cryptography VS rust

Congratulations to the authors, this was a feature that was dearly missing from pyca/cryptography. It took a long time to get right.

For the history: https://github.com/pyca/cryptography/issues/2381

Some context:

- The cryptography dependency used by the current release of mitmproxy has a CVE related to an OpenSSL vulnerability (https://github.com/pyca/cryptography/security/advisories/GHS...)

- The main branch of mitmproxy has already upgraded to the latest version of the cryptography package

- The author of the package does not believe the CVE impacts users of mitmproxy so a release including this commit has not been made

Also you'll use https://github.com/pyca/cryptography

first, I did see a correlation between an endpoint being heavily hit in a given time window, and an increase of memory usage that didn't went down afterwards. The endpoint didn't do much so I went through every instruction - is a global variable appended indefinitely ? Is a cache decorator growing without a limit set ? Do I use a 3rd party that has a known issue ? Turns out, it was using cryptography, so I looked up known issues. Saw an issue about a leak when using load_pem_x509_certificate https://github.com/pyca/cryptography/issues/4833 - which I used ! I could fortunately just upgrade the library

Après le kerfuffle du paquet de cryptographie cette semaine (https://github.com/pyca/cryptography/issues/5771), J’ai passé en revue l’état des outils de gestion des dépendances en Python.

> A big problem with Rust, long-term, is that the kind of programs that really need it are somewhat out of today's mainstream. It's not that useful for webcrap. It's not that useful for phone apps. The AI people use Jupyter notebooks and Python to drive code on GPUs.

One thing this is missing is that Rust is useful for libraries callable by many different languages. You may or may not want to use it to build an actual Web app (I personally think it's a solid choice, but reasonable people can disagree). But for building, say, the Python cryptography library [1], which is used as a part of "webcrap" and Jupyter notebooks, Rust is clearly an excellent option. Nobody is going to build core Python infrastructure in Go or Node, and there will always be a need for plumbing libraries.

[1]: https://github.com/pyca/cryptography

Also, I see more and more examples where rust gets included in different technologies using FFI. Ie for python https://github.com/pyca/cryptography for security/performance critical pieces.

> I am curious. Could you give some more context?

Probably talking about this: https://github.com/pyca/cryptography/issues/5771

You will be hard pressed to find a cryptography library that doesn't depend on openssl. Fortunately openssl bindings can be installed on Windows. One of the more popular libraries for python is cryptography, but it does depend on libssl.

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.