Profiling Crystal on OSX


How do I profile my program to determine where it is slow?

This is one of the first questions any developer asks after building a non-toy program. Crystal has a reputation for being quite fast but every language has tricks and optimizations we miss.

Since Crystal uses the LLVM compiler suite, we can reuse a lot of the infrastructure which knows about LLVM-compiled binaries. Net result: the OSX Developer Tools include a beautiful profiler that works with Crystal binaries out of the box - so awesome! If you have XCode installed (and if you are reading this blog, it’s very likely you do), you can profile a Crystal binary right now, here’s how.

Instruments is the OSX profiling tool. We’re going to instrument a command line run and then view the results in its GUI. I assume you have Crystal installed; if not, run this:

brew update
brew install crystal-lang

Now we need an app to profile. Let’s make a toy app that doesn’t do much of anything; put this code in

def foo(i)
  "mike" + i.to_s

10_000_000.times do |x|

Compile and run in the profiler:

$ crystal compile
$ instruments -t "Time Profiler" ./app
Instruments Trace Complete (Duration : 4.458741s; Output : /Users/mike/instrumentscli0.trace)
$ open instrumentscli0.trace/

You should now see a lovely UI with a totally rad tree view where you can drill down into the trace to see where your code spent its time. Looks like 80% of my app’s time was spent in Int32#to_s and String#+, not exactly shocking but this is a toy example.

crystal profiler

Note that I didn’t use --release flag with the compiler. This was a choice I made for this blog post; the traces are a LOT easier to understand without release optimizations because LLVM doesn’t inline method calls so it’s easier to drill into the code execution. You should profile with the –release flag when profiling your own non-trivial code so you are profiling the same binary as you run in production.

Also note that Instruments supports a lot more modes that just the Time Profiler - it can track memory allocations, syscalls, and many other aspects. Play with it and see what modes are useful to you.

In conclusion, profiling Crystal code is super easy due to Crystal leveraging the LLVM compiler. We can use LLVM-standard tools rather than needing custom profiling APIs and runtime support.