dataframe VS swift-evolution

For working with datasets (loading and processing), I use Kotlin DataFrame. It is a library designed for working with structured in-memory data, such as tabular or JSON. It offers convenient storage, manipulation, and data analysis with a convenient, typesafe, readable API. With features for data initialization and operations like filtering, sorting, and integration, Kotlin DataFrame is a powerful tool for data analytics. I also use the Kandy - Kotlin plotting library, designed specifically for full compatibility with Kotlin DataFrame. It brings many types of plots (including statistical) with rich customization options via a powerful Kotlin DSL. The best way to run all of this is Kotlin Notebook. It works out of the box, has native rendering of Kandy plots and DataFrame tables, and has IntelliJ IDEA support. It can also be run in Jupyter notebooks with a Kotlin kernel and on Datalore.

kotlin-dataframe only supports JVM, it is not (yet) a multiplatform library and cannot be used in Kotlin/JS projects. https://github.com/Kotlin/dataframe/issues/24

Kotlin DataFrame is a library for in-memory data manipulation

[A Vision for Embedded Swift](https://github.com/apple/swift-evolution/blob/main/visions/e...) has the details on this new build mode and is quite interesting.

> Effectively, there will be two bottom layers of Swift, and the lower one, “non-allocating” Embedded Swift, will necessarily be a more restricted compilation mode (e.g. classes will be disallowed as they fundamentally require heap allocations) and likely to be used only in very specialized use cases. “Allocating” Embedded Swift should allow classes and other language facilities that rely on the heap (e.g. indirect enums).

Also, this seems to maybe hint at the Swift runtime eventually being reimplemented in non-allocating Embedded Swift rather than the C++ (?) that it uses now:

> The Swift runtime APIs will be provided as an implementation that’s optimized for small codesize and will be available as a static library in the toolchain for common CPU architectures. Interestingly, it’s possible to write that implementation in “non-allocating” Baremetal Swift.

I may be out of my depth here as I've only casually used Rust, but this seems similar to Swift's proposed lifetime dependencies[1]. They're not in the type system formally so maybe they're closer to poloneius work

[1]: https://github.com/apple/swift-evolution/blob/3055becc53a3c3...

Swift recently adopted a region-based approach for safe concurrency that builds on Milano et al’s ideas: https://github.com/apple/swift-evolution/blob/main/proposals...

No, it's not. Refcounting CAN be a garbage collection algorithm, but in Swift it's deterministic and done at compile time. Not to mention recently added support for non-copyable types that enforces unique ownership: https://github.com/apple/swift-evolution/blob/main/proposals...

You can stackallocate buffers with unsafe Swift but it's not exactly fun to use. https://github.com/apple/swift-evolution/blob/main/proposals/0322-temporary-buffers.md

If the docs do not suffice, read the concurrency proposals of Swift Evolution. The authors describe the semantics in a very detailed way there.