Whoa...The Python interoperability is incredible.<p>You can use numpy from swift..As well as load pickle files !<p><a href="https://github.com/tensorflow/swift/blob/master/docs/DesignOverview.md#python-interoperability" rel="nofollow">https://github.com/tensorflow/swift/blob/master/docs/DesignO...</a>
At first I was fairly disappointed that Swift was chosen over Julia, and I still wish there was strong Julia support because Julia is a great language, but I've slowly been changing my mind and think Swift could be a really good choice long term.<p>I also just really like Chris' work and trust him to make the right calls until proven otherwise.
As a longtime fan of C#, this article and use case just pushed me from “why would anyone think they needed to invent Swift” to “wow that’s an extremely cool set of language design constraints!”
> Automatic differentiation in Swift is a compiler IR transformation implemented with static analysis.<p>Super cool to see this implemented at the language level like this.
Given the fact that the vast majority of people is still on Windows, using Swift (with zero official support for Windows) will artificially limit the use of the project outside the circle of the original developers.<p>That being said, you can use Swift through WSL, but not directly on Windows.
Does Swift have a large community beyond iOS apps? Last I used it was years ago, right after it was introduced by Apple. I'm curious if it has found growth in other areas.
Still a bit more verbose than Python. What would you gain by doing the same in Swift actually? If you have to type more code to do some experiments, and still have to import Python libraries for extra functions as they do in that example, what's the selling point? (beside it being cool)