the code was ugly I could read it, understand it, and modify the 1000 lines of if-else statements.
Maybe this says something about me more than the code but I hate to admit I was more productive in the non clean code companies. And don’t get me started on the huge amount of discussions they avoided on what’s clean or not.
Some parts of this book are extremely useful, especially when it's talking about concepts that are more general than Python or any other specific language -- such as event-driven architecture, commands, CQRS etc.
That being said, I have a number issues with other parts of it, and I have seen how dangerous it can be when inexperienced developers take it as a gospel and try to implement everything at once (which is a common problem with any collection of design patterns like this.
For example, repository is a helpful pattern in general; but in many cases, including the examples in the book itself, it is a huge overkill that adds complexity with very little benefit. Even more so as they're using SQLAlchemy, which is a "repository" in its own right (or, more precisely, a relational database abstraction layer with an ORM added on top).
Similarly, service layers and unit of work are useful when you have complex applications that cover multiple complex use cases; but in a system consisting of small services with narrow responsibilities they quickly become overly bloated using this pattern. And don't even get me started with dependency injection in Python.
The essential thing about design patterns is that they're tools like any other, and the developers should understand when to use them, and even more importantly when not to use them. This book has some advice in that direction, but in my opinion it should be more prominent and placed upfront rather at the end of each chapter.
I’m a Typescript dev but this book is one of my favorite architecture books, I reference it all the time. My favorite pattern is the fake unit of work/service patterns for testing, I use this religiously in all my projects for faking (not mocking!!) third party services. It also helped me with dilemmas around naming, eg it recommends naming events in a very domain specific way rather than infrastructure or pattern specific way (eg CART_ITEM_BECAME_UNAVAILABLE is better than USER_NOTIFICATION). Some of these things are obvious but tedious to explain to teammates, so the fact that cosmic python is fully online makes it really easy to link to. Overall, a fantastic and formative resource for me!
I grew tired from the forced OOP mindset, where you have to enforce encapsulation and inheritance on everything, where you only have private fields which are set through methods.
I grew tired of SOLID, clean coding, clean architecture, GoF patterns and Uncle Bob.
I grew tired of the Kingdom of Nouns and of FizzBuzz Enterprise Editions.
I now follow imperative or functional flows with least OOP as possible.
In the rare cases I use Python (not because I don't want to, but because I mainly use .NET at work) I want the experience to be free of objects and patterns.
I am not trying to say that this book doesn't have a value. It does. It's useful to learn some patterns. But don't try to fit everything in real life programming. Don't make everything about patterns, objects and SOLID.
- Reimplement SQLAlchemy models (we'll call it a "repository")
- Reimplement SQLAlchemy sessions ("unit of work")
- Add a "service layer" that doesn't even use the models -- we unroll all the model attributes into separate function parameters because that's less coupled somehow
- Scatter everything across a message bus to remove any hope of debugging it
- AND THIS IS JUST FOR WRITES!
- For reads, we have a separate fucking denormalized table that we query using raw SQL. (Seriously, see Chapter 12)
Hey, let's see how much traffic MADE.com serves. 500k total visits from desktop + mobile last month works out to... 12 views per MINUTE.
Gee, I wish my job was cushy enough that I could spend all day writing about "DDD" with my thumb up my ass.
I started writing python professionally a few years ago. Coming from Kotlin and TypeScript, I found the language approachable but I was struggling to build things in an idiomatic fashion that achieved the loose coupling and testability that I was used to. I bought this book after a colleague recommended it and read it cover to cover. It really helped me get my head around ways to manage complexity in non trivial Python codebases. I don’t follow every pattern it recommends, but it opened my eyes to what’s possible and how to apply my experience in other paradigms to Python without it becoming “Java guy does Python”.
Truly one of the great python programming books. The one thing that I found missing was the lack of static typing in the code, but that was a deliberate decision by the authors.
I have this on my shelf. It's a small volume, similar to K&R, and like that book mine is showing visible signs of wear as I've thumbed through it a lot.
This was a great read and summary! About three years ago, I worked in a C#/.NET DDD environment, and now revisiting these concepts in Python really distills the essential parts. As I said, great read — highly recommend it if you're also into this kind of stuff.
