Summary: I describe a simple interview problem (counting frequencies of unique words), solve it in various languages, and compare performance across them. For each language, I’ve included a simple, idiomatic solution as well as a more optimized approach via profiling…
Language Simple Optimized Notes grep0.04 0.04 grepbaseline; optimized setsLC_ALL=Cwc -w0.29 0.20 wcbaseline; optimized setsLC_ALL=CZig 0.54 by ifreund and matu3ba Nim 0.76 0.58 by csterritt and euantorano C 0.97 0.23 Go 1.14 0.39 Crystal 1.29 by Andrea Manzini PHP 1.36 by Max Semenik Rust 1.43 0.38 by Andrew Gallant C# 1.51 0.82 by J Taylor, Y Ostapenko, O Turan OCaml 1.72 by Nate Dobbins and Pavlo Khrystenko C++ 1.73 0.42 optimized by Jussi Pakkanen Perl 1.81 by Charles Randall F# 1.82 1.59 by Yuriy Ostapenko Kotlin 1.86 by Kazik Pogoda Python 2.07 1.30 Lua 2.50 1.97 by themadsens; runs under luajit JavaScript 2.52 1.90 by Dani Biro and Flo Hinze Ruby 3.13 2.43 by Bill Mill AWK 3.55 1.13 optimized uses mawkD 4.16 1.01 by Ross Lonstein Swift 4.23 by Daniel Muellenborn Forth 4.26 1.46 Shell 14.60 1.85 optimized does LC_ALL=C sort -S 2G
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