
Julia: Come for the Syntax, Stay for the Speed - SriniK
https://www.nature.com/articles/d41586-019-02310-3
======
jagtesh
I've been following Julia for many years now and it hasn't quite picked up
outside the Data Science/Research communities. I'm at a loss to understand why
it hasn't gone mainstream. Technically, isn't this a superior language to
everything out there if you are getting performance + readability?

To start the discussion, maybe one factor could be the lack of a package
manager like npm/crate. What else?

~~~
cbkeller
The initial precompilation times may give some new users the wrong idea, but
those have been for me a total non-issue once I'm using the language
regularly.

------
plg
Something I always try with new (to me) languages: write a short script to

(1) load a .txt file containing space-delimited columns of data;

(2) fit a linear model in which one column is predicted by a linear
combination of the others;

(3) plot the predicted values again the actual values using dots and overlay a
y=x line

Tried this with Julia a short while ago and basically gave up, couldn’t figure
out how to get something to plot. Has the Julia-verse changed? Is it easier
now?

I can do this in MATLAB in basically 3 or 4 lines of code. Python, not much
more than that.

~~~
ahurmazda
Not familiar with matlab but its not as terse as R

``` using GLM, CSV, Plots

data = CSV.read("data.csv", header=["x","y"], types=[Float64, Float64])
#returns dataframe

ols = lm(@formula(y ~ x), data)

ypred = predict(ols)

yall = Base.hcat(data.y, ypred)

plot(data.x, yall, linewidth=2, title="Linear regression", label=["y",
"ypred"], xlabel="x", ylabel="y")

```

~~~
cbkeller
The comment I was going to reply to disappeared, but for something closer in
form to the Matlab example that used to be here:

    
    
      using Plots, DelimitedFiles
      d = readdlm("data.tsv",'\t')
      A = [ones(10,1) d[:,1:2]]; B = copy(d[:,3]); X = A\B
      plot(B, seriestype=:scatter, color=:blue); plot!(A*X, seriestype=:scatter, color=:red)
    

I find Julia syntax feels closer to Matlab than to Python or R, just different
enough to be frustrating for the first month or so (followed by a period of
"oh, _that 's_ why Julia does it this way instead!")

~~~
DNF2
No need to `copy` from `d[:,3]`. Slicing already creates copies (so you're
copying twice), but even if it made a view you could still just write `B =
d[:, 3]`.

~~~
cbkeller
Ah, didn't realize slicing always made copies. A view/alias/whatever would
have been fine for the example, but having multiple variable names referring
to the same memory has caused me enough problems to try to avoid it by
default.

