Swift compared to Python was getting way too complex. Why would anyone learn Swift for data science when Python will do?
Putting aside the Python 2/3 transition, I think that Python does a good job of introducing new features carefully. For example, the "X if P else Y" syntax. While I prefer the C approach, the Python approach works fine and fits in the language well.
I had a mild dislike of Swift from the beginning, but it was a lot more palatable than working in Objective C. What bothered me was all the gimmicky syntax. Sometimes "let" unwraps an optional, sometimes it doesn't. ! and ? seem badly overused. ARC doesn't compose well with other language features. There is a ton of syntax whose only purpose appears to be to stuff logic into and around assignment syntax. Then it got worse, with major language changes across versions 3-5, each one introducing lots of new concepts and syntax.
And of course, Swift is a proprietary Apple language, (in the same way that C# is tied to Microsoft). When I stopped doing iOS programming, I very happily but Swift behind me.
I saw the TensorFlow additions to the language and thought the whole thing bizarre. I put my reaction down to my lack of involvement with data science. Maybe I'd appreciate those changes more if I knew more about data science. But I also remember thinking that it was quite odd to make such extensive additions to the language to support this one application area, which was very, very far from the language's sweet spot.