3 ms·
I know R and have used Octave. I started learning Julia this morning after a physicist recommended it to me after he switched from python. I used Jupyter/Julia
by papaf 10y ago
I know R and have used Octave. I started learning Julia this morning after a physicist recommended it to me after he switched from python. I used Jupyter/Julia to simulate a neuron as a practice exercise. This is my experience as a beginner:
1. The static typing makes a big and positive difference. Its nice having a statically typed repl.
2. The documentation is good.
3. Using unicode symbols and \mu style tab completion is nice, especially in Jupyter where you can use the same symbols in latex style equations.
4. The base install is a bit bare. It would be nice if batteries were included - distributions and dataframes in particular.
5. R uses 1 based indexing and it was no shock to see this in Julia.
6. I had no problems with the mix of lisp and C++ in the source code. The lisp implementation is beautiful and worth a read.
Generally, I was shocked to see a blog post like this given that my first day with Julia was so positive.
- SolarNet 10y ago> The base install is a bit bare. I think the problem here is the library approach. They should break stuff out of Julia's core library and move them into default included libraries (like python does).
- argonaut 10y agoWhat is the difference?
- ta2507823 10y ago* initial memory footprint is lower * faster start up time * cleaner global scope
- pkm 10y agoYes they should, and that is exactly what is happening in Base, and has been happening for a while. A project like Julia doesn't have too much dev time input, so you cannot expect this to happen over night.