This blog post introduces an algebraic approach to representing and manipulating knitting patterns. It defines a knitting algebra based on two fundamental operations: knit and purl, along with transformations like increase and decrease, capturing the essential structure of stitch manipulations. These operations are combined with symbolic variables representing yarn colors and stitch types, allowing for formal representation of complex patterns and transformations like mirroring or rotating designs. The algebra enables automated manipulation and analysis of knitting instructions, potentially facilitating the generation of new patterns and supporting tools for knitters to explore variations and verify their designs. This formal, mathematical framework provides a powerful basis for developing software tools that can bridge the gap between abstract design and physical realization in knitting.
Clolog is a small, experimental logic programming language implemented in Clojure. It aims to bring the declarative power of Prolog to Clojure, allowing developers to define facts and rules, and then query those facts and rules using logical inference. Clolog supports basic Prolog features such as unification, backtracking, and recursion, and integrates seamlessly with existing Clojure code and data structures. While it's not a full-fledged Prolog implementation, it provides a lightweight and accessible way to experiment with logic programming within the Clojure ecosystem.
HN commenters generally expressed interest in Clolog, praising its simplicity and elegance. Some highlighted its potential as a pedagogical tool for introducing logic programming concepts. Others discussed its limitations, particularly around performance and the lack of certain features found in Prolog, like cut and negation. There was a short thread comparing it to miniKanren, with a commenter pointing out Clolog's more traditional Prolog-like syntax. A few users shared their experiences experimenting with the code, including porting it to other Lisps. Overall, the reception was positive, with many appreciating the project as a clean and understandable implementation of core logic programming ideas.
Clean is a new domain-specific language (DSL) built in Lean 4 for formally verifying zero-knowledge circuits. It aims to bridge the gap between circuit development and formal verification by offering a high-level, functional programming style for defining circuits, along with automated proofs of correctness within Lean's powerful theorem prover. Clean compiles to the intermediate representation used by the Circom zk-SNARK toolkit, enabling practical deployment of verified circuits. This approach allows developers to write circuits in a clear, maintainable way, and rigorously prove that these circuits correctly implement the desired logic, enhancing security and trust in zero-knowledge applications. The DSL includes features like higher-order functions and algebraic data types, enabling more expressive and composable circuit design than existing tools.
Several Hacker News commenters praise Clean's innovative approach to verifying zero-knowledge circuits, appreciating its use of Lean4 for formal proofs and its potential to improve the security and reliability of ZK systems. Some express excitement about Lean4's dependent types and metaprogramming capabilities, and how they might benefit the project. Others raise practical concerns, questioning the performance implications of using a theorem prover for this purpose, and the potential difficulty of debugging generated circuits. One commenter questions the comparison to other frameworks like Noir and Arkworks, requesting clarification on the specific advantages of Clean. Another points out the relative nascency of formal verification in the ZK space, emphasizing the need for further development and exploration. A few users also inquire about the tooling and developer experience, wondering about the availability of IDE support and debugging tools for Clean.
This 2015 blog post demonstrates how to leverage Lua's flexible syntax and metamechanisms to create a Domain Specific Language (DSL) for generating HTML. The author uses Lua's tables and functions to create a clean, readable syntax that abstracts away the verbosity of raw HTML. By overloading the concatenation operator and utilizing metatables, the DSL allows users to build HTML elements and structures in a declarative way, mirroring the structure of the output. This approach simplifies HTML generation within Lua, making the code cleaner and more maintainable. The post provides concrete examples showing how to define tags, attributes, and nested elements, offering a practical guide to building similar DSLs for other output formats.
Hacker News users generally praised the article for its clear explanation of building a DSL in Lua, particularly appreciating the focus on leveraging Lua's existing features and metamechanisms. Several commenters shared their own experiences and preferences for using Lua for DSLs, including its use in game development and configuration management. One commenter pointed out potential performance considerations when using this approach, suggesting that precompilation could mitigate some overhead. Others discussed alternative methods for building DSLs, such as using parser generators. The use of Lua's setfenv was highlighted, with some acknowledging its power while others expressing caution due to potential debugging difficulties. A few users also mentioned other languages like Fennel and Janet as interesting alternatives to Lua for similar purposes.
