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I'm happy to announce that guile-websocket 0.2.0 has been released! Guile-websocket is an implementation of the WebSocket protocol, both the client and server sides, for Guile Scheme. This release introduces breaking changes that overhaul the client and server implementations in order to support non-blocking I/O and TLS encrypted connections. source tarball: https://files.dthompson.us/guile-websocket/guile-websocket-0.2.0.tar.gz signature: https://files.dthompson.us/guile-websocket/guile-websocket-0.2.0.tar.gz.asc See the guile-websocket project page for more information. Bug reports, bug fixes, feature requests, and patches are welcomed.
Wasm GC is a wonderful thing that is now available in all major web browsers since slowpoke Safari/WebKit finally shipped it in December. It provides a hierarchy of heap allocated reference types and a set of instructions to operate on them. Wasm GC enables managed memory languages to take advantage of the advanced garbage collectors inside web browser engines. It’s now possible to implement a managed memory language without having to ship a GC inside the binary. The result is smaller binaries, better performance, and better integration with the host runtime. However, Wasm GC has some serious drawbacks when compared to linear memory. I enjoy playing around with realtime graphics programming in my free time, but I was disappointed to discover that Wasm GC just isn’t a good fit for that right now. I decided to write this post because I’d like to see Wasm GC on more or less equal footing with linear memory when it comes to binary data manipulation. Hello triangle For starters, let's take a look at what a “hello triangle” WebGL demo looks like with Wasm GC. I’ll use Hoot, the Scheme to Wasm compiler that I work on, to build it. Below is a Scheme program that declares imports for the subset of the WebGL, HTML5 Canvas, etc. APIs that are necessary and then renders a single triangle: (use-modules (hoot ffi)) ;; Document (define-foreign get-element-by-id "document" "getElementById" (ref string) -> (ref null extern)) ;; Element (define-foreign element-width "element" "width" (ref extern) -> i32) (define-foreign element-height "element" "height" (ref extern) -> i32) ;; Canvas (define-foreign get-canvas-context "canvas" "getContext" (ref extern) (ref string) -> (ref null extern)) ;; WebGL (define GL_VERTEX_SHADER 35633) (define GL_FRAGMENT_SHADER 35632) (define GL_COMPILE_STATUS 35713) (define GL_LINK_STATUS 35714) (define GL_ARRAY_BUFFER 34962) (define GL_STATIC_DRAW 35044) (define GL_COLOR_BUFFER_BIT 16384) (define GL_TRIANGLES 4) (define GL_FLOAT 5126) (define-foreign gl-create-shader "gl" "createShader" (ref extern) i32 -> (ref extern)) (define-foreign gl-delete-shader "gl" "deleteShader" (ref extern) (ref extern) -> none) (define-foreign gl-shader-source "gl" "shaderSource" (ref extern) (ref extern) (ref string) -> none) (define-foreign gl-compile-shader "gl" "compileShader" (ref extern) (ref extern) -> none) (define-foreign gl-get-shader-parameter "gl" "getShaderParameter" (ref extern) (ref extern) i32 -> i32) (define-foreign gl-get-shader-info-log "gl" "getShaderInfoLog" (ref extern) (ref extern) -> (ref string)) (define-foreign gl-create-program "gl" "createProgram" (ref extern) -> (ref extern)) (define-foreign gl-delete-program "gl" "deleteProgram" (ref extern) (ref extern) -> none) (define-foreign gl-attach-shader "gl" "attachShader" (ref extern) (ref extern) (ref extern) -> none) (define-foreign gl-link-program "gl" "linkProgram" (ref extern) (ref extern) -> none) (define-foreign gl-use-program "gl" "useProgram" (ref extern) (ref extern) -> none) (define-foreign gl-get-program-parameter "gl" "getProgramParameter" (ref extern) (ref extern) i32 -> i32) (define-foreign gl-get-program-info-log "gl" "getProgramInfoLog" (ref extern) (ref extern) -> (ref string)) (define-foreign gl-create-buffer "gl" "createBuffer" (ref extern) -> (ref extern)) (define-foreign gl-delete-buffer "gl" "deleteBuffer" (ref extern) (ref extern) -> (ref extern)) (define-foreign gl-bind-buffer "gl" "bindBuffer" (ref extern) i32 (ref extern) -> none) (define-foreign gl-buffer-data "gl" "bufferData" (ref extern) i32 (ref eq) i32 -> none) (define-foreign gl-enable-vertex-attrib-array "gl" "enableVertexAttribArray" (ref extern) i32 -> none) (define-foreign gl-vertex-attrib-pointer "gl" "vertexAttribPointer" (ref extern) i32 i32 i32 i32 i32 i32 -> none) (define-foreign gl-draw-arrays "gl" "drawArrays" (ref extern) i32 i32 i32 -> none) (define-foreign gl-viewport "gl" "viewport" (ref extern) i32 i32 i32 i32 -> none) (define-foreign gl-clear-color "gl" "clearColor" (ref extern) f64 f64 f64 f64 -> none) (define-foreign gl-clear "gl" "clear" (ref extern) i32 -> none) (define (compile-shader gl type source) (let ((shader (gl-create-shader gl type))) (gl-shader-source gl shader source) (gl-compile-shader gl shader) (unless (= (gl-get-shader-parameter gl shader GL_COMPILE_STATUS) 1) (let ((info (gl-get-shader-info-log gl shader))) (gl-delete-shader gl shader) (error "shader compilation failed" info))) shader)) (define (link-shader gl vertex-shader fragment-shader) (let ((program (gl-create-program gl))) (gl-attach-shader gl program vertex-shader) (gl-attach-shader gl program fragment-shader) (gl-link-program gl program) (unless (= (gl-get-program-parameter gl program GL_LINK_STATUS) 1) (let ((info (gl-get-program-info-log gl program))) (gl-delete-program gl program) (error "program linking failed" info))) program)) ;; Setup GL context (define canvas (get-element-by-id "canvas")) (define gl (get-canvas-context canvas "webgl")) (when (external-null? gl) (error "unable to create WebGL context")) ;; Compile shader (define vertex-shader-source "attribute vec2 position; attribute vec3 color; varying vec3 fragColor; void main() { gl_Position = vec4(position, 0.0, 1.0); fragColor = color; }") (define fragment-shader-source "precision mediump float; varying vec3 fragColor; void main() { gl_FragColor = vec4(fragColor, 1); }") (define vertex-shader (compile-shader gl GL_VERTEX_SHADER vertex-shader-source)) (define fragment-shader (compile-shader gl GL_FRAGMENT_SHADER fragment-shader-source)) (define shader (link-shader gl vertex-shader fragment-shader)) ;; Create vertex buffer (define stride (* 4 5)) (define buffer (gl-create-buffer gl)) (gl-bind-buffer gl GL_ARRAY_BUFFER buffer) (gl-buffer-data gl GL_ARRAY_BUFFER #f32(-1.0 -1.0 1.0 0.0 0.0 1.0 -1.