Neut is a statically-typed, compiled programming language designed for building reliable and maintainable systems software. It emphasizes simplicity and explicitness through its C-like syntax, minimal built-in features, and focus on compile-time evaluation. Key features include a powerful macro system enabling metaprogramming and code generation, algebraic data types for representing data structures, and built-in support for pattern matching. Neut aims to empower developers to write efficient and predictable code by offering fine-grained control over memory management and avoiding hidden runtime behavior. Its explicit design choices and limited standard library encourage developers to build reusable components tailored to their specific needs, promoting code clarity and long-term maintainability.
The author details their process of creating a WebAssembly (Wasm) virtual machine (VM) written entirely in C. Driven by a desire for a lightweight, embeddable Wasm runtime for resource-constrained environments, they built the VM from scratch, implementing core features like the stack-based execution model, linear memory, and basic WebAssembly System Interface (WASI) support. The project focused on simplicity and understandability over performance, serving primarily as a learning exercise and a platform for experimentation with Wasm. The post walks through key aspects of the VM's design and implementation, including parsing the Wasm binary format, handling function calls, and managing memory. It also highlights the challenges faced and lessons learned during the development process.
Hacker News users generally praised the author's clear writing style and the educational value of the post. Several commenters discussed the project's performance, noting that it's not optimized for speed and suggesting potential improvements like just-in-time compilation. Some shared their own experiences with WASM interpreters and related projects, including comparisons to other implementations and alternative approaches like using a stack machine. Others appreciated the detailed explanation of the parsing and execution process, finding it helpful for understanding WASM internals. A few users pointed out minor corrections or areas for potential enhancement in the code, demonstrating active engagement with the technical details.
Inboxbooster, a Y Combinator-backed company, is hiring a fully remote JVM Bytecode Engineer. This role involves working on their core email deliverability product by developing and maintaining a Java agent that modifies bytecode at runtime. Ideal candidates are proficient in Java, bytecode manipulation libraries like ASM or Javassist, and have experience with performance optimization and debugging. Familiarity with email deliverability concepts is a plus.
Hacker News users discussing the Inboxbooster job posting largely focused on the low salary range ($60k-$80k) offered for a JVM Bytecode Engineer, especially given the specialized and in-demand nature of the skillset. Many commenters found this range significantly below market value, even considering the potential for remote work. Some speculated about the reasoning, suggesting either a misjudgment of the market by the company or a targeting of less experienced engineers. The remote aspect was also discussed, with some suggesting it might be a way to justify the lower salary, while others pointed out that top talent in this area can command high salaries regardless of location. A few commenters expressed skepticism about the YC backing given the seemingly low budget for engineering talent.
Mukul Rathi details his journey of creating a custom programming language, focusing on the compiler construction process. He explains the key stages involved, from lexing (converting source code into tokens) and parsing (creating an Abstract Syntax Tree) to code generation and optimization. Rathi uses his language, which he implements in OCaml, to illustrate these concepts, providing code examples and explanations of how each component works together to transform high-level code into executable machine instructions. He emphasizes the importance of understanding these foundational principles for anyone interested in building their own language or gaining a deeper appreciation for how programming languages function.
Hacker News users generally praised the article for its clarity and accessibility in explaining compiler construction. Several commenters appreciated the author's approach of building a complete, albeit simple, language instead of just a toy example. Some pointed out the project's similarity to the "Let's Build a Compiler" series, while others suggested alternative or supplementary resources like Crafting Interpreters and the LLVM tutorial. A few users discussed the tradeoffs between hand-written lexers/parsers and using parser generator tools, and the challenges of garbage collection implementation. One commenter shared their personal experience of writing a language and the surprising complexity of seemingly simple features.
Summary of Comments ( 27 )
https://news.ycombinator.com/item?id=43154883
HN commenters generally express interest in Neut, praising its focus on simplicity, safety, and explicitness. Several highlight the appealing aspects of linear types and the borrow checker, noting similarities to Rust but with a seemingly gentler learning curve. Some question the practical applicability of linear types for larger projects, while others anticipate its usefulness in specific domains like game development or embedded systems. A few commenters express skepticism about the limited standard library and the overall maturity of the project, but the overall tone is positive and curious about the language's potential. Performance, particularly relating to garbage collection or its lack thereof, is a recurring point of discussion, with some wondering about the potential for optimizations given the linear type system.
The Hacker News post for "Neut Programming Language" (https://news.ycombinator.com/item?id=43154883) has a modest number of comments, sparking a discussion around the language's unique features and potential applications.
Several commenters focus on Neut's core concept of "neural types," expressing interest in its potential for type-safe neural networks. One commenter highlights the challenge of representing complex neural network architectures within a type system, wondering how Neut handles concepts like skip connections and shared weights. Another commenter draws parallels with other typed functional programming languages used in machine learning, like Dex and F*. They question whether Neut offers significant advantages over these existing solutions.
The discussion also touches upon the practicalities of using Neut. One commenter inquires about the language's performance characteristics and the availability of debugging tools. Another raises the crucial question of integration with existing machine learning frameworks like TensorFlow or PyTorch. A separate comment expresses skepticism about the overall usefulness of strict typing for neural networks, arguing that the dynamic nature of the field often necessitates flexibility over rigid type safety.
A few comments delve into specific aspects of Neut's design. One points out the potential benefits of using dependent types for expressing tensor shapes and preventing common errors. Another discusses the implications of Neut's choice of Haskell as its implementation language.
Overall, the comments reflect a mixture of curiosity, skepticism, and cautious optimism. While some commenters are intrigued by Neut's novel approach to type safety in neural networks, others remain unconvinced of its practical benefits and express concerns about its integration with existing tools and workflows. The limited number of comments, however, prevents a truly in-depth exploration of the language's potential and drawbacks.