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5 points by cchooper 6063 days ago | link | parent

Everyone who comes to Lisp has problems with the syntax at first. It's not hard, it just takes time to unlearn all that bad syntax from other languages :)

It also sounds like you're not used to functional programming. That's a much harder hurdle, because it's a completely different way of thinking, a whole new world. You basically have to learn to program all over again.

But it's worth it. Imperative programming is simple to learn, but can only take you so far. In contrast, you can spend your whole life learning functional programming and you'll just keep getting better and better at it. There's a virtual infinity of new abstractions and techniques you can use, and there are whole branches of computer science inventing more: iterators, generators, zippers, monads, arrows, lazy lists... It's endless.

So don't worry if you find Lisp hard. Everyone does. All I can say is that everyone who has persevered at it and mastered it comes to love it and never wants to go back.



3 points by kens 6063 days ago | link

I've interviewed a lot of people who have experience with Lisp, and I ask them if they think learning Lisp is worthwhile. Almost all of them reply with some variant of "Why on earth would you do that?" I've received a couple "Yes, definitely" replies from people who are hard-core Lisp hackers. So empirically it seems that most people who learn Lisp don't find it particularly rewarding.

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1 point by absz 6058 days ago | link

I've talked to many fewer people than you, but my impression has been slightly different. Broadly speaking, the engineer-type programmers tend to dislike Lisp, and the computer-science-type programmers tend to like it. (Those two classes cover, in my [albeit limited] experience, two of the principle ways of thinking about programming.)

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1 point by almkglor 6057 days ago | link

LOL. Considering that my boss thinks I'm an engineer (and hired me as such), this really hurts!

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1 point by absz 6057 days ago | link

Eh. It's attitude, not job description :) And anyway, you should probably take that with a relatively enormous grain of salt, as small sample sizes aren't conducive to accurate data.

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