Rename depth into maxDepth in toDataFrame and count from 0 instead of 1. Fix bug in implementation.

Author: nikitinas

src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/toDataFrame.kt

@@ -28,14 +28,14 @@ import kotlin.reflect.KProperty
 // region read DataFrame from objects
 
 public inline fun <reified T> Iterable<T>.toDataFrame(): DataFrame<T> = toDataFrame {
-    properties(depth = 1)
+    properties()
 }
 
 public inline fun <reified T> Iterable<T>.toDataFrame(noinline body: CreateDataFrameDsl<T>.() -> Unit): DataFrame<T> = createDataFrameImpl(T::class, body)
 
-public inline fun <reified T> Iterable<T>.toDataFrame(vararg props: KProperty<*>, depth: Int = 1): DataFrame<T> =
+public inline fun <reified T> Iterable<T>.toDataFrame(vararg props: KProperty<*>, maxDepth: Int = 0): DataFrame<T> =
     toDataFrame {
-        properties(roots = props, depth = depth)
+        properties(roots = props, maxDepth = maxDepth)
     }
 
 public inline fun <reified T> DataColumn<T>.read(): AnyCol = when (kind()) {
@@ -45,7 +45,7 @@ public inline fun <reified T> DataColumn<T>.read(): AnyCol = when (kind()) {
         typeClass == File::class -> cast<File?>().mapNotNullValues { DataFrame.read(it) }
         typeClass == URL::class -> cast<URL?>().mapNotNullValues { DataFrame.read(it) }
         else -> values().createDataFrameImpl(typeClass) {
-            (this as CreateDataFrameDsl<T>).properties(depth = 1)
+            (this as CreateDataFrameDsl<T>).properties()
         }.asColumnGroup(name()).asDataColumn()
     }
 }
@@ -172,7 +172,7 @@ public abstract class CreateDataFrameDsl<T> : TraversePropertiesDsl {
 
     public abstract fun properties(
         vararg roots: KProperty<*>,
-        depth: Int = 1,
+        maxDepth: Int = 0,
         body: (TraversePropertiesDsl.() -> Unit)? = null
     )
 

src/main/kotlin/org/jetbrains/kotlinx/dataframe/impl/api/toDataFrame.kt

@@ -100,12 +100,12 @@ internal class CreateDataFrameDslImpl<T>(
         }
     }
 
-    override fun properties(vararg roots: KProperty<*>, depth: Int, body: (TraversePropertiesDsl.() -> Unit)?) {
+    override fun properties(vararg roots: KProperty<*>, maxDepth: Int, body: (TraversePropertiesDsl.() -> Unit)?) {
         val dsl = configuration.clone()
         if (body != null) {
             body(dsl)
         }
-        val df = convertToDataFrame(source, clazz, roots.toList(), dsl.excludeProperties, dsl.preserveClasses, dsl.preserveProperties, depth)
+        val df = convertToDataFrame(source, clazz, roots.toList(), dsl.excludeProperties, dsl.preserveClasses, dsl.preserveProperties, maxDepth)
         df.columns().forEach {
             add(it)
         }
@@ -127,7 +127,7 @@ internal fun convertToDataFrame(
     excludes: Set<KProperty<*>>,
     preserveClasses: Set<KClass<*>>,
     preserveProperties: Set<KProperty<*>>,
-    depth: Int
+    maxDepth: Int
 ): AnyFrame {
     val order = getPropertiesOrder(clazz)
 
@@ -167,7 +167,7 @@ internal fun convertToDataFrame(
         val kclass = (type.classifier as KClass<*>)
         when {
             hasExceptions -> DataColumn.createWithTypeInference(it.columnName, values, nullable)
-            preserveClasses.contains(kclass) || preserveProperties.contains(property) || (depth == 1 && !type.shouldBeConvertedToFrameColumn() && !type.shouldBeConvertedToColumnGroup()) || kclass.isValueType ->
+            preserveClasses.contains(kclass) || preserveProperties.contains(property) || (maxDepth <= 0 && !type.shouldBeConvertedToFrameColumn() && !type.shouldBeConvertedToColumnGroup()) || kclass.isValueType ->
                 DataColumn.createValueColumn(it.columnName, values, property.returnType.withNullability(nullable))
             kclass == DataFrame::class && !nullable -> DataColumn.createFrameColumn(it.columnName, values as List<AnyFrame>)
             kclass == DataRow::class -> DataColumn.createColumnGroup(it.columnName, (values as List<AnyRow>).concat())
@@ -191,15 +191,15 @@ internal fun convertToDataFrame(
                             if (it == null) DataFrame.empty()
                             else {
                                 require(it is Iterable<*>)
-                                convertToDataFrame(it, elementClass, emptyList(), excludes, preserveClasses, preserveProperties, depth - 1)
+                                convertToDataFrame(it, elementClass, emptyList(), excludes, preserveClasses, preserveProperties, maxDepth - 1)
                             }
                         }
                         DataColumn.createFrameColumn(it.columnName, frames)
                     }
                 }
             }
             else -> {
-                val df = convertToDataFrame(values, kclass, emptyList(), excludes, preserveClasses, preserveProperties, depth - 1)
+                val df = convertToDataFrame(values, kclass, emptyList(), excludes, preserveClasses, preserveProperties, maxDepth - 1)
                 DataColumn.createColumnGroup(it.columnName, df)
             }
         }

