dataframe-0.3.0.0: benchmark/Main.hs

{-# LANGUAGE NumericUnderscores #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE TypeApplications #-}

import qualified DataFrame as D
import qualified DataFrame.Functions as F
import qualified Data.Vector.Unboxed as VU
import qualified Data.Vector.Unboxed.Mutable as VUM

import Control.Monad (replicateM)
import Criterion.Main
import DataFrame ((|>))
import Data.Time
import System.Process
import System.Random.Stateful

haskell :: IO ()
haskell = do
  output <- readProcess "cabal" ["run", "dataframe"] ""
  putStrLn output

polars :: IO ()
polars = do
  output <- readProcess "./benchmark/dataframe_benchmark/bin/python3" ["./benchmark/polars/polars_benchmark.py"] ""
  putStrLn output

pandas :: IO ()
pandas = do
  output <- readProcess "./benchmark/dataframe_benchmark/bin/python3" ["./benchmark/pandas/pandas_benchmark.py"] ""
  putStrLn output

groupByHaskell :: IO ()
groupByHaskell = do
  df <- D.readCsv "./data/housing.csv"
  print $ df |> D.groupBy ["ocean_proximity"]
             |> D.aggregate [ (F.minimum (F.col @Double "median_house_value")) `F.as` "minimum_median_house_value"
                            , (F.maximum (F.col @Double "median_house_value")) `F.as` "maximum_median_house_value"]

groupByPolars :: IO ()
groupByPolars = do
  output <- readProcess "./benchmark/dataframe_benchmark/bin/python3" ["./benchmark/polars/group_by.py"] ""
  putStrLn output

groupByPandas :: IO ()
groupByPandas = do
  output <- readProcess "./benchmark/dataframe_benchmark/bin/python3" ["./benchmark/pandas/group_by.py"] ""
  putStrLn output

main = do
  output <- readProcess "cabal" ["build", "-O2"] ""
  putStrLn output
  defaultMain [
    bgroup "stats" [ bench  "simpleStatsHaskell" $ nfIO haskell
                   , bench  "simpleStatsPandas" $ nfIO pandas
                   , bench  "simpleStatsPolars" $ nfIO polars
                   , bench  "groupByHaskell" $ nfIO groupByHaskell
                   , bench  "groupByPolars"  $ nfIO groupByPolars
                   , bench  "groupByPandas"  $ nfIO groupByPandas
                   ]
    ]