Type annotations are a formalized way to add some extra information about types to your project. Once you get through adding mypy to your project and annotate your code (remember you can do it automatically, at least to some extent) you will find yourself at the ocean of possibilities. This post will show the most […]
Category: python
mypy: how to use it in my project? Part 2: automatically annotate code
Even after successful integration of mypy with an existing project (see mypy: how to use it in my project part 1), there are tons of code that does not have type annotations. Adding them manually is an unimaginable amount of work. We may do it gradually (as suggested in part 1) or use tools to […]
mypy: how to use it in my project?
Type annotations are like comments Type annotations are a great addition to Python. Thanks to them, finally our IDEs are able to provide good quality autocompletion. They did not turn Python into statically typed language, though. If you put a wrong annotation (or forget to update it after code change), Python will still happily try […]
Implementing the Clean Architecture with Python – my book is here!
It is my pleasure to announce that my book is finally available to buy. 🙂 https://leanpub.com/implementing-the-clean-architecture The books focuses on practical aspects and is illustrated with tons of code snippets in Python. Don’t forget to check out a code repository with the project which is illustrating the book: http://github.com/Enforcer/clean-architecture
The Clean Architecture in Python. How to write testable and flexible code
An ideal project? If someone asked about the features of an ideal project, responses would surely mention a few specific things. First of all, an ideal project would have a clean codebase that is simple to read. Secondly, there should be high test coverage to ensure that the project works as expected. What is more, […]
Is your test suite wasting your time?
This article has been originally included in a PyconPL 2018 conference book. Abstract Nowadays there is no need for convincing anyone about the enormous advantages of writing automated tests for their code. Many developers had an occasion to feel total confidence in introducing changes to their codebases under the protection of vast test suites. The […]
Implementing Event Sourcing in Python – part 4, efficient read model with projections
This post is a part of Implementing Event Sourcing series. It consists of code snippets, thoughts and practical advice how to implement ES in your own project. The contents of this post will probably make the most sense if you also read all other parts. Then you should be ready to use it in your […]
Implementing Event Sourcing in Python – part 3, robust event store atop RethinkDB
This post is a part of Implementing Event Sourcing series. It consists of code snippets, thoughts and practical advice how to implement ES in your own project. The contents of this post will probably make most sense if you also read all other parts. Then you should be ready to use it in your own […]
Implementing Event Sourcing in Python – part 2, robust event store atop PostgreSQL
This post is a part of Implementing Event Sourcing series. It consists of code snippets, thoughts and practical advice how to implement ES in your own project. The contents of this post will probably make most sense if you also read all other parts. Then you should be ready to use it in your own […]
Implementing Event Sourcing in Python – part 1, aggregates
This post is a part of Implementing Event Sourcing series. It consists of code snippets, thoughts and practical advice how to implement ES in your own project. The contents of this post will probably make most sense if you also read all other parts. Then you should be ready to use it in your own […]