src/test/kotlin/org/jetbrains/kotlinx/dataframe/rendering/html/Browsing.kt

@@ -24,7 +24,7 @@ class Browsing {
         val df = students.toDataFrame {
             "year of birth" from { 2021 - it.age }
 
-            properties(depth = 2) {
+            properties(maxDepth = 1) {
 //                exclude(Score::subject) // `subject` property will be skipped from object graph traversal
 //                preserve<Name>() // `Name` objects will be stored as-is without transformation into DataFrame
             }

src/test/kotlin/org/jetbrains/kotlinx/dataframe/testSets/person/DataFrameTests.kt

@@ -2202,7 +2202,7 @@ class DataFrameTests : BaseTest() {
         val list = grouped.toListOf<Target>()
         list shouldBe grouped.convertTo<Target>().toList()
 
-        val listDf = list.toDataFrame(depth = 2)
+        val listDf = list.toDataFrame(maxDepth = 2)
         listDf shouldBe grouped.update { getFrameColumn("students") }.with { it.remove("city") }
 
         listDf.toList() shouldBe list
@@ -2229,7 +2229,7 @@ class DataFrameTests : BaseTest() {
         val list = grouped.toListOf<Target>()
         list shouldBe grouped.convertTo<Target>().toList()
 
-        val listDf = list.toDataFrame(depth = 2)
+        val listDf = list.toDataFrame(maxDepth = 2)
         listDf shouldBe grouped
         listDf.toList() shouldBe list
     }

tests/src/test/kotlin/org/jetbrains/kotlinx/dataframe/api/toDataFrame.kt

@@ -111,7 +111,7 @@ class CreateDataFrameTests {
     fun `don't convert value types`() {
         data class Entry(val a: Int, val b: String, val c: Boolean, val e: DummyEnum)
 
-        val df = listOf(Entry(1, "s", true, DummyEnum.A)).toDataFrame(depth = 100)
+        val df = listOf(Entry(1, "s", true, DummyEnum.A)).toDataFrame(maxDepth = 100)
         df.columns().forEach {
             it.kind shouldBe ColumnKind.Value
         }
@@ -122,11 +122,31 @@ class CreateDataFrameTests {
         class Child
         class Entry(val a: Int, val child: Child)
 
-        val df = listOf(Entry(1, Child())).toDataFrame(depth = 100)
+        val df = listOf(Entry(1, Child())).toDataFrame(maxDepth = 100)
         df.rowsCount() shouldBe 1
 
         val childCol = df[Entry::child]
         childCol.kind() shouldBe ColumnKind.Group
         childCol.asColumnGroup().columnsCount() shouldBe 0
     }
+
+    @Test
+    fun `convert child schemas`() {
+        class Child2(val s: String)
+
+        @DataSchema
+        class Child1(val child: Child2)
+
+        @DataSchema
+        class Entry(val a: Int, val child: Child1)
+
+        val df = listOf(Entry(1, Child1(Child2("s")))).toDataFrame()
+        df.rowsCount() shouldBe 1
+
+        val child1 = df[Entry::child]
+        child1.kind shouldBe ColumnKind.Group
+
+        val child2 = child1.asColumnGroup()[Child1::child]
+        child2.kind shouldBe ColumnKind.Value
+    }
 }

tests/src/test/kotlin/org/jetbrains/kotlinx/dataframe/samples/api/Create.kt

@@ -331,7 +331,7 @@ class Create : TestBase() {
             Student(Name("Bob", "Marley"), 20, listOf(Score("music", 5)))
         )
 
-        val df = students.toDataFrame(depth = 2)
+        val df = students.toDataFrame(maxDepth = 1)
         // SampleEnd
         df.columnsCount() shouldBe 3
         df.rowsCount() shouldBe 2
@@ -357,7 +357,7 @@ class Create : TestBase() {
             "year of birth" from { 2021 - it.age }
 
             // scan all properties
-            properties(depth = 2) {
+            properties(maxDepth = 1) {
                 exclude(Score::subject) // `subject` property will be skipped from object graph traversal
                 preserve<Name>() // `Name` objects will be stored as-is without transformation into DataFrame
             }