Feature/monadic api tests 2

.gitignore

@@ -28,3 +28,4 @@ bin/
 coverage-html
 .DS_Store
 flake.lock
+tags

dataframe.cabal

@@ -201,7 +201,8 @@ test-suite tests
                    Operations.Subset,
                    Operations.Statistics,
                    Operations.Take,
-                   Parquet
+                   Parquet,
+                   Monad
     build-depends:  base >= 4 && < 5,
                     dataframe ^>= 0.4,
                     directory >= 1.3.0.0 && < 2,

tests/GenDataFrame.hs

@@ -21,8 +21,8 @@ genColumn len =
 
 genDataFrame :: Gen DataFrame
 genDataFrame = do
-    numRows <- choose (0, 100)
-    numCols <- choose (0, 10)
+    numRows <- choose (100, 1000)
+    numCols <- choose (1, 10)
     colNames <- V.fromList <$> vectorOf numCols genUniqueColName
     cols <- V.fromList <$> vectorOf numCols (genColumn numRows)
     let indices = M.fromList $ zip (V.toList colNames) [0 ..]

tests/Main.hs

@@ -18,6 +18,7 @@ import Test.HUnit
 import Test.QuickCheck
 
 import qualified Functions
+import qualified Monad
 import qualified Operations.Aggregations
 import qualified Operations.Apply
 import qualified Operations.Core
@@ -5138,6 +5139,10 @@ main = do
         mapM
             (quickCheckWithResult stdArgs)
             Operations.Subset.tests
-    if failures result > 0 || errors result > 0 || not (all isSuccessful propRes)
+    monadRes <- mapM (quickCheckWithResult stdArgs) Monad.tests
+    if failures result > 0
+        || errors result > 0
+        || not (all isSuccessful propRes)
+        || not (all isSuccessful monadRes)
         then Exit.exitFailure
         else Exit.exitSuccess

tests/Monad.hs

@@ -0,0 +1,27 @@
+module Monad where
+
+import qualified DataFrame as D
+import DataFrame.Internal.DataFrame
+import DataFrame.Monad
+import GenDataFrame ()
+import System.Random
+import Test.QuickCheck
+import Test.QuickCheck.Monadic
+
+roundToTwoPlaces x = fromIntegral (round (x * 100)) / 100.0
+
+prop_sampleM :: DataFrame -> Gen (Gen Property)
+prop_sampleM df = monadic' $ do
+    p <- run $ choose (0.0 :: Double, 1.0 :: Double)
+    let expectedRate = roundToTwoPlaces p
+    seed <- run $ choose (0, 1000)
+    let rowCount = D.nRows df
+    let colCount = D.nColumns df
+    pre (colCount > 1 && rowCount > 100)
+    let finalDf = execFrameM df (sampleM (mkStdGen seed) expectedRate)
+    let finalRowCount = D.nRows finalDf
+    let realRate = roundToTwoPlaces $ fromIntegral finalRowCount / fromIntegral rowCount
+    let diff = abs $ expectedRate - realRate
+    assert (diff <= 0.11)
+
+tests = [prop_sampleM]