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As a Lisp fan who sometimes codes in Scheme and Common Lisp whenever I get the chance, I agree with you. The gap has certainly narrowed in the past 20 or so ye

As a Lisp fan who sometimes codes in Scheme and Common Lisp whenever I get the chance, I agree with you. The gap has certainly narrowed in the past 20 or so years between Lisp and widely-used programming languages. In addition, the rise of statically-typed functional programming languages like OCaml and Haskell provide another alternative for those who love functional programming but want Hindley-Milner types. I still think Lisp, whether in the form of Scheme or Common Lisp (I haven’t tried Clojure), is quite enlightening due to the immense flexibility these languages provide. However, I’m reminded of the rationale of MIT’s decision back in 2009 to move away from SICP and Scheme in the intro CS course in favor of Python: the vast majority of developers aren’t building new ecosystems from the ground up, but are instead reliant on an ecosystem of libraries. Lisps are wonderful for creating whole worlds due to the powerful tools they provide. I’m currently working on a side project where Lisp’s flexibility comes in handy. But if I’m effectively gluing together APIs to build a solution (and this is not an insult), then do I need macros, MOP, multiple dispatch, and homoiconicity? Thus, many programmers do not need the full power of Lisp to get their jobs done. There’s also the fact that languages like Python and JavaScript have a lot more commercial and community backing than Scheme and Common Lisp. If I’m writing something complex like a DBMS or web browser, then Common Lisp would be one of my first choices. However, if I’m writing a machine learning application or a web application, then I’ll most likely reach for Python or JavaScript, respectively, due to the library ecosystems.

brightball 3y ago
If you have any interest in submitting a talk for a polyglot conference in South Carolina this August, you're talking about several languages that haven't yet been represented in the submissions. I don't think Lisp, Scheme, OCaml or Haskell talks have been submitted yet actually. https://blog.carolina.codes/p/call-for-speakers-is-now-open-2023 https://blog.carolina.codes/p/call-for-speakers-is-now-open-... If you decide to submit a talk, the deadline is May 25th.
7thaccount 3y ago
I feel exactly the same. I wish I did something cool enough to require the full power of lisp, but generally speaking...I just need to glue some stuff together. Other people will have different needs though. I can still appreciate the beauty of lisp and I'm glad its out there in case I ever need it!
- vindarel 3y ago
  You don't need to do something super cool to use CL. Boring stuff works too. I use a small program in production© that reads a DB, formats data and sends it to FTP servers. Was a breeze to develop, is a breeze to deploy. It's a better experience overall for me than doing it in Python. Oh, and I do use CL's super powers during development: interactive debugger, restarting a point in the stackframe, fast and incremental compilation, good type checks by SBCL… and I get a fast binary. Learning didn't come without a few gotchas, but they're all better documented out there now.
lukego 3y ago
> if I’m writing a machine learning application or a web application, then I’ll most likely reach for Python or JavaScript, respectively, due to the library ecosystems. This sounds eminently sensible but it never pans out that way in practice for me: How do you understand the ML algorithms if you haven't implemented them yourself? And if you have implemented them for the sake of understanding, in whatever language you fancied, why not just keep using that implementation? The reason I'd choose Python in practice would be as a social compromise with collaborators. (I say this having recently switched from Julia to Common Lisp because I didn't feel the ecosystem was giving me much practical benefit.)
- Thiez 3y ago
  Do you drive a car you built from scratch? How can you drive from A to B without first understanding how a car works by building one? And since you already built one, why not just keep using that one? Or maybe you have built a car. But did you type your message on a computer you built yourself using some silicon and a home-baked x-ray lithography machine? I definitely think there can be value in reimplementing something for educational purposes, but often knowing how to use something without necessarily being able to build it yourself is just fine. And those things you do build for educational purposes should almost always be abandoned after serving their educational purpose.
  - lukego 3y ago
    Fair point on general. My limited experience with probabilistic sorts of programming though is that the risk of misunderstanding/misuse is very high relative to the implementation complexity. Cars and. X-ray machines don't have simple implementations. Often very little code but a lot of opportunities to goof up one assumption or another. But yeah I'm probably overgeneralizing from limited experience.

brightball 3y ago

If you have any interest in submitting a talk for a polyglot conference in South Carolina this August, you're talking about several languages that haven't yet been represented in the submissions. I don't think Lisp, Scheme, OCaml or Haskell talks have been submitted yet actually. https://blog.carolina.codes/p/call-for-speakers-is-now-open-2023 https://blog.carolina.codes/p/call-for-speakers-is-now-open-... If you decide to submit a talk, the deadline is May 25th.

7thaccount 3y ago

I feel exactly the same. I wish I did something cool enough to require the full power of lisp, but generally speaking...I just need to glue some stuff together. Other people will have different needs though. I can still appreciate the beauty of lisp and I'm glad its out there in case I ever need it!

vindarel 3y ago
You don't need to do something super cool to use CL. Boring stuff works too. I use a small program in production© that reads a DB, formats data and sends it to FTP servers. Was a breeze to develop, is a breeze to deploy. It's a better experience overall for me than doing it in Python. Oh, and I do use CL's super powers during development: interactive debugger, restarting a point in the stackframe, fast and incremental compilation, good type checks by SBCL… and I get a fast binary. Learning didn't come without a few gotchas, but they're all better documented out there now.

lukego 3y ago

> if I’m writing a machine learning application or a web application, then I’ll most likely reach for Python or JavaScript, respectively, due to the library ecosystems. This sounds eminently sensible but it never pans out that way in practice for me: How do you understand the ML algorithms if you haven't implemented them yourself? And if you have implemented them for the sake of understanding, in whatever language you fancied, why not just keep using that implementation? The reason I'd choose Python in practice would be as a social compromise with collaborators. (I say this having recently switched from Julia to Common Lisp because I didn't feel the ecosystem was giving me much practical benefit.)

Thiez 3y ago
Do you drive a car you built from scratch? How can you drive from A to B without first understanding how a car works by building one? And since you already built one, why not just keep using that one? Or maybe you have built a car. But did you type your message on a computer you built yourself using some silicon and a home-baked x-ray lithography machine? I definitely think there can be value in reimplementing something for educational purposes, but often knowing how to use something without necessarily being able to build it yourself is just fine. And those things you do build for educational purposes should almost always be abandoned after serving their educational purpose.
- lukego 3y ago
  Fair point on general. My limited experience with probabilistic sorts of programming though is that the risk of misunderstanding/misuse is very high relative to the implementation complexity. Cars and. X-ray machines don't have simple implementations. Often very little code but a lot of opportunities to goof up one assumption or another. But yeah I'm probably overgeneralizing from limited experience.