This blog post explores improving type safety and reducing boilerplate when communicating between iOS apps and WatchOS complications using Swift. The author introduces two Domain Specific Languages (DSLs) built with Swift's result builders. The first DSL simplifies defining data models shared between the app and complication, automatically generating the necessary Codable conformance and WatchConnectivity transfer code. The second DSL streamlines updating complications, handling the asynchronous nature of data transfer and providing compile-time checks for supported complication families. By leveraging these DSLs, the author demonstrates a cleaner, safer, and more maintainable approach to iOS/WatchOS communication, minimizing the risk of runtime errors.
HN commenters generally praised the approach outlined in the article for its type safety and potential to reduce bugs in iOS/WatchOS communication. Some expressed concern about the verbosity of the generated code and suggested exploring alternative approaches like protobuf or gRPC, while acknowledging their added complexity. Others questioned the necessity of a DSL for this specific problem, suggesting that Swift's existing features might suffice with careful design. The potential benefits for larger teams and complex projects were also highlighted, where the enforced type safety could prevent subtle communication errors. One commenter pointed out the similarity to Apache Thrift. Several users appreciated the author's clear explanation and practical example.
The blog post explores the feasibility and potential advantages of using existing telephone wiring (specifically the unused pairs in twisted-pair copper lines) for home networking. It highlights POTS's robust infrastructure and broad availability, even in areas lacking cable or fiber internet. The author discusses various modulation techniques like G.hn that could deliver speeds comparable to or exceeding current home network technologies while potentially offering better security and interference resistance than Wi-Fi. They also acknowledge challenges such as distance limitations, potential crosstalk with active phone lines (if present), and the need for new hardware. Overall, the post suggests that repurposing telephone wiring could be a viable and even superior alternative to traditional home networking methods.
Hacker News users generally found the idea of networking over phone lines intriguing, though impractical in most modern contexts. Several commenters discussed the technical details, pointing out limitations in bandwidth and the potential interference issues with existing phone services like DSL. Some reminisced about earlier phone networking attempts, including using BBS systems and dedicated phone-line networking hardware. The consensus was that while the technical challenge is interesting, existing solutions like Ethernet and WiFi are far superior for most residential networking needs, making this approach a novelty rather than a practical solution. A few users pointed out niche use cases, such as situations where running new cables is impossible or extremely difficult, suggesting a very limited potential application.
Ohm is a parsing toolkit designed for creating parsers in JavaScript and TypeScript that are both powerful and easy to use. It features a grammar definition syntax closely resembling EBNF, enabling developers to express complex syntax rules clearly and concisely. Ohm's built-in support for semantic actions allows users to directly embed JavaScript or TypeScript code within their grammar rules, simplifying the process of building abstract syntax trees (ASTs) and performing other actions during parsing. The toolkit provides excellent error reporting capabilities, helping developers quickly identify and fix syntax errors. Its flexible architecture makes it suitable for various applications, from validating user input to building full-fledged compilers and interpreters.
HN users generally expressed interest in Ohm, praising its user-friendliness, clear documentation, and the power offered by its grammar-based approach to parsing. Several compared it favorably to traditional parser generators like PEG.js and nearley, highlighting Ohm's superior error messages and easier learning curve. Some users discussed potential applications, including building linters, formatters, and domain-specific languages. A few questioned the performance implications of its JavaScript implementation, while others suggested potential improvements like adding support for left-recursive grammars. The overall sentiment leaned positive, with many eager to try Ohm in their own projects.
This blog post explores using Python decorators as a foundation for creating just-in-time (JIT) compilers. The author demonstrates this concept by building a simple JIT for a subset of Python, focusing on numerical computations. The approach uses decorators to mark functions for JIT compilation, leveraging Python's introspection capabilities to analyze the decorated function's Abstract Syntax Tree (AST). This allows the JIT to generate optimized machine code at runtime, replacing the original Python function. The post showcases how this technique can significantly improve performance for computationally intensive tasks while still maintaining the flexibility and expressiveness of Python. The example demonstrates transforming simple arithmetic operations into optimized machine code using LLVM, effectively turning Python into a domain-specific language (DSL) for numerical computation.
