fp.

But the main idea I was going for was real-time JIT evaluation with rendered errors (specifically learning / using cranelift JIT) - less to do with the calculator aspect.

I ended up choosing miette for errors.

https://github.com/jasonjmcghee/basic-treesitter-cranelift-j...

occamatl•8mo ago

> sqrt(10^100)-1 -> 100000000000000000000000000000000000000000000000000

Not what I expected.

emaro•8mo ago

In the readme it says it uses double precision for numbers. Also not quite whet I expected from 'arbitrary precision'.

chriswarbo•8mo ago

Hmm, yeah. It cites `bc` as prior art, which is quite widely used; but another interesting arbitrary-precision calculator is spigot https://www.chiark.greenend.org.uk/~sgtatham/spigot/spigot.h...

mananaysiempre•8mo ago

Also the AOSP calculator, of course[1,2,3].

[1] https://chadnauseam.com/coding/random/calculator-app

[2] https://dl.acm.org/doi/10.1145/2911981

[3] https://dl.acm.org/doi/10.1145/3385412.3386037

emmelaich•8mo ago

Ivy does big numbers (not arbitrary) but does rationals too. It's an APL subset.

    0.1 + 0.2
    3/10

https://github.com/robpike/ivy

lttlrck•8mo ago

the addition of astro_float fixed this.

primitivesuave•8mo ago

The UI is awesome, amazing work! However, arbitrary precision implies that there is no fixed upper limit to the number of digits - simple tests like `0.1 + 0.2 == 0.3` and `2^53 == 2^53 + 1` (both produce "false") indicates you're still using IEEE 754 double precision floats.

If "arbitrary precision" is not as important to you as "high precision", a 128 bit decimal has enough precision for 99% of real-world applications.

crap•8mo ago

Thanks for checking it out! Should have been more clear that this is actively being worked on. This is ultimately the goal, and I'm currently working on integrating `astro_float` as the base for numbers.

primitivesuave•8mo ago

That is awesome, I look forward to following the project and hopefully contributing! I became a better Rust programmer from reading your code :)

jdhwosnhw•8mo ago

Do you mean, the first returns false and the second returns true?

primitivesuave•8mo ago

Ah you're right, thank you for pointing it out!

In the previous version of this comment (where I was still reading it incorrectly) I added a fun fact, that the significand of an IEEE 754 double-precision float is only allocated 52 bits, but the "hidden bit trick" provides an extra bit of precision when the normalized form starts with 1.

johannesrexx•8mo ago

Rewrite it like so

> 1/10 + 2/10 == 3/10 true >

I_complete_me•8mo ago

I wish you well. And I clicked you a star on github. Keep up the good work.

crap•8mo ago

Thanks to everyone who gave feedback!

Arbitrary precision is now supported in 0.3.0 after integrating the `astro_float` (https://docs.rs/astro-float/latest/astro_float/index.html) `BigFloat` type as the base for numbers in the language.

Still working out the kinks, but its live so give it a try!

lttlrck•8mo ago

This is cool.

It love to have to base conversion functions, even if it's print only. Does that fit at all?

lttlrck•8mo ago

and different input base notations, 0x, o, 0b etc

crap•8mo ago

This definitely fits, base conversion is on the roadmap!

librasteve•8mo ago

very cool, welcome to the small club of CLI calculator authors! before I read this I knew of frink and crag (https://raku.land/zef:librasteve/App::Crag since you ask)

Crag is built on raku so has some neat tricks up its sleeve - you can see Crag of the Day to see some in action...

  crag '0.1+0.2=0.2'   #True (arbitrary precision)
  crag '₃₆123.45'      #3F.G77777  (base 36)
  crag 'e ** (i * π) =~= -1'   #True  (math symbols, complex numbers)
  crag '0rMCMXLIV'     #1944 (Roman numerals)
  crag '^<௪௨ mph>'     #42mph  (Unicode and units)

hee hee