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 1.0) GL_STATIC_DRAW) ;; Draw (gl-viewport gl 0 0 (element-width canvas) (element-height canvas)) (gl-clear gl GL_COLOR_BUFFER_BIT) (gl-use-program gl shader) (gl-enable-vertex-attrib-array gl 0) (gl-vertex-attrib-pointer gl 0 2 GL_FLOAT 0 stride 0) (gl-enable-vertex-attrib-array gl 1) (gl-vertex-attrib-pointer gl 1 3 GL_FLOAT 0 stride 8) (gl-draw-arrays gl GL_TRIANGLES 0 3) Note that in Scheme, the equivalent of a Uint8Array is a bytevector. Hoot uses a packed array, an (array i8) specifically, for the contents of a bytevector. And here is the JavaScript code necessary to boot the resulting Wasm binary: window.addEventListener("load", async () => { function bytevectorToUint8Array(bv) { let len = reflect.bytevector_length(bv); let array = new Uint8Array(len); for (let i = 0; i < len; i++) { array[i] = reflect.bytevector_ref(bv, i); } return array; } let mod = await SchemeModule.fetch_and_instantiate("triangle.wasm", { reflect_wasm_dir: 'reflect-wasm', user_imports: { document: { getElementById: (id) => document.getElementById(id) }, element: { width: (elem) => elem.width, height: (elem) => elem.height }, canvas: { getContext: (elem, type) => elem.getContext(type) }, gl: { createShader: (gl, type) => gl.createShader(type), deleteShader: (gl, shader) => gl.deleteShader(shader), shaderSource: (gl, shader, source) => gl.shaderSource(shader, source), compileShader: (gl, shader) => gl.compileShader(shader), getShaderParameter: (gl, shader, param) => gl.getShaderParameter(shader, param), getShaderInfoLog: (gl, shader) => gl.getShaderInfoLog(shader), createProgram: (gl, type) => gl.createProgram(type), deleteProgram: (gl, program) => gl.deleteProgram(program), attachShader: (gl, program, shader) => gl.attachShader(program, shader), linkProgram: (gl, program) => gl.linkProgram(program), useProgram: (gl, program) => gl.useProgram(program), getProgramParameter: (gl, program, param) => gl.getProgramParameter(program, param), getProgramInfoLog: (gl, program) => gl.getProgramInfoLog(program), createBuffer: (gl) => gl.createBuffer(), deleteBuffer: (gl, buffer) => gl.deleteBuffer(buffer), bindBuffer: (gl, target, buffer) => gl.bindBuffer(target, buffer), bufferData: (gl, buffer, data, usage) => { let bv = new Bytevector(reflect, data); gl.bufferData(buffer, bytevectorToUint8Array(bv), usage); }, enableVertexAttribArray: (gl, index) => gl.enableVertexAttribArray(index), vertexAttribPointer: (gl, index, size, type, normalized, stride, offset) => { gl.vertexAttribPointer(index, size, type, normalized, stride, offset); }, drawArrays: (gl, mode, first, count) => gl.drawArrays(mode, first, count), viewport: (gl, x, y, w, h) => gl.viewport(x, y, w, h), clearColor: (gl, r, g, b, a) => gl.clearColor(r, g, b, a), clear: (gl, mask) => gl.clear(mask) } } }); let reflect = await mod.reflect({ reflect_wasm_dir: 'reflect-wasm' }); let proc = new Procedure(reflect, mod.get_export("$load").value); proc.call(); }); Hello problems There are two major performance issues with this program. One is visible in the source above, the other is hidden in the language implementation. Heap objects are opaque on the other side Wasm GC heap objects are opaque to the host. Likewise, heap objects from the host are opaque to the Wasm guest. Thus the contents of an (array i8) object are not visible from JavaScript and the contents of a Uint8Array are not visible from Wasm. This is a good security property in the general case, but it’s a hinderance in this specific case. Let’s say we have an (array i8) full of vertex data we want to put into a WebGL buffer. To do this, we must make one JS->Wasm call for each byte in the array and store it into a Uint8Array. This is what the bytevectorToUint8Array function above is doing. Copying any significant amount of data per frame is going to tank performance. Hope you aren’t trying to stream vertex data! Contrast the previous paragraph with Wasm linear memory. A WebAssembly.Memory object can be easily accessed from JavaScript as an ArrayBuffer. To get a blob of vertex data out of a memory object, you just need to know the byte offset and length and you’re good to go. There are many Wasm linear memory applications using WebGL successfully. Manipulating multi-byte binary data is inefficient To read a multi-byte number such as an unsigned 32-bit integer from an (array i8), you have to fetch each individual byte and combine them together. Here’s a self-contained example that uses Guile-flavored WAT format: (module (type $bytevector (array i8)) (data $init #u32(123456789)) (func (export "main") (result i32) (local $a (ref $bytevector)) (local.set $a (array.new_data $bytevector $init (i32.const 0) (i32.const 4))) (array.get_u $bytevector (local.get $a) (i32.const 0)) (i32.shl (array.get_u $bytevector (local.get $a) (i32.const 1)) (i32.const 8)) (i32.or) (i32.shl (array.get_u $bytevector (local.get $a) (i32.const 2)) (i32.const 16)) (i32.or) (i32.shl (array.get_u $bytevector (local.get $a) (i32.const 3)) (i32.const 24)) (i32.or))) By contrast, Wasm linear memory needs but a single i32.load instruction: (module (memory 1) (func (export "main") (result i32) (i32.store (i32.const 0) (i32.const 123456789)) (i32.load (i32.const 0)))) Easy peasy. Not only is it less code, it's a lot more efficient. Unsatisfying workarounds There’s no way around the multi-byte problem at the moment, but for byte access from JavaScript there are some things we could try to work with what we have been given. Spoiler alert: None of them are pleasant. Use Uint8Array from the host This approach makes all binary operations from within the Wasm binary slow since we’d have to cross the Wasm->JS bridge for each read/write. Since most of the binary data manipulation is happening in the Wasm module, this approach will just make things slower overall. Use linear memory for bytevectors This would require a little malloc/free implementation and a way to reclaim memory for GC'd bytevectors. You could register every bytevector in a FinalizationRegistry in order to be notified upon GC and free the memory. Now you have to deal with memory fragmentation. This is Wasm GC, we shouldn’t have to do any of this! Use linear memory as a scratch space This avoids crossing the Wasm/JS boundary for each byte, but still involves a byte-by-byte copy from (array i8) to linear memory within the Wasm module. So far this feels like the least worst option, but the extra copy is still going to greatly reduce throughput. Wasm GC needs some fixin' I’ve used realtime graphics as an example because it’s a use case that is very sensitive to performance issues, but this unfortunate need to copy binary data byte-by-byte is also the reason why strings are trash on Wasm GC right now. Stringref is a good proposal and the Wasm community group made a mistake by rejecting it. Anyway, there has been some discussion about both multi-byte and ArrayBuffer access on GitHub, but as far as I can tell neither issue is anywhere close to a resolution. Can these things be implemented efficiently? How can the need for direct access to packed arrays from JS be reconciled with Wasm heap object opaqueness? I hope the Wasm community group can arrive at solutions sooner than later because it will take a long time to get the proposal(s) to phase 4 and shipped in all browsers, perhaps years. It would be a shame to be effectively shut out from using WebGPU when it finally reaches stable browser releases.
