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Partially inline AnyFrame typealias in return type position #888

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Merged
merged 1 commit into from
Oct 2, 2024
Merged

Partially inline AnyFrame typealias in return type position #888

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52 changes: 26 additions & 26 deletions core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/constructors.kt
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Original file line number Diff line number Diff line change
Expand Up @@ -261,31 +261,31 @@ public inline fun <reified T> column(values: Iterable<T>): DataColumn<T> =
* @throws [UnequalColumnSizesException] if column size are not equal
* @param columns columns for [DataFrame]
*/
public fun dataFrameOf(columns: Iterable<AnyBaseCol>): AnyFrame {
public fun dataFrameOf(columns: Iterable<AnyBaseCol>): DataFrame<*> {
val cols = columns.map { it.unbox() }
val nrow = if (cols.isEmpty()) 0 else cols[0].size
return DataFrameImpl<Unit>(cols, nrow)
}

public fun dataFrameOf(vararg header: ColumnReference<*>): DataFrameBuilder = DataFrameBuilder(header.map { it.name() })

public fun dataFrameOf(vararg columns: AnyBaseCol): AnyFrame = dataFrameOf(columns.asIterable())
public fun dataFrameOf(vararg columns: AnyBaseCol): DataFrame<*> = 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 =
public inline fun <reified C> dataFrameOf(vararg header: String, fill: (String) -> Iterable<C>): DataFrame<*> =
dataFrameOf(header.asIterable(), fill)

public fun dataFrameOf(header: Iterable<String>): DataFrameBuilder = DataFrameBuilder(header.asList())

public fun dataFrameOf(vararg columns: Pair<String, List<Any?>>): AnyFrame =
public fun dataFrameOf(vararg columns: Pair<String, List<Any?>>): DataFrame<*> =
columns.map { it.second.toColumn(it.first, Infer.Type) }.toDataFrame()

public fun dataFrameOf(header: Iterable<String>, values: Iterable<Any?>): AnyFrame =
public fun dataFrameOf(header: Iterable<String>, values: Iterable<Any?>): DataFrame<*> =
dataFrameOf(header).withValues(values)

public inline fun <T, reified C> dataFrameOf(header: Iterable<T>, fill: (T) -> Iterable<C>): AnyFrame =
public inline fun <T, reified C> dataFrameOf(header: Iterable<T>, fill: (T) -> Iterable<C>): DataFrame<*> =
header.map { value ->
fill(value).asList().let {
DataColumn.create(value.toString(), it)
Expand All @@ -296,9 +296,9 @@ public fun dataFrameOf(header: CharProgression): DataFrameBuilder = dataFrameOf(

public class DataFrameBuilder(private val header: List<String>) {

public operator fun invoke(vararg columns: AnyCol): AnyFrame = invoke(columns.asIterable())
public operator fun invoke(vararg columns: AnyCol): DataFrame<*> = invoke(columns.asIterable())

public operator fun invoke(columns: Iterable<AnyCol>): AnyFrame {
public operator fun invoke(columns: Iterable<AnyCol>): DataFrame<*> {
val cols = columns.asList()
require(cols.size == header.size) { "Number of columns differs from number of column names" }
return cols.mapIndexed { i, col ->
Expand All @@ -308,19 +308,19 @@ public class DataFrameBuilder(private val header: List<String>) {

@Refine
@Interpretable("DataFrameBuilderInvoke0")
public operator fun invoke(vararg values: Any?): AnyFrame = withValues(values.asIterable())
public operator fun invoke(vararg values: Any?): DataFrame<*> = withValues(values.asIterable())

@JvmName("invoke1")
internal fun withValues(values: Iterable<Any?>): AnyFrame =
internal fun withValues(values: Iterable<Any?>): DataFrame<*> =
withValuesImpl(header, values.asList()).map { (name, values) ->
DataColumn.createWithTypeInference(name, values)
}.toDataFrame()

public operator fun invoke(args: Sequence<Any?>): AnyFrame = invoke(*args.toList().toTypedArray())
public operator fun invoke(args: Sequence<Any?>): DataFrame<*> = invoke(*args.toList().toTypedArray())

public fun withColumns(columnBuilder: (String) -> AnyCol): AnyFrame = header.map(columnBuilder).toDataFrame()
public fun withColumns(columnBuilder: (String) -> AnyCol): DataFrame<*> = header.map(columnBuilder).toDataFrame()

public inline operator fun <reified T> invoke(crossinline valuesBuilder: (String) -> Iterable<T>): AnyFrame =
public inline operator fun <reified T> invoke(crossinline valuesBuilder: (String) -> Iterable<T>): DataFrame<*> =
withColumns { name ->
valuesBuilder(name).let {
DataColumn.create(
Expand All @@ -330,7 +330,7 @@ public class DataFrameBuilder(private val header: List<String>) {
}
}

