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| APL.jl | array | |
|---|---|---|
| 3 | 6 | |
| 62 | 45 | |
| - | - | |
| 0.0 | 0.8 | |
| about 2 years ago | about 1 year ago | |
| Julia | Kotlin | |
| GNU General Public License v3.0 or later | MIT License |
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APL.jl
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The counter-intuitive rise of Python in scientific computing (2020)
2. ipython repl
1. pairs with jaimebuelta's artistic vs engineering dichotomy, but also plays into the scientist wearing many more hats than just programmer. Code can be two or more degrees removed from the published paper -- code isn't the passion. There isn't reason, time, or motivation to think deeply about syntax.
2. For a lot of academic work, the programming language is primarily an interface to an advanced plotting calculator. Or at least that's how I think about the popularity of SPSS and Stata. Ipython and then jupyter made this easy for python.
For what it's worth, the lab I work for is mostly using shell, R, matlab, and tiny bit of python. For numerical analysis, I like R the best. It has a leg up on the interactive interface and feels more flexible than the other two. R also has better stats libraries. But when we need to interact with external services or file formats, python is the place to look (why PyPI beat out CPAN is similar question).
Total aside: Perl's built in regexp syntax is amazing and a thing I reach for often, but regular expressions as a DSL are supported almost everywhere (like using languages other than shell to launch programs and pipes -- totally find but misses all the ergonomics of using the right tool for the job). It'd love to explore APL as an analogous numerical DSL across scripting languages. APL.jl [0] and, less practically april[1], are exciting.
[0] https://github.com/shashi/APL.jl
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Symbolic Programming
APL.jl might be of interest to you.
- Try APL
array
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Ngn/k (free K implementation)
In some of the example programs written in KAP (my APL derivative), I tried to write it in a style that makes people unfamiliar with the array style more comfortable.
This code could of course have been written in a style similar to some of the more extreme examples, and they would have been significantly shorter in that case.
https://github.com/lokedhs/array/blob/master/demo/advent-of-...
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Why would a Java prime sieve run at only half its speed _some_ of the times?
This issue isn't directly related to BitSet. I have observed the same thing in my programming language interpreter that runs on the JVM (well, it's written in Kotlin multiplatform so it runs on JS and Natively as well).
I start the interpreter and measue the time it takes to all all then numbers below 1000000000.
The first time I run it after starting the interpreter it always takes 1.4 seconds (within 0.1 second precision). The second time I measure the time it takes 1.7, and for every invocation following that it takes 2 seconds.
If I stop the interpreter and try again, I get exactly the same result.
I have not been able to explain this behaviour. This is on OpenJDK 11 by the way.
If anyone wants to test this, just run the interpreter from here: https://github.com/lokedhs/array
To run the benchmark, type the following command in the UI:
time:measureTime { +/⍳1000000000 } - Is APL Dead?
- Symbolic Programming
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Try APL
I'm the opportunity to mention my project that implements a language that is inspired by, and is mostly compatible with APL. It has some major differences, such as being lazy evaluated and providing support for first-class functions.
It also supports defining syntax extensions which is used by the standard library to provide imperative syntax, which means you can mix traditional APL together with your familiar if/else statements, etc.
At this point there isn't much documentation, and the implementation isn't complete, so I'm not actually suggesting that people run out to try it unless they are really interested in APL. I just took this opportunity since APL is mentioned so rarely here.
https://github.com/lokedhs/array
There is an example of a graphical mandelbrot implementation in the demo directory, that may be interesting.
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Why am I wasting time on EndBASIC?
This post mirrors my feeling on this topic as well. Just like the author, I'm also working on a programming language which will not be used by a lot of people.
In fact, having a lot of users would make things complicated as I would have to stop making incompatible changes if I want to try something new.
Designing your own programming language is such a nice hobby, and something I believe a lot of programmers do. In fact, I would like to see links to other people's programming languages, just to see what people are playing around with at the moment.
Here is my project: https://github.com/lokedhs/array
What are some alternatives?
ngn-apl - An APL interpreter written in JavaScript. Runs in a browser or NodeJS.
BQN - An APL-like programming language. Self-hosted!
ride - Remote IDE for Dyalog APL
json - A tiny JSON parser and emitter for Perl 6 on Rakudo
julia - The Julia Programming Language
j-prez
conan - Conan - The open-source C and C++ package manager
jelm - Extreme Learning Machine in J
nlvm - LLVM-based compiler for the Nim language