Rust Macros vs Zig Comptime: Compile Time Optimization

Appears that a big chunk of Claude Code's source code has been exposed on npm via a .map file accidentally uploaded to the public repository. ~512K lines of code ~1,900 files The guy who forked - Got 32.6k stars, 44.3k forks. - Got scared of getting sued. - Converted the whole codebase from TypeScript to Python with Codex AI is quietly erasing copyright. https://lnkd.in/gcnt8z-t

Iterators in Rust are zero-cost abstractions - essentially you could use the high-level functional constructs like map, filter, and sum without any additional runtime overhead. I ran a simple test - iterating a slice - to compare both. Both versions - iterators and handwritten loops - compile down to identical machine code. For an x86_64 target with release optimization (-O3), the compiler uses SIMD with loop unrolling for both. Instead of processing one number at a time, it processes 4 numbers simultaneously by utilising multiple 128-bit registers in parallel. To quote the official Rust-lang book: `Now that you know this, you can use iterators and closures without fear! They make code seem like it’s higher level but don’t impose a runtime performance penalty for doing so.` Side-by-side comparison on Compiler Explorer : Iterator version : `https://lnkd.in/gVSRkcpf Handwritten loop : `https://lnkd.in/gUVfqUy2 #RustLang 

Can a C port of the Go stdlib be faster than the original? I was able to get a 2-4x speed boost with strings.Builder, but couldn't beat Go's substring search. On porting, benchmarks, and optimization: https://lnkd.in/d8SuPwCz

Confused about what your compiler errors are? In Rust, a feature has been added that gives you a graphic example to help resolve your issue... 🦀 If you have been tweaking Rust code for some time, you'll eventually be confronted with the language's compiler errors. Some can be easy to resolve... and some can be harder. Certain compiler errors (if not all) come with a code that starts with E. That code can be of big help when trying to understand the issue. In this post's image, the code is E0425. When you have that code, 2 options present themselves: 1️⃣ Use the command 'rustc --explain <YOUR_CODE>' 2️⃣ Go to the 'Error code index' and look for your code (https://lnkd.in/e3pPmYyY) In my opinion, option 2️⃣ is better, because the text is more clearly separated (with the presence of clear code blocks). According to the 2025 State of Rust Survey results, 𝐧𝐞𝐚𝐫𝐥𝐲 𝟐𝟐% 𝐨𝐟 𝐫𝐞𝐬𝐩𝐨𝐧𝐝𝐞𝐧𝐭𝐬 𝐝𝐢𝐝 𝐧𝐨𝐭 𝐤𝐧𝐨𝐰 𝐨𝐟 𝐭𝐡𝐢𝐬 𝐟𝐞𝐚𝐭𝐮𝐫𝐞 (https://lnkd.in/eRi2tKjP). To be honest, I didn't even know about it until today. Hopefully, I just simplified your coding experience by presenting this to you. ⚡ #Rust

Spent the last 3 hours debugging a “small change” in my Rust code. You know… the kind where you just tweak one file and expect a quick compile. Instead, Rust politely hands you a novel: → 17 errors → 9 warnings → 3 existential crises And the best part? You fix one error… hit compile again… and Rust unlocks new errors like it’s a boss level progression system. At some point, it stops feeling like coding and starts feeling like: “Rust is correct. I am wrong.” But weirdly… when it finally compiles cleanly, it feels earned. Like the compiler didn’t just accept your code… it approved your existence. Stockholm syndrome? Maybe. Reliable, memory-safe code? Definitely. PS. Error is still not fixed 😭 #RustLang #SoftwareEngineering #DeveloperLife #Debugging #ProgrammingHumor #SystemsProgramming #BuildInPublic #CodeLife

Just read another great article by Gabor Ruzsinszki about how many C# features are actually just syntax sugar and what the compiler really does behind the scenes. 🍭 👉 https://lnkd.in/dgeNFNCz It made me wonder, do we really need to master every new syntax sugar to be good developers? Are there cases in C# where the older, more explicit code is actually more readable than the new constructs? Curious to hear your thoughts! 👇

Claude Code’s source code was accidentally exposed through a source map in their npm package. Not a hack. Not a breach. A build artifact mistake, .map files pointing to unobfuscated TypeScript hosted on Anthropic’s own R2 bucket. Publicly downloadable. 1,900 files. 512,000+ lines of code. Now everyone knows how it works. Within hours, developers had already built clean-room rewrites in Python and Rust. One repo hit 121,000 stars in under 24 hours, the fastest in GitHub history. One mistake from Anthropic and open source agentic AI got an upgrade overnight. Thousands of developers now have a blueprint for how one of the best agent systems in the world actually works under the hood. What gets built from this over the next 12 months is going to be very interesting to watch.

🚀 LeetCode — Day 23 Solved: Word Break Today’s problem was a solid introduction to Dynamic Programming on strings. Approach: • Use a DP array where dp[i] indicates if the substring s[0...i-1] can be formed • For each position, check all words in the dictionary • If a valid split is found → mark it as true Key idea: Break the problem into smaller subproblems and reuse previously computed results. This problem really shows how DP helps turn an exponential recursion into a polynomial solution. Also reinforces thinking in terms of: “Can I build this string step by step from known valid parts?” Day 23. Still building consistency. 🔁🔥 #LeetCode #Day23 #DSA #DynamicProgramming #ProblemSolving #Consistency #Cpp #CodingJourney

Owen's Year of Reinvention Day 12 Today, I reacquainted myself with a project I haven't touched in a good while -- a shader compiler for my engine. Now, to explain, I did not write the individual compilers themselves, as they were included with the Vulkan toolchain. Rather, it's a wrapper around the Vulkan SDK compilers for HLSL (DXC), GLSL (ShaderC or GLSLC), and Slang (SlangC). Essentially, what it allows for is any shader of those 3 formats to be submitted as input, and it emits a compiled SPIR-V output along with reflection data. The file itself that is output is in a format that is described by the attached PDF, which I designed custom for this system. The command line tool can be found on branch #010 on my engine's Git, although my plan for tomorrow is to move it to its own repo as well as provide a single header reader util so that the compiler can be used more easily by those who are interested in adding reflection to their compiled shaders but don't feel like doing the leg work necessary to do so at runtime. So yeah, that's what I'd been digging up this week, and I now have a concrete goal for tomorrow that I should be reporting happily. Keep grinding folks 🤙 Engine Git: https://lnkd.in/ehFhNg2W)

🚀 Day 53 of #100DaysOfCode Solved 3100. Water Bottles II on LeetCode 🔗 🧠 Key Insight: This problem is a twist on the classic water bottle exchange. Unlike the original, the exchange rate increases after each trade, making it slightly more tricky. ⚙️ Approach: 1️⃣ Start with numBottles → initial full bottles 2️⃣ While we can exchange: 🔹Spend numExchange empty bottles 🔹Gain 1 full bottle 🔹Increment numExchange (cost increases each time) 3️⃣ Keep tracking total bottles drunk 🔁 This is essentially a simulation problem with a dynamic condition. ⏱️ Time Complexity: O(k) (number of exchanges) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #Greedy #Simulation #Java #CodingJourney