Cello VS rust

Yes, that's C. C macros can take you quite far. Unfortunately because it's just a bunch of macros, it's quite brittle. Like high level abstractions created with macros in assembly language. You have to do all the checking and reasoning about it since the compiler cannot.

[1] https://libcello.org/

It took me a long time to understand, coming from higher level programming, that a lot of exactly that "higher level" is just systematic fat pointer conventions. And because pointers-with-metadata is not a first-class language construct, we invent all these languages that codify a particular fat pointer convention. Cello is an example of what kinds of abstractions can be built on top of a tiny little bit of (non-native) fat pointer convention.

There is a lightweight object oriented extension to C called Objective-C [1] that unfortunately never gained much traction outside the NeXT/Apple ecosystem. There is also Cello [2].

[1] https://en.wikipedia.org/wiki/Objective-C

[2] https://github.com/orangeduck/Cello

Regular expressions library to validate information before dumping to rocksdb.

https://www.gnu.org/software/libc/manual/html_node/Regular-E...

Non-critical implimentation fun, use cello [1] for 'gawk' functionality in C with C++ objects/classes.

[1] https://libcello.org/

You can achieve a fairly decent runtime safety for some types of project. Check out libcello and my own monster (libstent, lame presentation).

towards lisp related data structures / algorithms (aka recursive tree data structures & algorithms).

So, no distinction between metadata vs. structual storage unless noted.

Anything beyond that tends towards masters & upper level undergraduate level material. aka review the implimentation of a programming language for algorithm & data structure usage per language features.

aka Autonoma / regular expressions backround: Lisp in Small Pieces by Christian Queinnec; ; https://github.com/aalhour/awesome-compilers; On Lisp by Paul Graham; Let over Lambda by Doug Hoyte; C 'macro's pushed to maximum effect : https://libcello.org/

    Left out Comparison of languages; Transform from lang a to lang b; and language implimentation as discussions tend to assume masters / upper level undergraduate knowledge

with skills like this, mind to push cello forward? https://github.com/orangeduck/Cello really like it but not skillful enough to do it myself.

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.