ts-node VS rust

I thought this was going to be a project like ts-node [1]

[1] https://github.com/TypeStrong/ts-node

The command specified in the app option uses ts-node by default, which is an execution engine for Node.js that allows you to run TypeScript code directly. The --prefer-ts-exts flag prevents ts-node from prioritizing precompiled .js files and will always import the TypeScript source code instead, if it is available. This is useful if you are also using tsc (the TypeScript compiler) alongside the app option. The bin/cdk.ts file is the entry point for our CDK app, which defines the main function that will be executed when the app is run.

If you want to write apps that run on Node.js I would suggest using Google’s TypeScript style guide. You can start using it by simply running npx gts init. I’d suggest that you start with this and run your apps using ts-node/ts-node-dev because it does not require an extra build step.

ts-node (“TypeScript execution and REPL for Node.js”)

Here is a relevant discussion and dev comment: https://github.com/TypeStrong/ts-node/issues/155

It does support ESM, with a --loader[1], but even with its SWC option it’s still significantly slower than the esbuild loader I’m working on. Unfortunately, esbuild isn’t totally compatible with tsc, so it’s not a drop-in replacement without plugins.

1: https://github.com/TypeStrong/ts-node#native-ecmascript-modu...

The process of compiling TypeScript source files into JavaScript code before executing them with Node.js can get a little tedious after a while, especially during development. You can eliminate the intermediate steps before running the program through the ts-node CLI to execute .ts files directly. Go ahead and install the ts-node package using the command below:

I tried suggested solution by https://github.com/TypeStrong/ts-node/issues/1007 but this causes problem with NestJS decorators:

Almost fixed the compiler: https://github.com/rust-lang/rust/pull/123325

Rust: A secure, efficient, and modern programming language (omitting ten thousand words). You can simply follow the installation instructions provided on the official website.

Recently did something similar in Rust but for generating SVGs. We've adopted it for snapshot testing of cargo and rustc's output. Don't have a good PR handy for showing Github's rendering of changes in the SVG (text, side-by-side, swiping) but https://github.com/rust-lang/rust/pull/121877/files has newly added SVGs.

To see what is supported, see the screenshot in the docs: https://docs.rs/anstyle-svg/latest/anstyle_svg/

We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.

The above Assert<{N % 2 == 1}> requires #![feature(generic_const_exprs)] and the nightly toolchain. See https://github.com/rust-lang/rust/issues/76560 for more info.

Another week, another dive into Rust. This time, we're delving into structs. Structs bear resemblance to interfaces in TypeScript, enabling the grouping of intricate data sets within an object, much like TypeScript/JavaScript. Rust also accommodates functions within these structs, offering a semblance of classes, albeit with distinctions. Let's delve into this topic.

There’s also other reasons. For example, take binary search:

* prefetch + cmov. These should be part of the STL but languages and compilers struggle to emit the cmov properly (Rust’s been broken for 6 years: https://github.com/rust-lang/rust/issues/53823). Prefetch is an interesting one because while you do optimize the binary search in a micro benchmark, you’re potentially putting extra pressure on the cache with “garbage” data which means it’s a greedy optimization that might hurt surrounding code. Probably should have separate implementations as binary search isn’t necessarily always in the hot path.

* Eytzinger layout has additional limitations that are often not discussed when pointing out “hey this is faster”. Adding elements is non-trivial since you first have to add + sort (as you would for binary search) and then rebuild a new parallel eytzinger layout from scratch (i.e. you’d have it be an index of pointers rather than the values themselves which adds memory overhead + indirection for the comparisons). You can’t find the “insertion” position for non-existent elements which means it can’t be used for std::lower_bound (i.e. if the element doesn’t exist, you just get None back instead of Err(position where it can be slotted in to maintain order).

Basically, optimizations can sometimes rely on changing the problem domain so that you can trade off features of the algorithm against the runtime. These kinds of algorithms can be a bad fit for a standard library which aims to be a toolbox of “good enough” algorithms and data structures for problems that appear very very frequently. Or they could be part of the standard library toolkit just under a different name but you also have to balance that against maintenance concerns.