I'm pleased to announce that the very first release of guile-bstructs, version 0.1.0, has been released! This is a library I've been working on for quite some time and after more than one rewrite and many smaller refactors I think it's finally ready to release publicly. Let's hope I'm not wrong about that! About guile-bstructs Guile-bstructs is a library that provides structured read/write access to binary data for Guile. A bstruct (short for “binary structure”) is a data type that encapsulates a bytevector and a byte offset which interprets that bytevector based on a specified layout. Some use cases for bstructs are: manipulating C structs when using the foreign function interface packing GPU vertex buffers when using graphics APIs such as OpenGL implementing data types that benefit from Guile's unboxed math optimizations such as vectors and matrices This library was initially inspired by guile-opengl's define-packed-struct syntax but is heavily based on "Ftypes: Structured foreign types" by Andy Keep and R. Kent Dybvig. The resulting interface is quite similar but the implementation is completely original. This library provides a syntax-heavy interface; nearly all of the public API is syntax. This is done to ensure that bstruct types are static and well-known at compile time resulting in efficient bytecode and minimal runtime overhead. A subset of the interface deals in raw bytevector access for accessing structured data in bytevectors directly without going through an intermediary bstruct wrapper. This low-level interface is useful for certain batch processing situations where the overhead of creating wrapper bstructs would hinder throughput. Example Here are some example type definitions to give you an idea of what it’s like to use guile-bstructs: ;; Struct (define-bstruct <vec2> (padded (struct (x float) (y float)))) ;; Type group with a union (define-bstruct (<mouse-move-event> (struct (type uint8) (x int32) (y int32))) (<mouse-button-event> (struct (type uint8) (button uint8) (state uint8) (x int32) (y int32))) (<event> (union (type uint8) (mouse-move <mouse-move-event>) (mouse-button <mouse-button-event>)))) ;; Array (define-bstruct <matrix4> (array 16 float)) ;; Bit fields (define-bstruct <date> (bits (year 32 s) (month 4 u) (day 5 u))) ;; Pointer (define-bstruct (<item> (struct (type int))) (<chest> (struct (opened? uint8) (item (* <item>))))) ;; Packed struct modifier (define-bstruct <enemy> (packed (struct (type uint8) (health uint32)))) ;; Endianness modifier (define-bstruct <big-float> (endian big float)) ;; Recursive type (define-bstruct <node> (struct (item int) (next (* <node>)))) ;; Mutually recursive type group (define-bstruct (<forest> (struct (children (* <tree>)))) (<tree> (struct (value int) (forest (* <forest>)) (next (* <tree>))))) ;; Opaque type (define-bstruct SDL_GPUTexture) Download Source tarball: guile-bstructs-0.1.0.tar.gz GPG signature: guile-bstructs-0.1.0.tar.gz.asc This release was signed with this GPG key. See the guile-bstructs project page for more information.
The Spring Lisp Game Jam 2024 ended one week ago. 48 games were submitted, a new record for the jam! This past week has been a time for participants to play and rate each other’s games. As I explored the entries, I noticed two distinct meta-patterns in how people approached building games with Lisp. I think these patterns apply more broadly to all applications of Lisp. Let’s talk about these patterns in some detail, with examples. But first! Here’s the breakdown of the jam submissions by language: lang entries % (rounded) ---- ------- ----------- guile 15 31 fennel 10 21 clojure 5 10 cl 5 10 racket 4 8 elisp 4 8 s7 3 6 kawa 1 2 owl 1 2 I haven’t rolled up the various Schemes (Guile, Racket, S7, Kawa) into a general scheme category because Scheme is so minimally specified and they are all very distinct implementations for different purposes, not to mention that Racket has a lot more going on than just Scheme. For the first time ever, Guile came out on top with the most submissions! There’s a very specific reason for this outcome. 11 out of the 15 Guile games were built for the web with Hoot, a Scheme-to-WebAssembly compiler that I work on at the Spritely Institute. 2 of those 11 were official Spritely projects. We put out a call for people to try making games with Hoot before the jam started, and a lot of people took us up on it! Very cool! The next most popular language, which is typically the most popular language in these jams, is Fennel. Fennel is a Lisp that compiles to Lua. It’s very cool, too! Also of note, at least to me as a Schemer, is that three games used S7. Hmm, there might be something relevant to this post going on there. The patterns I’m about to talk about could sort of be framed as “The Guile Way vs. The Fennel Way”, but I don’t want to do that. It's not an “us vs. them” thing. It’s wonderful that there are so many flavors of Lisp these days that anyone can find a great implementation that suits their preferences. Not only that, but many of these implementations can be used to make games that anyone can easily play in their web browser! That was not the case several years ago. Incredible! I want to preface the rest of this post by saying that both patterns are valid, and while I prefer one over the other, that is not to say that the other is inferior. I'll also show how these patterns can be thought of as two ends of a spectrum and how, in the end, compromises must be made. Okay, let’s get into it! Lisp as icing The icing pattern is using Lisp as a “scripting” language on top of a cake that is made from C, Rust, and other static languages. The typical way to do this is by embedding a Lisp interpreter into the larger program. If you’re most interested in writing the high-level parts of an application in Lisp then this pattern is the fastest way to get there. All you need is a suitable interpreter/compiler and a way to add the necessary hooks into your application. Since the program is mainly C/Rust/whatever, you can then use emscripten to compile it to WebAssembly and deploy to the web. Instant gratification, but strongly tied to static languages and their toolchains. S7 is an example of an embeddable Scheme. Guile is also used for extending C programs, though typically that involves dynamically linking to libguile rather than embedding the interpreter into the program’s executable. Fennel takes a different approach, recognizing that there are many existing applications that are already extensible through Lua, and provides a lispy language that compiles to Lua. Lisp as cake The cake pattern is using Lisp to implement as much of the software stack as possible. It’s Lisp all the way down... sorta. Rather than embedding Lisp into a non-Lisp program, the cake pattern does the inverse: the majority of the program is written in Lisp. When necessary, shared libraries can be called via a foreign function interface, but this should be kept to a minimum. This approach takes longer to yield results. Time is spent implementing missing libraries for your Lisp of choice and writing wrappers around the C shared libraries you can’t avoid using. Web deployment gets trickier, too, since the project is not so easily emscriptenable. (You may recognize this as the classic embed vs. extend debate. You’re correct! I'm just adding my own thoughts and applying it specifically to some real-world Lisp projects.) I mentioned Guile as an option for icing, but Guile really shines best as cake. The initial vision