Two weeks ago someone ran a poll on Hacker News
asking what the readers’ favorite programming language was. Yesterday
(April 5) I took a look back at the poll to see who came out on top.
I wasn’t surprised to see Python win, but I was surprised to see it lead Ruby by over 1,000 votes. C# fared well with 5th place, and Haskell and Clojure rounded out the top 10.
Polls like this don’t do much to tell us which programming languages are “best” or what languages are most used in production. They’re not even controlled to make sure the people voting are actually programmers, so it’s hard to read too much into them. But they do tell a bit about what languages developers like to use. As developers become entrepreneurs and startups become enterprises, these sort of preferences can have an impact on the job market, so taking a look at these sorts of lists can help developers decide what to learn. And for employers, they can provide a data point for deciding what languages attract developers. Of course the usual caveats apply – use the best tool for the job and use these results as only a single data point weighted against many others to decide what to learn/use.
I wasn’t surprised to see Python win, but I was surprised to see it lead Ruby by over 1,000 votes. C# fared well with 5th place, and Haskell and Clojure rounded out the top 10.
- Python (3044)
- Ruby (1718)
- JavaScript (1412)
- C 966
- C# 828
- PHP 662
- Java 551
- C++ 529
- Haskell 518
- Clojure 458
- CoffeeScript 361
- Objective C 326
- Lisp 321
- Perl 310
- Scala 233
- Scheme 190
- Other 188
- Erlang 162
- Lua 145
- SQL 101
Polls like this don’t do much to tell us which programming languages are “best” or what languages are most used in production. They’re not even controlled to make sure the people voting are actually programmers, so it’s hard to read too much into them. But they do tell a bit about what languages developers like to use. As developers become entrepreneurs and startups become enterprises, these sort of preferences can have an impact on the job market, so taking a look at these sorts of lists can help developers decide what to learn. And for employers, they can provide a data point for deciding what languages attract developers. Of course the usual caveats apply – use the best tool for the job and use these results as only a single data point weighted against many others to decide what to learn/use.
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