Oh neat, I read the paper back of this book maybe two and a half or three years or so ago. I enjoyed it quite a bit. They do a good job at keeping tests a first class topic and consistently updating them with each addition. Some older architecture books don't treat testing as being as high up in their priorities. I've just found that having tests ready, easy to write, and easy to update, makes the development process more enjoyable for me since it's less manual for running the code to check for issue - tighter feedback look I guess.
I will say that some of the event oriented parts of this book were very interesting, but didn't seem as practical to implement in my current work.
Even though most people might think of web architectures when it comes to this book, we used this to design an architecture for an AI that optimises energy efficiency in a manufacturing factory.
I don’t understand the need for most of the patterns described in this book. Why abstract away SQLalchemy using a Repository when it is already an abstraction over the database? What’s the purpose of the unit of work? To me hand rolling SQL is much more maintainable than this abstraction soup
Unfortunately https://www.cosmicpython.com/book/ does give a 404 - this is a very bad architectural choice for web applications. I hope their other tips are better.
Architecture Patterns with Python
(cosmicpython.com)487 points by asicsp 28 March 2025 | 140 comments
Comments
Having said that, from a practical and experience standpoint, using some of these patterns can really spiral out into an increased complexity and performance issues in Python, specially when you use already opinionated frameworks like Django which already uses the ActiveRecord pattern.
I’ve been in companies big and small using Python, both using and ignoring architectural patterns. Turns out all the big ones with strict architectural (n=3) pattern usage, although “clean”, the code is waaaay to complex and unnecessarily slow in tasks that at first glance should had been simple.
Whereas the big companies that didn’t care for these although the code was REALLY ugly in some places (huge if-else files/functions, huge Django models with all business logic implemented in them), I was most productive because although the code was ugly I could read it, understand it, and modify the 1000 lines of if-else statements.
Maybe this says something about me more than the code but I hate to admit I was more productive in the non clean code companies. And don’t get me started on the huge amount of discussions they avoided on what’s clean or not.
That being said, I have a number issues with other parts of it, and I have seen how dangerous it can be when inexperienced developers take it as a gospel and try to implement everything at once (which is a common problem with any collection of design patterns like this.
For example, repository is a helpful pattern in general; but in many cases, including the examples in the book itself, it is a huge overkill that adds complexity with very little benefit. Even more so as they're using SQLAlchemy, which is a "repository" in its own right (or, more precisely, a relational database abstraction layer with an ORM added on top).
Similarly, service layers and unit of work are useful when you have complex applications that cover multiple complex use cases; but in a system consisting of small services with narrow responsibilities they quickly become overly bloated using this pattern. And don't even get me started with dependency injection in Python.
The essential thing about design patterns is that they're tools like any other, and the developers should understand when to use them, and even more importantly when not to use them. This book has some advice in that direction, but in my opinion it should be more prominent and placed upfront rather at the end of each chapter.
I grew tired from the forced OOP mindset, where you have to enforce encapsulation and inheritance on everything, where you only have private fields which are set through methods.
I grew tired of SOLID, clean coding, clean architecture, GoF patterns and Uncle Bob.
I grew tired of the Kingdom of Nouns and of FizzBuzz Enterprise Editions.
I now follow imperative or functional flows with least OOP as possible.
In the rare cases I use Python (not because I don't want to, but because I mainly use .NET at work) I want the experience to be free of objects and patterns.
I am not trying to say that this book doesn't have a value. It does. It's useful to learn some patterns. But don't try to fit everything in real life programming. Don't make everything about patterns, objects and SOLID.
- Reimplement SQLAlchemy models (we'll call it a "repository")
- Reimplement SQLAlchemy sessions ("unit of work")
- Add a "service layer" that doesn't even use the models -- we unroll all the model attributes into separate function parameters because that's less coupled somehow
- Scatter everything across a message bus to remove any hope of debugging it
- AND THIS IS JUST FOR WRITES!
- For reads, we have a separate fucking denormalized table that we query using raw SQL. (Seriously, see Chapter 12)
Hey, let's see how much traffic MADE.com serves. 500k total visits from desktop + mobile last month works out to... 12 views per MINUTE.
Gee, I wish my job was cushy enough that I could spend all day writing about "DDD" with my thumb up my ass.
I cannot recommend it enough. Worth every penny.
I will say that some of the event oriented parts of this book were very interesting, but didn't seem as practical to implement in my current work.
Great book!
I actually do. It’s slow, buggy and not type safe.
Everything good about Python is actually C, namely the good packages. They’re not written in Python, because Python is shit.