for Guile was to Emacsify other programs by adding a Scheme interpreter to them. These days, the best practice is to write your program in Scheme to begin with. Common Lisp is probably the best example, though. Implementations like SBCL have good C FFIs and can compile efficient native executables, minimizing the desire to use some C for performance reasons. Case studies Let’s take a look at some of the languages and libraries used for the Lisp Game Jam and evaluate their icing/cake-ness. Fennel + love2d love2d has been a popular choice for solo or small team game development for many years. It is a C++ program that embeds a Lua interpreter, which means it’s a perfect target for Fennel. Most Linux distributions package love2d, so it’s easy to run .love files natively. Additionally, thanks to emscripten, love2d games can be deployed to the web. Thus most Fennel games use love2d. ./soko.bin and Gnomic Vengeance are two games that use this stack. Fennel + love2d is a perfect example of Lisp as icing. Fennel sits at the very top of the stack, but there’s not really a path to spread Lisp into the layers below. It is also the most successful Lisp game development stack to date. S7 + raylib This stack is new to me, but two games used it this time around: GhostHop and Life Predictor. (You really gotta play GhostHop, btw. It’s a great little puzzle game and it is playable on mobile devices.) Raylib is a C library with bindings for many higher-level languages that has become quite popular in recent years. S7 is also implemented in C and is easily embeddable. This makes the combination easy to deploy on the web with emscripten. S7 + raylib is another example of Lisp as icing. I’m curious to see if this stack becomes more popular in future jams. Guile + Chickadee This is the stack that I helped build. Chickadee is a game library for Guile that implements almost all of the interesting parts in Scheme, including rendering. Two games were built with Chickadee in the most recent jam: Turbo Racer 3000 and Bloatrunner. Guile + Chickadee is an example of Lisp as cake. Chickadee wraps some C libraries for low-level tasks such as loading images, audio, and fonts, but it is written in pure Scheme. All the matrix and vector math is in Scheme. Chickadee comes with a set of rendering primitives comparable to love2d and raylib but they’re all implemented in Scheme. I’ve even made progress on rendering vector graphics with Scheme, whereas most other Lisp game libraries use a C library such as nanosvg. Chickadee has pushed the limits of Guile’s compiler and virtual machine, and Guile has been improved as a result. But it’s the long road. Chickadee is mostly developed by me, alone, in my very limited spare time. It is taking a long time to reach feature parity with more popular game development libraries, but it works quite well for what it is. Hoot + HTML5 canvas I also helped build this one. Hoot is a Scheme-to-WebAssembly compiler. Rather than compile the Guile VM (written in C) to Wasm using emscripten, Hoot implements a complete Wasm toolchain and a new backend for Guile’s compiler that emits Wasm directly. Hoot is written entirely in Scheme. Unlike C programs compiled with emscripten that target Wasm 1.0 with linear memory, Hoot targets Wasm 2.0 with GC managed heap types. This gives Hoot a significant advantage: Hoot binaries do not ship a garbage collector and thus are much smaller than Lisp runtimes compiled via emscripten. The Wasm binary for my game weighs in at < 2MiB whereas the love2d game I checked had a nearly 6MiB love.wasm. Hoot programs can also easily interoperate with JavaScript. Scheme objects can easily be passed to JavaScript, and vice versa, as they are managed in the same heap. With all of the browser APIs just a Wasm import away, an obvious choice for games was the built-in HTML5 canvas API for easy 2D rendering. 11 games used Hoot in the jam, including (shameless plug) Cirkoban and Lambda Dungeon. Hoot + HTML5 canvas is mostly dense cake with a bit of icing. On one hand, it took a year and significant funding to boot Hoot. We said “no” to emscripten, built our own toolchain, and extended Guile’s compiler. It's Lisp all the way until you hit the browser runtime! We even have a Wasm interpreter that runs on the Guile VM! Hoot rules! It was a risk but it paid off. On the other hand, the canvas API is very high-level. The more cake thing to do would be to use Hoot’s JS FFI to call WebGL and/or WebGPU. Indeed, this is the plan for the future! Wasm GC needs some improvements to make this feasible, but my personal goal is to get Chickadee ported to Hoot. I want Chickadee games to be easy to play natively and in browsers, just like love2d games. The cake/icing spectrum I must acknowledge the limitations of the cake approach. We’re not living in a world of Lisp machines, but a world of glorified PDP-11s. Even the tallest of Lisp cakes sits atop an even larger cake made mostly of C. All modern Lisp systems bottom out at some point. Emacs rests on a C core. Guile’s VM is written in C. Hoot runs on mammoth JavaScript engines written in C++ like V8. Games on Hoot currently render with HTML5 canvas rather than WebGL/WebGPU. Good luck using OpenGL without libGL; Chickadee uses guile-opengl which uses the C FFI to call into libGL. Then there’s libpng, FreeType, and more. Who the heck wants to rewrite all this in Lisp? Who even has the resources? Does spending all this time taking the scenic route matter at all, or are we just deluding ourselves because we have fun writing Lisp code? I think it does matter. Every piece of the stack that can be reclaimed from the likes of C is a small victory. The parts written in Lisp are much easier to hack on, and some of those things become live hackable while our programs are running. They are also memory safe, typically, thanks to GC managed runtimes. Less FFI calls means less overhead from traversing the Lisp/C boundary and more safety. As more of the stack becomes Lisp, it starts looking less like icing and more like cake. Moving beyond games, we can look to the Guix project as a great example of just how tasty the cake can get. Guix took the functional packaging model from the Nix project and made a fresh implementation, replacing the Nix language with Guile. Why? For code staging, code sharing, and improved hackability. Guix also uses an init system written in Guile rather than systemd. Why? For code staging, code sharing, and improved hackability. These are real advantages that make the trade-off of not using the industry-standard thing worth it. I’ve been using Guix since the early days, and back then it was easy to make the argument that Guix was just reinventing wheels for no reason. But now, over 10 years later, the insistence on maximizing the usage of Lisp has been key to the success of the project. As a user, once you learn the Guix idioms and a bit of Guile, you unlock extraordinary power to craft your OS to your liking. It’s the closest thing you can get to a Lisp machine on modern hardware. The cake approach paid off for Guix, and it could pay off for other projects, too. If Common Lisp is more your thing, and even if it isn’t, you’ll be amazed by the Trial game engine and how much of it is implemented in Common Lisp rather than wrapping C libraries. There’s also projects like Pre-Scheme that give me hope that one day the layers below the managed GC runtime can be implemented in Lisp. Pre-Scheme was developed and successfully used for Scheme 48 and I am looking forward to a modern revival of it thanks to an NLnet grant. I'm a cake boy That’s right, I said it: I’m a cake boy. I want to see projects continue to push the boundaries of what Lisp can do. When it comes to the Lisp Game Jam, what excites me most are not the games themselves, but the small advances made to reclaim another little slice of the cake from stale, dry C. I intend to keep pushing the limits for Guile game development with my Chickadee project. It’s not a piece of cake to bake a lispy cake, and the way is often hazy, but I know we can’t be lazy and just do the cooking by the book. Rewrite it in Rust? No way! Rewrite it in Lisp!
