wiwinwlh VS reanimate

wiwibwlh

In this respect, The Haskell Guide is not a tutorial, project-based guide or textbook, which aims to give a more complete walk through the language, in a linear fashion, but more like a reference guide that is carefully designed to be accessible and clear. In that respect, it's like a beginner level version of What I Wish I Knew When I Learned Haskell, with more cross-referencing. (By the way, I don't think this is a substitute for more in-depth or didactically rich resources at all; it's trying to address a different problem.)

Many libraries try to stick to Haskell 98. Also whenever someone writes a paper about some new techniques, they always seem to take a lot of pleasure in pointing out when their technique works in Haskell 98.

I like that you can mix and match GHC extensions even in the same project. So one library (or even just one module) might use some crazy and messy extensions, but you can still use it from vanilla Haskell.

http://dev.stephendiehl.com/hask/#language-extensions has a list of extensions and some judgement on them.

For example, I really like TupleSections. They are not strictly necessary for anything, they are purely cosmetic / syntactic sugar. But they also don't cause any mess. https://ghc.gitlab.haskell.org/ghc/doc/users_guide/exts/tupl...

Also: TypedHoles are really neat for developing, and will never show up in your final code. https://ghc.gitlab.haskell.org/ghc/doc/users_guide/exts/type...

Maybe try to implement something using Haskell? For example, try to read through: https://en.wikibooks.org/wiki/Write_Yourself_a_Scheme_in_48_Hours to see how the concepts are used in a "real world" setting. Also, https://github.com/sdiehl/wiwinwlh is an underrated resource imo. Anyways, the best way to learn Haskell is to just use it. I'm still learning myself, so I don't have much to say beyond that.

Reanimate sounds almost ideal, with its support for LaTeX. But unfortunately, it is all rendered in batch, not providing for any interactivity.

Is this the discussion you're referring to? https://github.com/reanimate/reanimate/discussions/210

It's actually pretty interesting to read. The author makes a not totally unreasonable argument as for why it uses unsafePerformIO.

Now what I'm really curious about is why the very first example on the site I clicked into the source code for, a simple 59-line example, is using unsafePerformIO. That actually worries me more because it suggests that as a user I might have to use unsafePerformIO. https://github.com/reanimate/reanimate/blob/d4d3898831edb4aa...

Not really dashboard library, but reanimate is a good library for this kind of stuff.

Some other "applications" (if you're not interested in compilers) might be writing shell scripts: https://hackage.haskell.org/package/turtle Or animating stuff: https://github.com/reanimate/reanimate and https://hackage.haskell.org/package/gloss

That aside, it seems that svg-tree doesn’t support filter elements, so I recommend reanimate-svg. You can join the Discord server for Reanimate and ask for help. Good luck.

See also reanimate, a very similar Haskell library: https://reanimate.github.io/

This is very niche, but something I've wanted to do for a while is to generate some cool physics example on the surface of a sphere with https://hackage.haskell.org/package/hamilton, and display it with https://reanimate.github.io/ (using https://hackage.haskell.org/package/linear for the projection)

Hi u/Target_Organic, I wich you a warm welcome! Haskell is often very satisfying to work with, it has a sense of beauty in it. Regarding your questions: 1. I never had big problems about performance. However, I personally place more emphasis about correctness, simplicity and readability of my programs. Performance tuning comes after. 2. For graphic libraries, I know diagrams, Reanimate and Haskell-chart. Since you seems interested by mathematical approach to graphics, I think you will find happiness there. 3. I'm not sure about the AI field. Other, more practical languages such as Python seems to have taken the lead. What is sure for me, that Machine Learning/NN would be nicely describe in Haskell with solid foundations.