Django structure for scale and longevity

Why? Django is great. But as we add new features, as our dev team grows and the software needs to be stable on production, things can get quite messy. We are going to look at some common patterns, derived from experience, on how to structure your Django project for scale and longevity. What? Main topics are: Django service layer or where should business logic live? Using Django Rest Framework in a clean and repeatable way and combining it with the service layer. Testing everything that matters, without repeating ourselves in different tests. We are going to talk about when to rely on existing abstraction so it's actually helpful and when to avoid existing abstraction, and code things ourselves. The examples showed in this talk are derived from working with Django in the last 5 years on projects with: Daily production usage and production deploys. Dozens of apps. Hundreds of models and APIs. Tens of integrations working simultaneously. Teams of 5 to 10 people. Who? Key takeaways from the talk: Increased productivity when developing with Django. Deeper understanding of the software development process with Django. Demo project with everything mentioned in it. The talk is great for all levels of Django knowledge - from beginners to advanced users and teams. How The main way of getting the point across is going to be by showing regular code, talking how it can get messy and then following up with examples of improving that code. Hopefully this talk will start a lot of discussion afterwards. Breakdown of the talk: Django service layer: Fat models or fat views? Where do I put my business logic? What is a service and what goes into a service? What is a selector and what goes into a selector? General Django structure: How many apps should I have? Structuring your code so youр team can be more productive and have less conflicts. Common modules and utilities. Doing APIs with Django Rest Framework: Splitting APIs in 2 groups - "giving data" and "taking data" Using a lot of generics for "give data" When do to selectors? Using no generics for "take data" (APIView + Services) Handling errors from services Inlining serializers and avoiding serializers reuse A neat inline_serializer util Introducing general error formatting for your API Testing all of that - what should be and not be tested?

Design Django Python Video

 The Pillars of Domain-Driven Design

Domain-Driven Design is neither a method nor a technology, it is a culture, a way of thinking about the needs of the customers first and putting an emphasis on their language and human interactions. The promise of DDD is to tackle complexity in the heart of software, and the means are plentiful and can be overwhelming. There are three pillars though, on which the whole approach stands. A focus on learning, language, and empathy. With the right mindset, it becomes simple to derive good models, keep them pure and aligned with the business. Simple is not easy, but done right Domain-Driven Design transforms everything in your organization from code to culture, from agile to architecture.

DDD Event Sourcing Video

 Stability Patterns & Antipatterns • Michael T. Nygard

Once you hit Release 1.0, your system will be living in the real world. It has to survive everything the messy, noisy real world can throw at it: from flash mobs to Twitter. Once the public starts [...]

Architecture Systems Video

 Everyone Is Still Terrible At Creating Software At Scale

I have a hunch that once people saw the economic potential of software, they started looking for ways to "scale it up" and we haven't stopped searching yet.

Philosophy Software Development

 Unconditional Code • Michael Feathers

Many systems are full of error checks and conditional logic. They introduce discontinuities that make reasoning difficult. In this talk, Michael Feathers will present a conceptual framework for dealing with errors, conditionality and decision making at the level of code, architecture and user interface. Often by changing design and revisiting requirements we can make various error cases impossible, and make code and architecture simpler as well as more robust.

Abstraction Design Video

 Complex Adaptive Systems - Dave Snowden

Abstraction Philosophy Video

 Paradigms Without Progress: Kuhnian Reflections on Programming Practice

Borrowing from Thomas Kuhn, Robert Floyd introduced the notion of a programming paradigm. Today, paradigms are constantly debated. What might Kuhn tell us about this sad state of affairs? What can Programming learn from Philosophy?.

Paradigms Philosophy Video

 Higher Kinded Types in Python

* What Higher Kinded Types (HKTs) are and why they are useful * How they are implemented and what limitations there are * How can you use them in your own projects

Python

 Is High Quality Software Worth the Cost?

A common debate in software development projects is between spending time on improving the quality of the software versus concentrating on releasing more valuable features. Usually the pressure to deliver functionality dominates the discussion, leading many developers to complain that they don't have time to work on architecture and code quality.

Code quality Martin Fowler

 Greg Young - How to get productive in a project in 24h

So you are entering a new contract, or maybe it's just a new project you are being transferred to. How do you get up, going, and committing on your first day? How to identify the areas of the system that are risky or problematic? This session looks at tools and strategies to reach this goal coming from a speaker who regularly works for less than a week with a team and needs to provide value within that period of time

Code quality Observability Video