Update generated sources with recent changes

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/annotations/Plugin.kt

@@ -8,12 +8,12 @@ public annotation class HasSchema(val schemaArg: Int)
  * Needed because some function calls only serve as a part of overall compile time DataSchema evaluation
  * There's no need to update return type of such calls
  */
-internal annotation class Interpretable(val interpreter: String)
+public annotation class Interpretable(val interpreter: String)
 
 /**
  * Compiler plugin will replace return type of calls to the annotated function
  */
-internal annotation class Refine
+public annotation class Refine
 
 internal annotation class OptInRefine
 

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/Nulls.kt

@@ -200,6 +200,7 @@ private interface SetFillNullsOperationArg
  *
  * @param [columns] The [Columns Selector][org.jetbrains.kotlinx.dataframe.ColumnsSelector] used to select the columns of this [DataFrame][org.jetbrains.kotlinx.dataframe.DataFrame] to update.
  */
+@Interpretable("FillNulls0")
 public fun <T, C> DataFrame<T>.fillNulls(columns: ColumnsSelector<T, C?>): Update<T, C?> =
     update(columns).where { it == null }
 

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/constructors.kt

@@ -9,6 +9,8 @@ import org.jetbrains.kotlinx.dataframe.DataColumn
 import org.jetbrains.kotlinx.dataframe.DataFrame
 import org.jetbrains.kotlinx.dataframe.DataRow
 import org.jetbrains.kotlinx.dataframe.RowExpression
+import org.jetbrains.kotlinx.dataframe.annotations.Interpretable
+import org.jetbrains.kotlinx.dataframe.annotations.Refine
 import org.jetbrains.kotlinx.dataframe.columns.ColumnAccessor
 import org.jetbrains.kotlinx.dataframe.columns.ColumnPath
 import org.jetbrains.kotlinx.dataframe.columns.ColumnReference
@@ -18,6 +20,7 @@ import org.jetbrains.kotlinx.dataframe.exceptions.UnequalColumnSizesException
 import org.jetbrains.kotlinx.dataframe.impl.ColumnNameGenerator
 import org.jetbrains.kotlinx.dataframe.impl.DataFrameImpl
 import org.jetbrains.kotlinx.dataframe.impl.UNNAMED_COLUMN_PREFIX
+import org.jetbrains.kotlinx.dataframe.impl.api.withValuesImpl
 import org.jetbrains.kotlinx.dataframe.impl.asList
 import org.jetbrains.kotlinx.dataframe.impl.columnName
 import org.jetbrains.kotlinx.dataframe.impl.columns.ColumnAccessorImpl
@@ -268,6 +271,7 @@ public fun dataFrameOf(vararg header: ColumnReference<*>): DataFrameBuilder = Da
 
 public fun dataFrameOf(vararg columns: AnyBaseCol): AnyFrame = dataFrameOf(columns.asIterable())
 
+@Interpretable("DataFrameOf0")
 public fun dataFrameOf(vararg header: String): DataFrameBuilder = dataFrameOf(header.toList())
 
 public inline fun <reified C> dataFrameOf(vararg header: String, fill: (String) -> Iterable<C>): AnyFrame =
@@ -302,27 +306,15 @@ public class DataFrameBuilder(private val header: List<String>) {
         }.toDataFrame()
     }
 
+    @Refine
+    @Interpretable("DataFrameBuilderInvoke0")
     public operator fun invoke(vararg values: Any?): AnyFrame = withValues(values.asIterable())
 
     @JvmName("invoke1")
-    internal fun withValues(values: Iterable<Any?>): AnyFrame {
-        val list = values.asList()
-
-        val ncol = header.size
-
-        require(header.isNotEmpty() && list.size.rem(ncol) == 0) {
-            "Number of values ${list.size} is not divisible by number of columns $ncol"
-        }
-
-        val nrow = list.size / ncol
-
-        return (0 until ncol).map { col ->
-            val colValues = (0 until nrow).map { row ->
-                list[row * ncol + col]
-            }
-            DataColumn.createWithTypeInference(header[col], colValues)
+    internal fun withValues(values: Iterable<Any?>): AnyFrame =
+        withValuesImpl(header, values.asList()).map { (name, values) ->
+            DataColumn.createWithTypeInference(name, values)
         }.toDataFrame()
-    }
 
     public operator fun invoke(args: Sequence<Any?>): AnyFrame = invoke(*args.toList().toTypedArray())
 