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As I slowly but surely work towards the next release of my setcmd project for the Amiga (see the 68k branch for the gory details and my total noob-like C flailing around), I’ve made heavy use of documentation in the AmigaGuide format. Despite it’s age, it’s a great Amiga-native format and there’s a wealth of great information out there for things like the C API, as well as language guides and tutorials for tools like the Installer utility - and the AmigaGuide markup syntax itself. The only snag is, I had to have access to an Amiga (real or emulated), or install one of the various viewer programs on my laptops. Because like many, I spend a lot of time in a web browser and occasionally want to check something on my mobile phone, this is less than convenient. Fortunately, there’s a great AmigaGuideJS online viewer which renders AmigaGuide format documents using Javascript. I’ve started building up a collection of useful developer guides and other files in my own reference library so that I can access this documentation whenever I’m not at my Amiga or am coding in my “modern” dev environment. It’s really just for my own personal use, but I’ll be adding to it whenever I come across a useful piece of documentation so I hope it’s of some use to others as well! And on a related note, I now have a “unified” code-base so that SetCmd now builds and runs on 68k-based OS 3.x systems as well as OS 4.x PPC systems like my X5000. I need to: Tidy up my code and fix all the “TODO” stuff Update the Installer to run on OS 3.x systems Update the documentation Build a new package and upload to Aminet/OS4Depot Hopefully I’ll get that done in the next month or so. With the pressures of work and family life (and my other hobbies), progress has been a lot slower these last few years but I’m still really enjoying working on Amiga code and it’s great to have a fun personal project that’s there for me whenever I want to hack away at something for the sheer hell of it. I’ve learned a lot along the way and the AmigaOS is still an absolute joy to develop for. I even brought my X5000 to the most recent Kickstart Amiga User Group BBQ/meetup and had a fun day working on the code with fellow Amigans and enjoying some classic gaming & demos - there was also a MorphOS machine there, which I think will be my next target as the codebase is slowly becoming more portable. Just got to find some room in the “retro cave” now… This stuff is addictive :)
A little while back I heard about the White House launching their version of a Drudge Report style website called White House Wire. According to Axios, a White House official said the site’s purpose was to serve as “a place for supporters of the president’s agenda to get the real news all in one place”. So a link blog, if you will. As a self-professed connoisseur of websites and link blogs, this got me thinking: “I wonder what kind of links they’re considering as ‘real news’ and what they’re linking to?” So I decided to do quick analysis using Quadratic, a programmable spreadsheet where you can write code and return values to a 2d interface of rows and columns. I wrote some JavaScript to: Fetch the HTML page at whitehouse.gov/wire Parse it with cheerio Select all the external links on the page Return a list of links and their headline text In a few minutes I had a quick analysis of what kind of links were on the page: This immediately sparked my curiosity to know more about the meta information around the links, like: If you grouped all the links together, which sites get linked to the most? What kind of interesting data could you pull from the headlines they’re writing, like the most frequently used words? What if you did this analysis, but with snapshots of the website over time (rather than just the current moment)? So I got to building. Quadratic today doesn’t yet have the ability for your spreadsheet to run in the background on a schedule and append data. So I had to look elsewhere for a little extra functionality. My mind went to val.town which lets you write little scripts that can 1) run on a schedule (cron), 2) store information (blobs), and 3) retrieve stored information via their API. After a quick read of their docs, I figured out how to write a little script that’ll run once a day, scrape the site, and save the resulting HTML page in their key/value storage. From there, I was back to Quadratic writing code to talk to val.town’s API and retrieve my HTML, parse it, and turn it into good, structured data. There were some things I had to do, like: Fine-tune how I select all the editorial links on the page from the source HTML (I didn’t want, for example, to include external links to the White House’s social pages which appear on every page). This required a little finessing, but I eventually got a collection of links that corresponded to what I was seeing on the page. Parse the links and pull out the top-level domains so I could group links by domain occurrence. Create charts and graphs to visualize the structured data I had created. Selfish plug: Quadratic made this all super easy, as I could program in JavaScript and use third-party tools like tldts to do the analysis, all while visualizing my output on a 2d grid in real-time which made for a super fast feedback loop! Once I got all that done, I just had to sit back and wait for the HTML snapshots to begin accumulating! It’s been about a month and a half since I started this and I have about fifty days worth of data. The results? Here’s the top 10 domains that the White House Wire links to (by occurrence), from May 8 to June 24, 2025: youtube.com (133) foxnews.com (72) thepostmillennial.com (67) foxbusiness.com (66) breitbart.com (64) x.com (63) reuters.com (51) truthsocial.com (48) nypost.com (47) dailywire.com (36) From the links, here’s a word cloud of the most commonly recurring words in the link headlines: “trump” (343) “president” (145) “us” (134) “big” (131) “bill” (127) “beautiful” (113) “trumps” (92) “one” (72) “million” (57) “house” (56) The data and these graphs are all in my spreadsheet, so I can open it up whenever I want to see the latest data and re-run my script to pull the latest from val.town. In response to the new data that comes in, the spreadsheet automatically parses it, turn it into links, and updates the graphs. Cool! If you want to check out the spreadsheet — sorry! My API key for val.town is in it (“secrets management” is on the roadmap). But I created a duplicate where I inlined the data from the API (rather than the code which dynamically pulls it) which you can check out here at your convenience. Email · Mastodon · Bluesky
