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Added examples for DataFrame Spring integration with CSV data sources and improved build.gradle configuration.
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‎build.gradle.kts

Lines changed: 36 additions & 31 deletions
Original file line numberDiff line numberDiff line change
@@ -172,42 +172,47 @@ val modulesUsingJava17 = with(projects) {
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}.map { it.path }
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allprojects {
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if (path in modulesUsingJava11) {
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tasks.withType<KotlinCompile> {
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compilerOptions {
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jvmTarget = JvmTarget.JVM_11
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freeCompilerArgs.add("-Xjdk-release=11")
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when (path) {
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in modulesUsingJava11 -> {
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tasks.withType<KotlinCompile> {
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compilerOptions {
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jvmTarget = JvmTarget.JVM_11
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freeCompilerArgs.add("-Xjdk-release=11")
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}
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}
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}
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tasks.withType<JavaCompile> {
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sourceCompatibility = JavaVersion.VERSION_11.toString()
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targetCompatibility = JavaVersion.VERSION_11.toString()
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options.release.set(11)
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}
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}
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else if (path in modulesUsingJava17) {
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tasks.withType<KotlinCompile> {
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compilerOptions {
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jvmTarget = JvmTarget.JVM_17
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freeCompilerArgs.add("-Xjdk-release=17")
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tasks.withType<JavaCompile> {
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sourceCompatibility = JavaVersion.VERSION_11.toString()
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targetCompatibility = JavaVersion.VERSION_11.toString()
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options.release.set(11)
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}
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}
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tasks.withType<JavaCompile> {
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sourceCompatibility = JavaVersion.VERSION_17.toString()
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targetCompatibility = JavaVersion.VERSION_17.toString()
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options.release.set(17)
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}
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} else {
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tasks.withType<KotlinCompile> {
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compilerOptions {
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jvmTarget = JvmTarget.JVM_1_8
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freeCompilerArgs.add("-Xjdk-release=8")
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in modulesUsingJava17 -> {
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tasks.withType<KotlinCompile> {
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compilerOptions {
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jvmTarget = JvmTarget.JVM_17
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freeCompilerArgs.add("-Xjdk-release=17")
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}
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}
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tasks.withType<JavaCompile> {
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sourceCompatibility = JavaVersion.VERSION_17.toString()
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targetCompatibility = JavaVersion.VERSION_17.toString()
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options.release.set(17)
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}
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}
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tasks.withType<JavaCompile> {
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sourceCompatibility = JavaVersion.VERSION_1_8.toString()
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targetCompatibility = JavaVersion.VERSION_1_8.toString()
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options.release.set(8)
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else -> {
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tasks.withType<KotlinCompile> {
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compilerOptions {
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jvmTarget = JvmTarget.JVM_1_8
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freeCompilerArgs.add("-Xjdk-release=8")
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}
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}
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tasks.withType<JavaCompile> {
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sourceCompatibility = JavaVersion.VERSION_1_8.toString()
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targetCompatibility = JavaVersion.VERSION_1_8.toString()
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options.release.set(8)
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}
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}
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}
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tasks.withType<KotlinCompile> {

‎dataframe-spring/build.gradle.kts

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@@ -41,6 +41,37 @@ dependencies {
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testImplementation(libs.kotestAssertions)
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}
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// Define examples source set
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val examples by sourceSets.creating {
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kotlin.srcDir("examples/src")
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resources.srcDir("examples/resources")
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}
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// Configure examples classpath
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configurations {
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named("examplesImplementation") {
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extendsFrom(configurations.implementation.get())
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}
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named("examplesRuntimeOnly") {
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extendsFrom(configurations.runtimeOnly.get())
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}
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}
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// Add dependencies for examples
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dependencies {
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"examplesImplementation"(project(":dataframe-spring"))
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"examplesImplementation"("org.springframework:spring-context:6.2.7")
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"examplesImplementation"("org.springframework:spring-beans:6.2.7")
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}
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// Task for running examples
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tasks.register<JavaExec>("runExamples") {
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group = "Examples"
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description = "Runs the DataFrame Spring examples"
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classpath = examples.runtimeClasspath
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mainClass.set("org.jetbrains.kotlinx.dataframe.spring.examples.ExampleRunnerKt")
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}
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tasks.test {
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useJUnitPlatform()
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}

