As has been pointed out, Julia is not limited to a single thread. It's actually got a pretty good support for parallelism both at the thread and process level.
And no, Julia is not too similar to Python. Julia has multiple dispatch, Python does not.
And no, Julia is not too similar to Python. Julia has multiple dispatch, Python does not.
Yeh this is superficial, but so are 200 dollar sneakers and they do just fine.
Honestly there is a real pleasure writing code that looks like it could be on the blackboard. The numpy / numba world in Python just feels... not great.
Even after 25 years in the business, it's still a pain.
Edit for details: `Σλ∀φ` is a chore to read for me. These letters only make sense if I've absorbed the author's notation beforehand, like in a math proof. I parse the snake case version instantly, because my brain is trained for that. And I understand it much more quickly, because it says exactly what the function does in the way I would represent it in memory.
> I'd hate to have to learn which Greek letters correspond to which operations every time I dive into a new codebase.
You have to do that anyway, because you’ll have to connect the code you’re working on with the scientific paper describing it. When the code uses variable names too far removed from the mathematical symbols, you have to do make two steps: figure out how the words connect to symbols and then figure out the symbols. This will be especially difficult for the mathematician/scientist without a strong coding background: they’ll have much less friction reading code that matches the symbolic notation and Greek letters that they’re used to.
> The advantage of English words is that everyone knows them.
Not when it comes to “math” words.
> `Σλ∀φ` is a chore to read for me.
Right, but that’s because you have a different background. For me, `Σλ∀φ` is much easier to read and understand. More importantly, a symbolic notation is much denser, which allows to parse long expression that would be very hard to understand if they were written out in words.
Again, this is for the very specific context of highly mathematical/scientific software that Julia excels at and is primarily used for. In a more general context (when the software isn’t a direct representation of a scientific paper), I’m 100% on board with good, descriptive variable names
Of course it will limit who will be able to interact with your project, which can be a good thing or a bad thing. For the math-unicode in numerical software, you may not even want someone without at least a minimal math background (enough to understand Greek letters and math symbols) working on the code. Likewise, a project that’s inherently Chinese, where it doesn’t make sense for the users/developers not to know Chinese, should feel absolutely free to use Chinese symbols in their source code.
On the other hand, if you do it gratuitously, you just unnecessarily limit collaboration. I’m ok with that, too, personally: it’s your own foot you’re shooting.
There's really nothing wrong with beginners starting out in their own language. Why shouldn't a 14 year old Chinese kid write their first programs using Chinese characters as identifiers? I'd much rather have a language support full Unicode they way Julia does than to force everyone into ASCII.
It's a hell of a lot better than reading `Sigma`, `lambda`, etc. and having to do both the verbose English -> character translation in your head while trying to understand the mathematical form. At the end of the day, you do need to understand the math in order to understand mathematical code, and making it have as few translation steps really helps.
I remember that one of the first things I did when learning C++ was to implement a matrix library, operator overloading and all (oh, how naive when it comes to getting it right!).
So the ability to express computation in standard mathematical notation rather than having to invent pseudo symbols to do it makes it much easier to read for people who already have that training. And for people who don’t… it does require pre-reading to understand how these symbols are used but you have the benefit for hundreds of years of math literature and community to look it up!
But seriously, it's 2021. We are no longer slave to ASCII, or even English.
Most of the newer math oriented langs have heavy use of unicode (julia, agda, lean, etc).
And so it is with greek letters. Many of them carry intrinsic meaning, or a loose collection of related meanings - they effectively are labels. It's not that people want to write dense and impenetrable code, it's that they would rather write μ than coefficient_of_friction because that is its proper name and how it appears in formulas and textbooks.
To me, it's a matter of familiarity. clearly human brains can process large amount of symbols. Just look at some east asian languages. Historically, there has been an ASCII bias in computer languages, but that is history.
Mathematics is a /language/, and one of the most universal in humanity because it models certain human reasoning.