One of the first types we learn about is the boolean. It's pretty natural to use, because boolean logic underpins much of modern computing. And yet, it's one of the types we should probably be using a lot less of. In almost every single instance when you use a boolean, it should be something else. The trick is figuring out what "something else" is. Doing this is worth the effort. It tells you a lot about your system, and it will improve your design (even if you end up using a boolean). There are a few possible types that come up often, hiding as booleans. Let's take a look at each of these, as well as the case where using a boolean does make sense. This isn't exhaustive—[1]there are surely other types that can make sense, too. Datetimes A lot of boolean data is representing a temporal event having happened. For example, websites often have you confirm your email. This may be stored as a boolean column, is_confirmed, in the database. It makes a lot of sense. But, you're throwing away data: when the confirmation happened. You can instead store when the user confirmed their email in a nullable column. You can still get the same information by checking whether the column is null. But you also get richer data for other purposes. Maybe you find out down the road that there was a bug in your confirmation process. You can use these timestamps to check which users would be affected by that, based on when their confirmation was stored. This is the one I've seen discussed the most of all these. We run into it with almost every database we design, after all. You can detect it by asking if an action has to occur for the boolean to change values, and if values can only change one time. If you have both of these, then it really looks like it is a datetime being transformed into a boolean. Store the datetime! Enums Much of the remaining boolean data indicates either what type something is, or its status. Is a user an admin or not? Check the is_admin column! Did that job fail? Check the failed column! Is the user allowed to take this action? Return a boolean for that, yes or no! These usually make more sense as an enum. Consider the admin case: this is really a user role, and you should have an enum for it. If it's a boolean, you're going to eventually need more columns, and you'll keep adding on other statuses. Oh, we had users and admins, but now we also need guest users and we need super-admins. With an enum, you can add those easily. enum UserRole { User, Admin, Guest, SuperAdmin, } And then you can usually use your tooling to make sure that all the new cases are covered in your code. With a boolean, you have to add more booleans, and then you have to make sure you find all the places where the old booleans were used and make sure they handle these new cases, too. Enums help you avoid these bugs. Job status is one that's pretty clearly an enum as well. If you use booleans, you'll have is_failed, is_started, is_queued, and on and on. Or you could just have one single field, status, which is an enum with the various statuses. (Note, though, that you probably do want timestamp fields for each of these events—but you're still best having the status stored explicitly as well.) This begins to resemble a state machine once you store the status, and it means that you can make much cleaner code and analyze things along state transition lines. And it's not just for storing in a database, either. If you're checking a user's permissions, you often return a boolean for that. fn check_permissions(user: User) -> bool { false // no one is allowed to do anything i guess } In this case, true means the user can do it and false means they can't. Usually. I think. But you can really start to have doubts here, and with any boolean, because the application logic meaning of the value cannot be inferred from the type. Instead, this can be represented as an enum, even when there are just two choices. enum PermissionCheck { Allowed, NotPermitted(reason: String), } As a bonus, though, if you use an enum? You can end up with richer information, like returning a reason for a permission check failing. And you are safe for future expansions of the enum, just like with roles. You can detect when something should be an enum a proliferation of booleans which are mutually exclusive or depend on one another. You'll see multiple columns which are all changed at the same time. Or you'll see a boolean which is returned and used for a long time. It's important to use enums here to keep your program maintainable and understandable. Conditionals But when should we use a boolean? I've mainly run into one case where it makes sense: when you're (temporarily) storing the result of a conditional expression for evaluation. This is in some ways an optimization, either for the computer (reuse a variable[2]) or for the programmer (make it more comprehensible by giving a name to a big conditional) by storing an intermediate value. Here's a contrived example where using a boolean as an intermediate value. fn calculate_user_data(user: User, records: RecordStore) { // this would be some nice long conditional, // but I don't have one. So variables it is! let user_can_do_this: bool = (a && b) && (c || !d); if user_can_do_this && records.ready() { // do the thing } else if user_can_do_this && records.in_progress() { // do another thing } else { // and something else! } } But even here in this contrived example, some enums would make more sense. I'd keep the boolean, probably, simply to give a name to what we're calculating. But the rest of it should be a match on an enum! * * * Sure, not every boolean should go away. There's probably no single rule in software design that is always true. But, we should be paying a lot more attention to booleans. They're sneaky. They feel like they make sense for our data, but they make sense for our logic. The data is usually something different underneath. By storing a boolean as our data, we're coupling that data tightly to our application logic. Instead, we should remain critical and ask what data the boolean depends on, and should we maybe store that instead? It comes easier with practice. Really, all good design does. A little thinking up front saves you a lot of time in the long run. I know that using an em-dash is treated as a sign of using LLMs. LLMs are never used for my writing. I just really like em-dashes and have a dedicated key for them on one of my keyboard layers. ↩ This one is probably best left to the compiler. ↩
SumatraPDF is a fast, small, open-source PDF reader for Windows, written in C++. This article describes how I implemented StrVec class for efficiently storing multiple strings. Much ado about the strings Strings are among the most used types in most programs. Arrays of strings are also used often. I count ~80 uses of StrVec in SumatraPDF code. This article describes how I implemented an optimized array of strings in SumatraPDF C++ code . No STL for you Why not use std::vector<std::string>? In SumatraPDF I don’t use STL. I don’t use std::string, I don’t use std::vector. For me it’s a symbol of my individuality, and my belief in personal freedom. As described here, minimum size of std::string on 64-bit machines is 32 bytes for msvc / gcc and 24 bytes for short strings (15 chars for msvc / gcc, 22 chars for clang). For longer strings we have more overhead: 32⁄24 bytes for the header memory allocator overhead allocator metadata padding due to rounding allocations to at least 16 bytes There’s also std::vector overhead: for fast appends (push()) std::vectorimplementations over-allocated space Longer strings are allocated at random addresses so they can be spread out in memory. That is bad