Effect Systems: A Better Alternative to Async Programming for Managing Side Effects
By
marvinborner
Hand-rolled, kettle-boiled, baked to perfection. Worth every minute at the bakery.
Summary
The article explores the concept of effect systems in programming, arguing that traditional async programming models are flawed and that effect systems provide a better abstraction for handling side effects like I/O, errors, and state. The author explains that functions are social constructs and that effect systems allow programmers to explicitly declare and manage computational effects, making code more predictable and maintainable. The piece serves as an introduction to effect systems for programmers familiar with async/await patterns.
Key quotes
· 5 pulledFunctions don't exist. They're made up. They're a social construct.
Your CPU doesn't know or care what functions are, they're purely a book-keeping abstraction that makes it easier for you to reason about your code.
Effect systems let you declare what your code does, not just how it does it.
Async programming is just @Inject time - it's about managing effects at the right time.
I want effects now. So here's what I wished I could have read a few weeks ago.
You might also wanna read
The Migration of Object-Oriented Programming Concepts Across Domains
The article discusses how object-oriented programming (OOP) is not disappearing but rather shifting across different domains, which the auth
blog.jsbarretto.com·6mo ago
Practical Implementation of Algebraic Effects in Software Development with Flix
This article provides a practical guide to implementing algebraic effects in real-world software development using Flix. It explains how eff
relax.software·8mo ago
Why Average LLM Use Is Likely Destroying Value in Software Development
The author argues that, contrary to prevailing hype, the average use of Large Language Models (LLMs) is likely destroying value rather than
unessays.substack.com·12h ago
How AI Accelerated Prototyping: From Idea to Tangible in Record Time
The author reflects on how AI has transformed their prototyping workflow. Previously, the biggest bottleneck was the time needed to scaffold
darylcecile.net·12h ago
GitLab 19.0 launches with Secrets Manager, agentic workflows, and self-hosted AI models
GitLab 19.0 has been released, positioning itself as an intelligent orchestration platform for DevSecOps. The release includes expanded secr
bit.ly·1d ago
Centralizing Error Handling in Rust with Custom AppError Enums
This article discusses the importance of centralizing error handling in Rust applications using a custom AppError enum combined with map_err