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/convert.kt

@@ -94,6 +94,7 @@ public inline fun <T, C, reified R> Convert<T, C?>.notNull(
 public class Convert<T, out C>(internal val df: DataFrame<T>, internal val columns: ColumnsSelector<T, C>) {
     public fun <R> cast(): Convert<T, R> = Convert(df, columns as ColumnsSelector<T, R>)
 
+    @Refine
     @Interpretable("To0")
     public inline fun <reified D> to(): DataFrame<T> = to(typeOf<D>())
 

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/flatten.kt

@@ -2,16 +2,22 @@ package org.jetbrains.kotlinx.dataframe.api
 
 import org.jetbrains.kotlinx.dataframe.ColumnsSelector
 import org.jetbrains.kotlinx.dataframe.DataFrame
+import org.jetbrains.kotlinx.dataframe.annotations.Interpretable
+import org.jetbrains.kotlinx.dataframe.annotations.Refine
 import org.jetbrains.kotlinx.dataframe.columns.ColumnReference
 import org.jetbrains.kotlinx.dataframe.columns.toColumnSet
 import org.jetbrains.kotlinx.dataframe.impl.api.flattenImpl
 import kotlin.reflect.KProperty
 
 // region DataFrame
 
+@Refine
+@Interpretable("FlattenDefault")
 public fun <T> DataFrame<T>.flatten(keepParentNameForColumns: Boolean = false, separator: String = "."): DataFrame<T> =
     flatten(keepParentNameForColumns, separator) { all() }
 
+@Refine
+@Interpretable("Flatten0")
 public fun <T, C> DataFrame<T>.flatten(
     keepParentNameForColumns: Boolean = false,
     separator: String = ".",

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/toDataFrame.kt

@@ -202,6 +202,13 @@ public abstract class CreateDataFrameDsl<T> : TraversePropertiesDsl {
     public abstract operator fun String.invoke(builder: CreateDataFrameDsl<T>.() -> Unit)
 }
 
+@Refine
+@Interpretable("ToDataFrameColumn")
+public inline fun <reified T> Iterable<T>.toDataFrame(columnName: String): DataFrame<*> =
+    toDataFrame {
+        columnName from { it }
+    }
+
 // endregion
 
 // region toDataFrame overloads for built-in types
@@ -304,6 +311,8 @@ public interface ValueProperty<T> {
     public val value: T
 }
 
+// endregion
+
 // region Create DataFrame from Map
 
 public fun Map<String, Iterable<Any?>>.toDataFrame(): AnyFrame =

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/update.kt

@@ -8,6 +8,8 @@ import org.jetbrains.kotlinx.dataframe.DataFrameExpression
 import org.jetbrains.kotlinx.dataframe.DataRow
 import org.jetbrains.kotlinx.dataframe.RowColumnExpression
 import org.jetbrains.kotlinx.dataframe.RowValueFilter
+import org.jetbrains.kotlinx.dataframe.annotations.Interpretable
+import org.jetbrains.kotlinx.dataframe.annotations.Refine
 import org.jetbrains.kotlinx.dataframe.api.Update.Grammar
 import org.jetbrains.kotlinx.dataframe.columns.ColumnGroup
 import org.jetbrains.kotlinx.dataframe.columns.ColumnReference
@@ -458,7 +460,9 @@ public typealias UpdateExpression<T, C, R> = AddDataRow<T>.(C) -> R
  * - [Update per row col][org.jetbrains.kotlinx.dataframe.api.Update.perRowCol] to provide a new value for every selected cell giving its row and column.
  * @param [expression] The [Row Value Expression][org.jetbrains.kotlinx.dataframe.documentation.ExpressionsGivenRow.RowValueExpression.WithExample] to update the rows with.
  */
-public fun <T, C> Update<T, C>.with(expression: UpdateExpression<T, C, C?>): DataFrame<T> =
+@Refine
+@Interpretable("UpdateWith0")
+public fun <T, C, R : C?> Update<T, C>.with(expression: UpdateExpression<T, C, R>): DataFrame<T> =
     updateImpl { row, _, value ->
         expression(row, value)
     }

