timestats
This is a simple library for profiling time that can help when more
sophisticated tools aren’t available or needed. Most programs should
be possible to analyze by instrumenting the code with a few calls
and then building and running the application as usual.
This library associates fragments of a program with labels, and
measures the execution time of these fragments using the function
getMonotonicTimeNSec.
Multiple measures of a same program fragment (or different fragments
using the same label) are aggregated and reported at chosen times of
the execution.
The announcement post contains additional
motivation.
Usage
import Control.Exception (evaluate)
import qualified Debug.TimeStats as TimeStats (printTimeStats, measureM)
fib n = if n < 2 then 1 else fib (n - 1) + fib (n - 2)
main = do
-- measureM collects the time taken to compute the given action
-- and stores it associated with a given label in global state.
TimeStats.measureM "fib" $ evaluate (fib 31)
-- measuring multiple times with the same label adds up
-- the time taken by all of those invocations
TimeStats.measureM "fib2" $ evaluate (fib 30)
-- adds up to the existing "fib2" stats
TimeStats.measureM "fib2" $ evaluate (fib 29)
TimeStats.printTimeStats
The output when running the program with timestats enabled will look as
$ DEBUG_TIMESTATS_ENABLE=1 ./a.out
fib: 2.055s count: 1
fib2: 2.071s count: 2
timestats is enabled by setting the environment variable
DEBUG_TIMESTATS_ENABLE to any value ahead of invoking any function
in Debug.TimeStats.
See the API documentation for further details.