public inline fun <reified C> fill(nrow: Int, value: C): AnyFrame =
public inline fun <reified C> fill(nrow: Int, value: C): DataFrame<*> =
withColumns { name ->
DataColumn.createValueColumn(
name = name,
Expand All @@ -339,17 +339,17 @@ public class DataFrameBuilder(private val header: List<String>) {
)
}

public inline fun <reified C> nulls(nrow: Int): AnyFrame = fill<C?>(nrow, null)
public inline fun <reified C> nulls(nrow: Int): DataFrame<*> = fill<C?>(nrow, null)

public inline fun <reified C> fillIndexed(nrow: Int, crossinline init: (Int, String) -> C): AnyFrame =
public inline fun <reified C> fillIndexed(nrow: Int, crossinline init: (Int, String) -> C): DataFrame<*> =
withColumns { name ->
DataColumn.create(
name,
List(nrow) { init(it, name) },
)
}

public inline fun <reified C> fill(nrow: Int, crossinline init: (Int) -> C): AnyFrame =
public inline fun <reified C> fill(nrow: Int, crossinline init: (Int) -> C): DataFrame<*> =
withColumns { name ->
DataColumn.create(
name = name,
Expand All @@ -366,23 +366,23 @@ public class DataFrameBuilder(private val header: List<String>) {
)
}

public fun randomInt(nrow: Int): AnyFrame = fillNotNull(nrow) { Random.nextInt() }
public fun randomInt(nrow: Int): DataFrame<*> = fillNotNull(nrow) { Random.nextInt() }

public fun randomInt(nrow: Int, range: IntRange): AnyFrame = fillNotNull(nrow) { Random.nextInt(range) }
public fun randomInt(nrow: Int, range: IntRange): DataFrame<*> = fillNotNull(nrow) { Random.nextInt(range) }

public fun randomDouble(nrow: Int): AnyFrame = fillNotNull(nrow) { Random.nextDouble() }
public fun randomDouble(nrow: Int): DataFrame<*> = fillNotNull(nrow) { Random.nextDouble() }

public fun randomDouble(nrow: Int, range: ClosedRange<Double>): AnyFrame =
public fun randomDouble(nrow: Int, range: ClosedRange<Double>): DataFrame<*> =
fillNotNull(nrow) { Random.nextDouble(range.start, range.endInclusive) }

public fun randomFloat(nrow: Int): AnyFrame = fillNotNull(nrow) { Random.nextFloat() }
public fun randomFloat(nrow: Int): DataFrame<*> = fillNotNull(nrow) { Random.nextFloat() }

public fun randomLong(nrow: Int): AnyFrame = fillNotNull(nrow) { Random.nextLong() }
public fun randomLong(nrow: Int): DataFrame<*> = fillNotNull(nrow) { Random.nextLong() }

public fun randomLong(nrow: Int, range: ClosedRange<Long>): AnyFrame =
public fun randomLong(nrow: Int, range: ClosedRange<Long>): DataFrame<*> =
fillNotNull(nrow) { Random.nextLong(range.start, range.endInclusive) }

public fun randomBoolean(nrow: Int): AnyFrame = fillNotNull(nrow) { Random.nextBoolean() }
public fun randomBoolean(nrow: Int): DataFrame<*> = fillNotNull(nrow) { Random.nextBoolean() }
}

/**
Expand All @@ -408,7 +408,7 @@ public class DynamicDataFrameBuilder {
return uniqueName
}

public fun toDataFrame(): AnyFrame = dataFrameOf(cols)
public fun toDataFrame(): DataFrame<*> = dataFrameOf(cols)
}

/**
Expand Down
2 changes: 1 addition & 1 deletion plugins/expressions-converter/testData/box/df.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,7 @@ package org {

public final class Wrapper {
public constructor Wrapper()
public final val df: org.jetbrains.kotlinx.dataframe.AnyFrame /* = org.jetbrains.kotlinx.dataframe.DataFrame<*> */
public final val df: org.jetbrains.kotlinx.dataframe.DataFrame<*>
public final val typed: org.jetbrains.kotlinx.dataframe.DataFrame<org.jetbrains.kotlinx.dataframe.explainer.Person>
public open override /*1*/ /*fake_override*/ fun equals(/*0*/ other: kotlin.Any?): kotlin.Boolean
@org.jetbrains.kotlinx.dataframe.explainer.TransformDataFrameExpressions public final fun ff(): kotlin.Unit
Expand Down
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