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/impl/TypeUtils.kt

@@ -436,6 +436,8 @@ internal fun guessValueType(values: Sequence<Any?>, upperBound: KType? = null, l
                 collectionClasses.add(it.javaClass.kotlin)
             }
 
+            is Function<*> -> classes.add(Function::class)
+
             else -> classes.add(it.javaClass.kotlin)
         }
     }

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/impl/api/constructors.kt

@@ -0,0 +1,18 @@
+package org.jetbrains.kotlinx.dataframe.impl.api
+
+internal fun <T> withValuesImpl(header: List<String>, values: List<T>): List<Pair<String, List<T>>> {
+    val ncol = header.size
+
+    require(header.isNotEmpty() && values.size.rem(ncol) == 0) {
+        "Number of values ${values.size} is not divisible by number of columns $ncol"
+    }
+
+    val nrow = values.size / ncol
+
+    return (0 until ncol).map { col ->
+        val colValues = (0 until nrow).map { row ->
+            values[row * ncol + col]
+        }
+        header[col] to colValues
+    }
+}

core/generated-sources/src/test/kotlin/org/jetbrains/kotlinx/dataframe/api/toDataFrame.kt

@@ -11,6 +11,7 @@ import org.jetbrains.kotlinx.dataframe.kind
 import org.jetbrains.kotlinx.dataframe.type
 import org.junit.Ignore
 import org.junit.Test
+import java.io.File
 import kotlin.reflect.KProperty
 import kotlin.reflect.typeOf
 
@@ -452,4 +453,11 @@ class CreateDataFrameTests {
             df.participants[0].city
         }
     }
+
+    @Test
+    fun toDataFrameColumn() {
+        val files = listOf(File("data.csv"))
+        val df = files.toDataFrame(columnName = "files")
+        df["files"][0] shouldBe File("data.csv")
+    }
 }

core/generated-sources/src/test/kotlin/org/jetbrains/kotlinx/dataframe/samples/api/Create.kt

@@ -31,6 +31,7 @@ import org.jetbrains.kotlinx.dataframe.explainer.TransformDataFrameExpressions
 import org.jetbrains.kotlinx.dataframe.kind
 import org.jetbrains.kotlinx.dataframe.type
 import org.junit.Test
+import java.io.File
 import kotlin.reflect.typeOf
 
 class Create : TestBase() {
@@ -456,4 +457,13 @@ class Create : TestBase() {
         peek(dataFrameOf(col), dataFrameOf(col))
         // SampleEnd
     }
+
+    @Test
+    @TransformDataFrameExpressions
+    fun toDataFrameColumn() {
+        // SampleStart
+        val files = listOf(File("data.csv"), File("data1.csv"))
+        val df = files.toDataFrame(columnName = "data")
+        // SampleEnd
+    }
 }

core/generated-sources/src/test/kotlin/org/jetbrains/kotlinx/dataframe/testSets/person/DataFrameTests.kt

@@ -217,6 +217,13 @@ class DataFrameTests : BaseTest() {
         dataFrameOf("name", "age", "city", "weight")(c1, c2, c3, c4) shouldBe df
     }
 
+    @Test
+    fun `guess column type for type without classifier`() {
+        val df = dataFrameOf("a", "b")({ 1 }, 2)
+        df["a"].type() shouldBe typeOf<Function<*>>()
+        (df["a"][0] as () -> Int).invoke() shouldBe 1
+    }
+
     @Test
     fun `create with columnOf`() {
         val col = columnOf("Alice", "Bob")