‎dataframe-spring/examples/README.md

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# DataFrame Spring Examples
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This directory contains examples demonstrating the usage of the DataFrame Spring integration.
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## Overview
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The examples show how to use the DataFrame Spring module to automatically load data from various sources into DataFrames using annotations.
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## Examples
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1. **CSV Data Source** - Demonstrates loading DataFrames from CSV files using the `@CsvDataSource` annotation
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2. **CSV Data Source with Spring Context** - Shows how to use the `@CsvDataSource` annotation within a Spring application context
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## Running Examples
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To run all examples:
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```bash
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./gradlew :dataframe-spring:runExamples
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```
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## Example Descriptions
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### CSV Data Source
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This example demonstrates how to use the `DataFramePostProcessor` to process a bean with `@CsvDataSource` annotations outside of a Spring context.
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Key features:
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- Loading CSV data with default comma delimiter
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- Loading CSV data with custom delimiter (semicolon)
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- Accessing the loaded data through a typed DataFrame
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### CSV Data Source with Spring Context
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This example demonstrates how to use the `DataFramePostProcessor` within a Spring application context to process beans with `@CsvDataSource` annotations.
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Key features:
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- Registering the `DataFramePostProcessor` in a Spring context
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- Automatically processing beans with `@CsvDataSource` annotations
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- Retrieving processed beans from the Spring context
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## Data Models
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The examples use the following data models:
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- `CustomerRow` - Represents customer data with id, name, email, and age
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- `SalesRow` - Represents sales data with sale ID, customer ID, amount, and date
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## File Structure
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```
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examples/
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├── src/ # Source code for examples
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│ └── org/jetbrains/kotlinx/dataframe/spring/examples/
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│ ├── CsvDataSourceExample.kt # Basic CSV example
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│ ├── CsvDataSourceWithContextExample.kt # Spring context example
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│ ├── DataModels.kt # Data models and utilities
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│ └── ExampleRunner.kt # Main entry point
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└── resources/ # Resource files for examples
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└── data/ # Data files
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├── customers.csv # Customer data (created at runtime)
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└── sales.csv # Sales data (created at runtime)
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```
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## Learning Path
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1. Start with the basic CSV example to understand how the `@CsvDataSource` annotation works
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2. Move on to the Spring context example to see how to integrate with Spring
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## Additional Resources
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For more information, see:
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- [DataFrame Spring README](../README.md)
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- [DataFrame Spring Integration Guide](../INTEGRATION_GUIDE.md)

‎dataframe-spring/examples/resources/data/README.txt

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This directory contains data files used by the DataFrame Spring examples.
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The CSV files (customers.csv and sales.csv) are created dynamically when the examples are run.

‎dataframe-spring/examples/src/org/jetbrains/kotlinx/dataframe/spring/examples/CsvDataSourceExample.kt

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package org.jetbrains.kotlinx.dataframe.spring.examples
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import org.jetbrains.kotlinx.dataframe.spring.DataFramePostProcessor
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/**
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* Example demonstrating basic CSV data source processing.
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*
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* This example shows how to use the DataFramePostProcessor to process
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* a bean with @CsvDataSource annotations outside of a Spring context.
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*/
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fun csvDataSourceExample() {
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// Create sample CSV files in the resources directory
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val resourcesDir = System.getProperty("user.dir") + "\\dataframe-spring\\examples\\resources"
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createSampleData(resourcesDir)
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try {
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println("1. Creating DataFramePostProcessor...")
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val processor = DataFramePostProcessor()
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println("2. Processing @CsvDataSource annotations...")
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val service = ExampleDataService()
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processor.postProcessBeforeInitialization(service, "exampleService")
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println("3. DataFrame loaded successfully!")
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println(" - Rows loaded: ${service.customerData.rowsCount()}")
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println(" - Columns: ${service.customerData.columnNames()}")
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println("4. Running business logic...")
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service.printCustomerCount()
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service.printSalesCount()
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println("✓ @CsvDataSource annotation processing completed successfully!")
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} catch (e: Exception) {
35+
println("✗ Error processing @DataSource annotations: ${e.message}")
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e.printStackTrace()
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} finally {
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// Clean up sample files
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cleanupSampleData(resourcesDir)
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}
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}

‎dataframe-spring/examples/src/org/jetbrains/kotlinx/dataframe/spring/examples/CsvDataSourceWithContextExample.kt

