README.md

Benchee

Library for easy and nice (micro) benchmarking in Elixir. It allows you to compare the performance of different pieces of code and functions at a glance. Benchee is also versatile and extensible, relying only on functions - no macros!

Somewhat inspired by benchmark-ips from the ruby world, but of course it is a more functional spin as it fully lives in the Elixir world.

Provides you with the following statistical data:

• average - average execution time (the lower the better)
• ips - iterations per second, how often can the given function be executed within one second (the higher the better)
• deviation - standard deviation (how much do the results vary), given as a percentage of the average (raw absolute values also available)
• median - when all measured times are sorted, this is the middle value (or average of the two middle values when the number of samples is even). More stable than the average and somewhat more likely to be a typical value you see.

Benchee also first runs the functions for a given warmup time without recording the results, to simulate a "warm" running system.

Benchee does not:

• Keep results of previous and compare them, if you want that have a look at benchfella or bmark

Benchee has no runtime dependencies and is aimed at being the core benchmarking logic. Further functionality is provided through plugins that then pull in dependencies, such as CSV export. Check out the available plugins!

Installation

When available in Hex, the package can be installed as:

Add benchee to your list of dependencies in mix.exs:

def deps do
  [{:benchee, "~> 0.2", only: :dev}]
end

Install via mix deps.get and then happy benchmarking as described in Usage :)

Usage

After installing just write a little Elixir benchmarking script:

list = Enum.to_list(1..10_000)
map_fun = fn(i) -> [i, i * i] end

Benchee.run(%{time: 3},
             [{"flat_map", fn -> Enum.flat_map(list, map_fun) end},
              {"map.flatten",
              fn -> list |> Enum.map(map_fun) |> List.flatten end}])

First configuration options are passed, the only options available so far are:

• warmup - the time in seconds for which a benchmark should be run without measuring times before real measurements start. This simulates a "warm" running system. Defaults to 2.
• time - the time in seconds for how long each individual benchmark should be run and measured. Defaults to 5.

Running this script produces an output like:

tobi@happy ~/github/benchee $ mix run samples/run.exs
Benchmarking flat_map...
Benchmarking map.flatten...

Name                          ips            average        deviation      median
map.flatten                   1311.84        762.29μs       (±13.77%)      747.0μs
flat_map                      896.17         1115.86μs      (±9.54%)       1136.0μs

Comparison:
map.flatten                   1311.84
flat_map                      896.17          - 1.46x slower

See the general description for the meaning of the different statistics.

It is important to note that the benchmarking code shown before is the convenience interface. The same benchmark in its more verbose form looks like this:

list = Enum.to_list(1..10_000)
map_fun = fn(i) -> [i, i * i] end

Benchee.init(%{time: 3})
|> Benchee.benchmark("flat_map", fn -> Enum.flat_map(list, map_fun) end)
|> Benchee.benchmark("map.flatten",
                     fn -> list |> Enum.map(map_fun) |> List.flatten end)
|> Benchee.measure
|> Benchee.statistics
|> Benchee.Formatters.Console.format
|> IO.puts

This is a take on the functional transformation of data applied to benchmarks here:

1. Configure the benchmarking suite to be run
2. run n benchmarks with the given configuration gathering raw run times per function (done in 2 steps, gathering the benchmarks and then running them with Benchee.measure)
3. Generate statistics based on the raw run times
4. Format the statistics in a suitable way
5. Output the formatted statistics

This is also part of the official API and allows for more fine grained control. Do you just want to have all the raw run times? Grab them before Benchee.statistics! Just want to have the calculated statistics and use your own formatting? Grab the result of Benchee.statistics! Or, maybe you want to write to a file or send an HTTP post to some online service? Just replace the IO.puts.

This way Benchee should be flexible enough to suit your needs and be extended at will. Have a look at the available plugins.

For more example usages and benchmarks have a look at the samples directory!

Plugins

Packages that work with Benchee to provide additional functionality.

• BencheeCSV - generate CSV from your Benchee benchmark results so you can import them into your favorite spreadsheet tool and make fancy graphs

(You didn't really expect to find tons of plugins here when the library was just released, did you? ;) )

Contributing

Contributions to Benchee are very welcome! Bug reports, documentation, spelling corrections, whole features, feature ideas, bugfixes, new plugins, fancy graphics... all of those (and probably more) are much appreciated contributions!

You can get started with a look at the open issues.

A couple of (hopefully) helpful points:

• Feel free to ask for help and guidance on an issue/PR ("How can I implement this?", "How could I test this?", ...)
• Feel free to open early/not yet complete pull requests to get some early feedback
• When in doubt if something is a good idea open an issue first to discuss it
• In case I don't respond feel free to bump the issue/PR or ping me on other places

Development

• mix deps.get to install dependencies
• mix test to run tests or mix test.watch to run them continuously while you change files
• mix credo or mix credo --strict to find code style problems (no too strict with the 80 width limit for sample output in the docs)