idris-blink VS post-rfc

Or on one useless occasion, Idris, https://github.com/stepcut/idris-blink

With that being said, Python is without a doubt the best option, and I'd also be very interested to read the articles you found that say that Python is not a good choice because it's been the industry standard for a long time now. Data science and machine learning are one of the areas where the Haskell ecosystem is not as strong as other languages, but libraries and tools do exist. There's a great list of Haskell resources by domain here, and as you can see, there are Haskell bindings to tensorflow and pytorch, along with other libraries that support common data science programming.

State of the Haskell Ecosystem lists libraries for many of its domains.

Recently saw this repo that shows the state of Haskell in a lot of programming applications. It classifies it as Immature for Numerical Programming; I would like to know what are the challenges in it.

Good resource: https://github.com/Gabriel439/post-rfc/blob/main/sotu.md

I know haskell has https://github.com/Gabriel439/post-rfc/blob/main/sotu.md, clojure has https://clojure.org/news/2021/04/06/state-of-clojure-2021, and scala has https://www.jetbrains.com/lp/devecosystem-2021/scala/. I only find the haskell survey complete enough to use in evaluating haskell for production use on a new project.

Seriously though, Haskell is a very practical programming language that especially shines for some very useful real world application domains.

https://github.com/Gabriel439/post-rfc/blob/main/sotu.md will probably help here

At work, we tend to build so-called "serverless" APIs, running on AWS. Haskell's story for maintainable software, provided you have the libraries, is excellent. The State of the Haskell Ecosystem document is a good starting point. Once you have a toe-hold running systems in production, the cost of building "just that one missing library" is often not too bad.