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74 results for “ryguw”

  1. [#rediffusion] Petit partage improvisé depuis mon salon : Jean-Sébastien Bach, Courante de la 2e suite youtube.com/watch?v=q3CSa_R8Guw Merci d'avance pour vos vues / likes / abonnements / partages ! #musique #musiqueClassique #classicalMusic #music #myWork #Bach #alto #viola 😍🙏🎶🎻 @music

  2. @ryguw With Rust, you have fearless parallelism! No data races! (It can not prevent dead lock though, but this is a logic error). The crate is awesome for easy, safe and load balanced multithreading.

  3. Nim is like Python on steroids. Crystal is like Ruby on steroids. Which one is suited for competitive programming involving data structures like doubly linked lists? And which language is best for multi-core parallelism? Would love to hear opinions.

  4. Go 1.20 saw the inclusion of Profile Guided Optimization, or Pedal to the metal: seemingly effortless 2-7% performance boosts for most Go applications. There’s much to debunk, discover and to learn about, with Andrew Philips.

    Link: andrewwphillips.github.io/blog

  5. Important changes coming up in 1.22: No need to shadow loop variables anymore. Range over integers. Profile-guided optimization can make your production binaries 14% faster.

    Read more: antonz.org/go-1-22/

  6. I took my 'Flow State' track—the one for focus and calm and did the opposite. It's now a liquid drum and bass remix.

    If you fancy hearing what happens when focus music gets a bit more energetic, the teaser is here. Full track coming soon.

    youtube.com/shorts/ryGwqDBEoAY

    #LiquidDnB #DrumandBass #AarDHD #FlowState #Remix #ADHDMusic

  7. While I don't think code reviews are all bad and waste of time, I do think some are bad or partial waste of time. There are effective alternatives to those weeks-long PR reviews, worth exploring imo.

    More: qase.io/blog/code-review-alter

  8. One does not simply force the pendulum to swing back to typed languages

  9. Being able to use all cores with ease in , has taught me that not all problems can be parallelized. In fact, only few algorithms are concurrent, and CPU-bound. CPU caches, instruction sets, and single-core is still very relevant.

  10. To me this HN thread is pure gold. When I first discovered Dynamic Programming (DP) in Python with the @cache decorator quite late actually, it looked like magic to me. I could not find as much wisdom on it (top search results are all leetcode tutorials) but once again @hn_discussions fill that gap. Will dive deeper into the topic of generative recursion.

    🧵 HN thread: news.ycombinator.com/item?id=3

  11. Let me just say this, many languages exist that are better suited for code golfing than Go 🤣

  12. 2) Python Standard Library: #Python #stdlib comes with batteries included, that means even though there are several ways to do something, in specific cases using a certain stdlib function like `chain()` will be the fastest. Or not, like when cloning a 2d list it's faster to `copy()` manually in a loop than to pickle-unpickle

  13. 2) Python Standard Library: comes with batteries included, that means even though there are several ways to do something, in specific cases using a certain stdlib function like `chain()` will be the fastest. Or not, like when cloning a 2d list it's faster to `copy()` manually in a loop than to pickle-unpickle

  14. 2) Python Standard Library: #Python #stdlib comes with batteries included, that means even though there are several ways to do something, in specific cases using a certain stdlib function like `chain()` will be the fastest. Or not, like when cloning a 2d list it's faster to `copy()` manually in a loop than to pickle-unpickle

  15. 2) Python Standard Library: #Python #stdlib comes with batteries included, that means even though there are several ways to do something, in specific cases using a certain stdlib function like `chain()` will be the fastest. Or not, like when cloning a 2d list it's faster to `copy()` manually in a loop than to pickle-unpickle

  16. 2) Python Standard Library: #Python #stdlib comes with batteries included, that means even though there are several ways to do something, in specific cases using a certain stdlib function like `chain()` will be the fastest. Or not, like when cloning a 2d list it's faster to `copy()` manually in a loop than to pickle-unpickle

  17. Suddenly Bun has become much, much more interesting as a longterm Node.js competitor. Dropping Zig for Rust is a bold but ultimately wise move, in their specific case.

  18. screens transformed the way we perceive digital content forever. Crisp texts, vivid colors, deep blacks.

    I do miss the years when I could look at a screen, and deeply appreciate how artists designed the way their pixels bridged the gap between an imagined world and the real world. Elegant pixel fonts, smooth dithering, skeuomorphic art. Ah the

  19. Hints: it happens in a hot loop, and a Ring Queue can solve this issue...

  20. I made a tiny decision to become master in Python this year, instead of learning Go or Nim or Elixir. Not because of AI. Though being able to code in Python fluently does indeed open up new career opportunities. But primarily because of its maturity, versatility, and Rust/C interoperability. Still interested in any language that pushes the boundaries of developer productivity in any dimension. You’ll read more about Python here in the future, from a perspective!

  21. Managed to reduce the exec time for 2023 day 23 part 2 from 513 seconds (~8.5 mins) to a stellar 0.310 seconds. Looking back at my commits these were the biggest leaps:

    - By far the biggest leap: Shrink unique nodes to <= 64, then instead of a map simply use a `uint64` bitmask for boolean lookups (visited or not). Saves a lot of map accesses & assignments
    - Prefer `int` when doing most calculations and comparisons, seems super optimized in the Go runtime

  22. That said, running the exact squeezed single-core-optimized algorithm, but for multiple inputs on multiple cores simultaneously with 5 lines of code, feels absolutely awesome! 😎