for cache locality and that often cause more slowness than executing lots of instructions. Design and implementation of StrVec StrVec (vector of strings) solves all of the above: per-string overhead of only 8 bytes strings are laid out next to each other in memory StrVec High level design of StrVec: backing memory is allocated in singly-linked pages similar to std::vector, we start with small page and increase the size of the page. This strikes a balance between speed of accessing a string at random index and wasted space unlike std::vector we don’t reallocate memory (most of the time). That saves memory copy when re-allocating backing space Here’s all there is to StrVec: struct StrVec { StrVecPage* first = nullptr; int nextPageSize = 256; int size = 0; } size is a cached number of strings. It could be calculated by summing the size in all StrVecPages. nextPageSize is the size of the next StrVecPage. Most array implementation increase the size of next allocation by 1.4x - 2x. I went with the following progression: 256 bytes, 1k, 4k, 16k, 32k and I cap it at 64k. I don’t have data behind those numbers, they feel right. Bigger page wastes more space. Smaller page makes random access slower because to find N-th string we need to traverse linked list of StrVecPage. nextPageSize is exposed to allow the caller to optimize use. E.g. if it expects lots of strings, it could set nextPageSize to a large number. StrVecPage Most of the implementation is in StrVecPage. The big idea here is: we allocate a block of memory strings are allocated from the end of memory block at the beginning of the memory block we build and index of strings. For each string we have: u32 size u32 offset of the string within memory block, counting from the beginning of the block The layout of memory block is: StrVecPage struct { size u32; offset u32 } [] … not yet used space strings This is StrVecPage: struct StrVecPage { struct StrVecPage* next; int pageSize; int nStrings; char* currEnd; } next is for linked list of pages. Since pages can have various sizes we need to record pageSize. nStrings is number of strings in the page and currEnd points to the end of free space within page. Implementing operations Appending a string Appending a string at the end is most common operation. To append a string: we calculate how much memory inside a page it’ll need: str::Len(string) + 1 + sizeof(u32) + sizeof(u32). +1 is for 0-termination for compatibility with C APIs that take char*, and 2xu32 for size and offset. If we have enough space in last page, we add size and offset at the end of index and append a string from the end i.e. `currEnd - (str::Len(string) + 1). If there is not enough space in last page, we allocate new page We can calculate how much space we have left with: int indexEntrySize = sizeof(u32) + sizeof(u32); // size + offset char* indexEnd = (char*)pageStart + sizeof(StrVecPage) + nStrings*indexEntrySize int nBytesFree = (int)(currEnd - indexEnd) Removing a string Removing a string is easy because it doesn’t require moving memory inside StrVecPage. We do nStrings-- and move index values of strings after the removed string. I don’t bother freeing the string memory within a page. It’s possible but complicated enough I decided to skip it. You can compact StrVec to remove all overhead. If you do not care about preserving order of strings after removal, I haveRemoveAtFast() which uses a trick: instead of copying memory of all index values after removed string, I copy a single index from the end into a slot of the string being removed. Replacing a string or inserting in the middle Replacing a string or inserting a string in the middle is more complicated because there might not be enough space in the page for the string. When there is enough space, it’s as simple as append. When there is not enough space, I re-use the compacting capability: I compact all existing pages into a single page with extra space for the string and some extra space as an optimization for multiple inserts. Iteration A random access requires traversing a linked list. I think it’s still fast because typically there aren’t many pages and we only need to look at a single nStrings value. After compaction to a single page, random access is as fast as it could ever be. C++ iterator is optimized for sequential access: struct iterator { const StrVec* v; int idx; // perf: cache page, idxInPage from prev iteration int idxInPage; StrVecPage* page; } We cache the current state of iteration as page and idxInPage. To advance to next string we advance idxInPage. If it exceeds nStrings, we advance to page->next. Optimized search Finding a string is as optimized as it could be without a hash table. Typically to compare char* strings you need to call str::Eq(s, s2) for every string you compare it to. That is a function call and it has to touch s2 memory. That is bad for performance because it blows the cache. In StrVec I calculate length of the string to find once and then traverse the size / offset index. Only when size is different I have to compare the strings. Most of the time we just look at offset / size in L1 cache, which is very fast. Compacting If you know that you’ll not be adding more strings to StrVec you can compact all pages into a single page with no overhead of empty space. It also speeds up random access because we don’t have multiple pages to traverse to find the item and a given index. Representing a nullptr char* Even though I have a string class, I mostly use char* in SumatraPDF code. In that world empty string and nullptr are 2 different things. To allow storing nullptr strings in StrVec (and not turning them into empty strings on the way out) I use a trick: a special u32 value kNullOffset represents nullptr. StrVec is a string pool allocator In C++ you have to track the lifetime of each object: you allocate with malloc() or new when you no longer need to object, you call free() or delete However, the lifetime of allocations is often tied together. For example in SumatraPDF an opened document is represented by a class. Many allocations done to construct that object last exactly as long as the object. The idea of a pool allocator is that instead of tracking the lifetime of each allocation, you have a single allocator. You allocate objects with the same lifetime from that allocator and you free them with a single call. StrVec is a string pool allocator: all strings stored in StrVec have the same lifetime. Testing In general I don’t advocate writing a lot of tests. However, low-level, tricky functionality like StrVec deserves decent test coverage to ensure basic functionality works and to exercise code for corner cases. I have 360 lines of tests for ~700 lines of of implementation. Potential tweaks and optimization When designing and implementing data structures, tradeoffs are aplenty. Interleaving index and strings I’m not sure if it would be faster but instead of storing size and offset at the beginning of the page and strings at the end, we could store size / string sequentially from the beginning. It would remove the need for u32 of offset but would make random access slower. Varint encoding of size and offset Most strings are short, under 127 chars. Most offsets are under 16k. If we stored size and offset as variable length integers, we would probably bring down average per-string overhead from 8 bytes to ~4 bytes. Implicit size When strings are stored sequentially size is implicit as difference between offset of the string and offset of next string. Not