HN users generally praised the article for its clear explanation of using decorators for JIT compilation in Python, with several appreciating the author's approach to explaining a complex topic simply. Some commenters discussed alternative approaches to JIT compilation in Python, including using Numba and C extensions. Others pointed out potential drawbacks of the decorator-based approach, such as debugging challenges and the potential for unexpected behavior. One user suggested using a tracing JIT compiler as a possible improvement. Several commenters also shared their own experiences and use cases for JIT compilation in Python, highlighting its value in performance-critical applications.
Rhai is a fast and lightweight scripting language specifically designed for embedding within Rust applications. It boasts a simple, easy-to-learn syntax inspired by JavaScript and Rust, making it accessible for both developers and end-users. Rhai prioritizes performance and safety, leveraging Rust's ownership and borrowing system to prevent data races and other memory-related issues. It offers seamless integration with Rust, allowing direct access to Rust functions and data structures, and supports dynamic typing, custom functions, modules, and even asynchronous operations. Its versatility makes it suitable for a wide range of use cases, from game scripting and configuration to data processing and rapid prototyping.
HN commenters generally praised Rhai for its speed, ease of embedding, and Rust integration. Several users compared it favorably to Lua, citing better performance and a more "Rusty" feel. Some appreciated its dynamic typing and scripting-oriented nature, while others suggested potential improvements like static typing or a WASM target. The discussion touched on use cases like game scripting, configuration, and embedded systems, highlighting Rhai's versatility. A few users expressed interest in contributing to the project. Concerns raised included the potential performance impact of dynamic typing and the relatively small community size compared to more established scripting languages.
Summary of Comments ( 4 )
https://news.ycombinator.com/item?id=43763614
HN users were generally impressed with the algebraic approach to knitting, finding it a novel and interesting application of formal methods. Several commenters with knitting experience appreciated the potential for generating complex patterns and automating aspects of the design process. Some discussed the possibility of using similar techniques for other crafts like crochet or weaving. A few questioned the practicality for everyday knitters, given the learning curve involved in understanding the algebraic notation. The connection to functional programming was also noted, with comparisons made to Haskell and other declarative languages. Finally, there was some discussion about the limitations of the current implementation and potential future directions, like incorporating color changes or more complex stitch types.
The Hacker News post "Algebraic Semantics for Machine Knitting" (linking to an article about the same topic) generated a moderate discussion with several interesting comments.
Many commenters expressed fascination with the intersection of seemingly disparate fields like abstract algebra and knitting. One commenter highlighted the beauty of finding mathematical structures in unexpected places, echoing a sentiment shared by several others. They found the idea of formalizing knitting patterns with algebraic structures intriguing and intellectually stimulating.
A recurring theme was the potential for this research to improve existing knitting software. Commenters envisioned applications like better stitch visualization, more powerful pattern generation tools, and even automated error correction in knitting designs. One commenter specifically mentioned the possibility of creating software that could translate between different knitting machine formats, a long-standing challenge in the knitting community.
Some commenters with a technical background delved into the specifics of the algebraic structures used, discussing category theory and its potential relevance to this area. They speculated about the practical implications of using these advanced mathematical tools, including the possibility of optimizing yarn usage or creating entirely new knitting techniques.
A few commenters also touched upon the broader implications of this research for craft and technology. They saw this work as an example of how seemingly traditional crafts can benefit from modern computational methods. The idea of bridging the gap between digital fabrication and traditional handcrafts resonated with several commenters, suggesting a growing interest in this intersection.
While there wasn't extensive debate or controversy, a couple of commenters expressed skepticism about the immediate practical applications of the research. They acknowledged the intellectual merit of the work but questioned whether it would lead to tangible improvements in knitting software or techniques in the near future. However, even these skeptical comments were generally respectful and acknowledged the potential long-term benefits of the research.
Overall, the comments reflected a positive reception to the research, with many expressing excitement about the potential applications and the novelty of applying abstract algebra to the craft of knitting. The discussion was insightful and touched upon various aspects of the research, from its technical details to its broader implications for craft and technology.