Julia: Come for the Syntax, Stay for the Speed

Julia: Come for the Syntax, Stay for the Speed(nature.com)

8 points by SriniK 6 years ago | 8 comments

jagtesh 6 years ago |

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 6 years ago | |

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 6 years ago |

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 6 years ago | |

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 6 years ago | | |

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 6 years ago | |

That is strange. It is literally as easy as `using Plots; plot(...)`

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)