storing size would make insert and set operations more complicated and costly: we would have to compact and arrange strings in order every time. Storing index separately We could store index of size / offset in a separate vector and use pages to only allocate string data. This would simplify insert and set operations. With current design if we run out of space inside a page, we have to re-arrange memory. When offset is stored outside of the page, it can refer to any page so insert and set could be as simple as append. The evolution of StrVec The design described here is a second implementation of StrVec. The one before was simply a combination of str::Str (my std::string) for allocating all strings and Vec<u32> (my std::vector) for storing offset index. It had some flaws: appending a string could re-allocate memory within str::Str. The caller couldn’t store returned char* pointer because it could be invalidated. As a result the API was akward and potentially confusing: I was returning offset of the string so the string was str::Str.Data() + offset. The new StrVec doesn’t re-allocate on Append, only (potentially) on InsertAt and SetAt. The most common case is append-only which allows the caller to store the returned char* pointers. Before implementing StrVec I used Vec<char*>. Vec is my version of std::vector and Vec<char*> would just store pointer to individually allocated strings. Cost vs. benefit I’m a pragmatist: I want to achieve the most with the least amount of code, the least amount of time and effort. While it might seem that I’m re-implementing things willy-nilly, I’m actually very mindful of the cost of writing code. Writing software is a balance between effort and resulting quality. One of the biggest reasons SumatraPDF so popular is that it’s fast and small. That’s an important aspect of software quality. When you double click on a PDF file in an explorer, SumatraPDF starts instantly. You can’t say that about many similar programs and about other software in general. Keeping SumatraPDF small and fast is an ongoing focus and it does take effort. StrVec.cpp is only 705 lines of code. It took me several days to complete. Maybe 2 days to write the code and then some time here and there to fix the bugs. That being said, I didn’t start with this StrVec. For many years I used obvious Vec<char*>. Then I implemented somewhat optimized StrVec. And a few years after that I implemented this ultra-optimized version. References SumatraPDF is a small, fast, multi-format (PDF/eBook/Comic Book and more), open-source reader for Windows. The implementation described here: StrVec.cpp, StrVec.h, StrVec_ut.cpp By the time you read this, the implementation could have been improved.
Consent morality is the idea that there are no higher values or virtues than allowing consenting adults to do whatever they please. As long as they're not hurting anyone, it's all good, and whoever might have a problem with that is by definition a bigot. This was the overriding morality I picked up as a child of the 90s. From TV, movies, music, and popular culture. Fly your freak! Whatever feels right is right! It doesn't seem like much has changed since then. What a moral dead end. I first heard the term consent morality as part of Louise Perry's critique of the sexual revolution. That in the context of hook-up culture, situationships, and falling birthrates, we have to wrestle with the fact that the sexual revolution — and it's insistence that, say, a sky-high body count mustn't be taboo — has led society to screwy dating market in the internet age that few people are actually happy with. But the application of consent morality that I actually find even more troubling is towards parenthood. As is widely acknowledged now, we're in a bit of a birthrate crisis all over the world. And I think consent morality can help explain part of it. I was reminded of this when I posted a cute video of a young girl so over-the-moon excited for her dad getting off work to argue that you'd be crazy to trade that for some nebulous concept of "personal freedom". Predictably, consent morality immediately appeared in the comments: Some people just don't want children and that's TOTALLY OKAY and you're actually bad for suggesting they should! No. It's the role of a well-functioning culture to guide people towards The Good Life. Not force, but guide. Nobody wants to be convinced by the morality police at the pointy end of a bayonet, but giving up on the whole idea of objective higher values and virtues is a nihilistic and cowardly alternative. Humans are deeply mimetic creatures. It's imperative that we celebrate what's good, true, and beautiful, such that these ideals become collective markers for morality. Such that they guide behavior. I don't think we've done a good job at doing that with parenthood in the last thirty-plus years. In fact, I'd argue we've done just about everything to undermine the cultural appeal of the simple yet divine satisfaction of child rearing (and by extension maligned the square family unit with mom, dad, and a few kids). Partly out of a coordinated campaign against the family unit as some sort of trad (possibly fascist!) identity marker in a long-waged culture war, but perhaps just as much out of the banal denigration of how boring and limiting it must be to carry such simple burdens as being a father or a mother in modern society. It's no wonder that if you incessantly focus on how expensive it is, how little sleep you get, how terrifying the responsibility is, and how much stress is involved with parenthood that it doesn't seem all that appealing! This is where Jordan Peterson does his best work. In advocating for the deeper meaning of embracing burden and responsibility. In diagnosing that much of our modern malaise does not come from carrying too much, but from carrying too little. That a myopic focus on personal freedom — the nights out, the "me time", the money saved — is a spiritual mirage: You think you want the paradise of nothing ever being asked of you, but it turns out to be the hell of nobody ever needing you. Whatever the cause, I think part of the cure is for our culture to reembrace the virtue and the value of parenthood without reservation. To stop centering the margins and their pathologies. To start centering the overwhelming middle where most people make for good parents, and will come to see that role as the most meaningful part they've played in their time on this planet. But this requires giving up on consent morality as the only way to find our path to The Good Life. It involves taking a moral stance that some ways of living are better than other ways of living for the broad many. That parenthood is good, that we need more children both for the literal survival of civilization, but also for the collective motivation to guard against the bad, the false, and the ugly. There's more to life than what you feel like doing in the moment. The worst thing in the world is not to have others ask more of you. Giving up on the total freedom of the unmoored life is a small price to pay for finding the deeper meaning in a tethered relationship with continuing a bloodline that's been drawn for hundreds of thousands of years before it came to you. You're never going to be "ready" before you take the leap. If you keep waiting, you'll wait until the window has closed, and all you see is regret. Summon a bit of bravery, don't overthink it, and do your part for the future of the world. It's 2.1 or bust, baby!