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package org.jetbrains.kotlinx.dataframe.spring.examples
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import org.jetbrains.kotlinx.dataframe.spring.DataFramePostProcessor
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import org.springframework.context.annotation.AnnotationConfigApplicationContext
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/**
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* Example demonstrating CSV data source processing with Spring context.
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*
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* This example shows how to use the DataFramePostProcessor within a Spring
10+
* application context to process beans with @CsvDataSource annotations.
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*/
12+
fun csvDataSourceWithContextExample() {
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// Create sample CSV files in the resources directory
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val resourcesDir = System.getProperty("user.dir") + "\\dataframe-spring\\examples\\resources"
15+
createSampleData(resourcesDir)
16+
17+
try {
18+
println("1. Bootstrapping Spring context...")
19+
val ctx = AnnotationConfigApplicationContext().apply {
20+
register(DataFramePostProcessor::class.java)
21+
register(ExampleDataService::class.java)
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refresh()
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}
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25+
println("2. Getting ExampleDataService bean from context...")
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val dataService = ctx.getBean(ExampleDataService::class.java)
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println("3. DataFrame loaded successfully!")
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println(" - Rows loaded: ${dataService.customerData.rowsCount()}")
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println(" - Columns: ${dataService.customerData.columnNames()}")
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println("4. Running business logic...")
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dataService.printCustomerCount()
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dataService.printSalesCount()
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println("✓ @CsvDataSource annotation processing with Spring context completed successfully!")
37+
38+
} catch (e: Exception) {
39+
println("✗ Error processing @DataSource annotations: ${e.message}")
40+
e.printStackTrace()
41+
} finally {
42+
// Clean up sample files
43+
cleanupSampleData(resourcesDir)
44+
}
45+
}

‎dataframe-spring/examples/src/org/jetbrains/kotlinx/dataframe/spring/examples/DataModels.kt

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package org.jetbrains.kotlinx.dataframe.spring.examples
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import org.jetbrains.kotlinx.dataframe.DataFrame
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import org.jetbrains.kotlinx.dataframe.annotations.DataSchema
5+
import org.jetbrains.kotlinx.dataframe.spring.annotations.CsvDataSource
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import java.io.File
7+
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/**
9+
* Data schema for customer records.
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*
11+
* This interface defines the structure of customer data loaded from CSV files.
12+
*/
13+
@DataSchema
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interface CustomerRow {
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val id: Int
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val name: String
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val email: String
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val age: Int
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}
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/**
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* Data schema for sales records.
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*
24+
* This interface defines the structure of sales data loaded from CSV files.
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*/
26+
@DataSchema
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interface SalesRow {
28+
val saleId: Int
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val customerId: Int
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val amount: Double
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val date: String
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}
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/**
35+
* Example service class that uses DataFrame annotations.
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*
37+
* This class demonstrates how to use the @CsvDataSource annotation
38+
* to automatically load data from CSV files into DataFrames.
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*/
40+
class ExampleDataService {
41+
@CsvDataSource(file = CUSTOMERS_CSV)
42+
lateinit var customerData: DataFrame<CustomerRow>
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@CsvDataSource(file = SALES_CSV, delimiter = ';')
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lateinit var salesData: DataFrame<SalesRow>
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/**
48+
* Prints the total number of customers.
49+
*/
50+
fun printCustomerCount() {
51+
println("Number of customers: ${customerData.rowsCount()}")
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}
53+
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/**
55+
* Prints the total number of sales.
56+
*/
57+
fun printSalesCount() {
58+
println("Number of sales: ${salesData.rowsCount()}")
59+
}
60+
}
61+
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// Constants for file paths
63+
const val CUSTOMERS_CSV = "data\\customers.csv"
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const val SALES_CSV = "data\\sales.csv"
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/**
67+
* Creates sample CSV data files for the examples.
68+
*
69+
* This function creates customer and sales data files in the specified directory.
70+
*
71+
* @param directory The directory where the files will be created
72+
*/
73+
fun createSampleData(directory: String) {
74+
// Create customer data
75+
File("$directory\\$CUSTOMERS_CSV").apply {
76+
parentFile.mkdirs()
77+
writeText("""
78+
id,name,email,age
79+
1,John Doe,[email protected],28
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2,Jane Smith,[email protected],32
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3,Bob Johnson,[email protected],25
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4,Alice Brown,[email protected],30
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""".trimIndent())
84+
}
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// Create sales data with semicolon delimiter
87+
File("$directory\\$SALES_CSV").apply {
88+
parentFile.mkdirs()
89+
writeText("""
90+
sale_id;customer_id;amount;date
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1;1;150.00;2023-01-15
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2;2;200.50;2023-01-16
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3;1;75.25;2023-01-17
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4;3;300.00;2023-01-18
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""".trimIndent())
96+
}
97+
}
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/**
100+
* Cleans up the sample data files.
101+
*
102+
* @param directory The directory where the files were created
103+
*/
104+
fun cleanupSampleData(directory: String) {
105+
File("$directory\\$CUSTOMERS_CSV").delete()
106+
File("$directory\\$SALES_CSV").delete()
107+
}

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