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Experiments with different languages doing typical task

License: MIT License

Go 5.27% Rust 5.03% Elixir 4.51% Haskell 4.88% Ruby 5.44% Shell 0.13% Io 2.71% Scala 4.32% Python 2.90% Erlang 3.42% Clojure 3.33% OCaml 3.54% Hy 3.43% Makefile 15.31% C 9.34% C++ 5.94% Objective-C 6.84% Swift 4.53% C# 5.20% Lua 3.93%
go csharp elixir erlang fsharp haskell java javascript kotlin lua nim objective-c ocaml perl python ruby rust scala swift language-learning

explore's Introduction

Should take folder and field as parameters. Then scan all JSON files in that folder and generate CSV with sorted frequency report about strings in given field.

[✓] C
[✓] C#
[✓] C++
[✓] Clojure
[✓] D
[✓] Elixir
[✓] Erlang
[✓] F#
[✓] Go
[✓] Haskell
[✓] Hy
[ ] Idris
[✓] Io
[✓] Java
[✓] JavaScript (NodeJS)
[✓] Kotlin
[✓] Lua
[✓] Nim
[✓] Objective-C
[✓] OCaml
[✓] Perl
[✓] Python
[✓] Ruby
[✓] Rust
[✓] Scala
[✓] Swift

Benchmarks Timing for JVM-like languages is not that fair due to very short nature of task compared to VM startup cost. So we will repeat process call 100 times in main to get more accurate timing. Also some results are strange (like Elixirs' x1-x100 small run time diference) and can mean there is caching involved.

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