rand
swift
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rand | swift | |
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29 | 214 | |
1,568 | 65,842 | |
2.0% | 0.7% | |
8.2 | 10.0 | |
15 days ago | 6 days ago | |
Rust | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rand
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We have getrandom at home
Making compatibility promises for distributions means they cannot take advantage of potential advancements in the field.
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Blog Post: On Random Numbers
Defining an error type that is meaningful, portable, and compatible with no-std isn't straightforward. If the std lib's getrandom requires std, then just like that, rand and many other crates won't use it anyway. Using io::Result seems to me to face this challenge.
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Hey Rustaceans! Got a question? Ask here (52/2022)!
Some wasm targets can’t generate random numbers at all but in the case of the book because you are using wasm in a browser you can use JS to generate random numbers. I believe there’s a way to get the rand crate to use JS as the backend for generating rand but its a bit more convoluted than the easy one-liner that the book suggests.
- Data-driven performance optimization with Rust and Miri
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What crates are considered as de-facto standard?
rand
- Why Rust?
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[Media] Nebulabrot rendered with Rust — Explanations in the comments
This uses rand and xcomplex to handle the mathematics, png to write image files, and dialoguer and indicatif for some pretty prompts and progress bars.
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Do you ever use unsafe { .. } when not implementing custom data structures or interacting with external C code?
You can often achieve this without any unsafe by putting an assert!() on the length before the hot loop. For example, I got rid of some unsafe in rand that way.
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Original source of `(seed * 9301 and 49297) % 233280` random algorithm?
This is a widely used method to map random integers to floating point numbers, but it has the disadvantage of wasting 1 bit of float mantissa precision.
On modern CPUs, its computational advantage over full-precision mapping methods, such as multiplication by a float, is not always clear [1].
[1] https://github.com/rust-random/rand/issues/416
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Any plans for built-in support of Vec2/Vec3/Vec4 in Rust?
In fact, there are a lot of crates in Rust where in other programming languages, it would be included in the standard library. Examples are regex, random number generators, additional iterator methods, macros for other collections, num traits, loggers, HTTP libraries, error handling, async runtimes, serialization and deserialization, date and time, and many more.
swift
- Swift: Differentiable Programming Manifesto
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Embedded Swift on the Raspberry Pi Pico
Because of C/C++ interop, and integration with CMake, you can just add Swift to a Zephyr project and it pretty much Just Works. [The docs](https://github.com/apple/swift/blob/main/docs/EmbeddedSwift/...) should mostly apply to the Zephyr SDK as well.
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A Deep Dive Into Observation: A New Way to Boost SwiftUI Performance
Fortunately, the Observation framework is part of the Swift 5.9 standard library. We can learn more information by examining its source code.
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Swift was always going to be part of the OS
They do! See https://github.com/apple/swift/blob/main/docs/LibraryEvoluti...
You can also see an example of what a different high level language integration with Swift ABI looks like here: https://github.com/dotnet/designs/blob/main/proposed/swift-i...
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Differentiable Swift
So is differentiable Swift a package for Swift or is it part of the Swift standard library? The video says go to swift.org but I can't find any info about differentiable Swift on that site.
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Beyond Backpropagation - Higher Order, Forward and Reverse-mode Automatic Differentiation for Tensorken
Swift's Differentiable Programming Manifesto. Swift has a powerful differentiable programming component, integrated with the compiler.
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Kotlin Multiplatform for Android and iOS Apps
You can do the same thing the other way around - https://github.com/apple/swift/blob/main/docs/Android.md.
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This isn’t the way to speed up Rust compile times
Codable (along with other derived conformances like Equatable, Hashable, and RawRepresentable) is indeed built in to the compiler[0], but unlike Serde, it operates during type-checking on a fully-constructed AST (with access to type information), manipulating the AST to insert code. Because it operates at a later stage of compilation and at a much higher level (with access to type information), the work necessary is significantly less.
With ongoing work for Swift macros, it may eventually be possible to rip this code out of the compiler and rewrite it as a macro, though it would need to be a semantic macro[1] rather a syntactic one, which isn't currently possible in Swift[2].
[0] https://github.com/apple/swift/blob/main/lib/Sema/DerivedCon...
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How does Swift implement primitive types in its standard library?
`Int` is a regular struct with a single stored property of type `Builtin.Word` . But the latter is a magical compiler built-in. Source for integer types is generated from this template - https://github.com/apple/swift/blob/9da65ca0a15fdf341649c994b0a77ec3b71f2687/stdlib/public/core/IntegerTypes.swift.gyb
- Catalog of All SwiftUI Changes?
What are some alternatives?
fastrand - A simple and fast random number generator
solidity - Solidity, the Smart Contract Programming Language
fast-float-rust - Super-fast float parser in Rust (now part of Rust core)
cpp-lazy - C++11/14/17/20 library for lazy evaluation
winapi-rs - Rust bindings to Windows API
Elixir - Elixir is a dynamic, functional language for building scalable and maintainable applications
yew - Rust / Wasm framework for creating reliable and efficient web applications
tree-sitter - An incremental parsing system for programming tools
cargo-fuzz - Command line helpers for fuzzing
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.
rust - Rust for the xtensa architecture. Built in targets for the ESP32 and ESP8266
lobster - The Lobster Programming Language