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DevynBenson lesson_09 submission
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‎lesson_09/types/types_app/README.md‎

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# Types App - Data Types Exercise
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This application demonstrates data type identification and sample data generation for Lesson 09.
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## Overview
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The Types App provides two main functionalities:
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1. Generate sample data files for individual providers
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2. Bulk generate sample data files for all registered `DataProvider` implementations
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## Prerequisites
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- Java 17 or higher
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- Gradle (included via Gradle Wrapper)
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## Running the Application
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### Standard Mode - Single Provider
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Generate a sample data file for a specific provider:
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```bash
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cd lesson_09/types
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./gradlew bootRun --args="yourprovidername"
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```
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This will create a JSON file in `src/main/resources/data/yourprovidername.json` with 10 rows of sample data.
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**Example:**
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```bash
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./gradlew bootRun --args="devynbenson"
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```
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### Stretch Assignment - Bulk Generator Mode
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Generate sample data files for **all** registered `DataProvider` implementations:
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```bash
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cd lesson_09/types
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./gradlew bootRun --args="-bulk"
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```
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This bulk mode will:
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- Automatically discover all registered `DataProvider` implementations
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- Generate a unique JSON file for each provider
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- Create files in `src/main/resources/data/` directory
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- Each file contains 10 rows of sample data with appropriate data types
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**What happens in bulk mode:**
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1. The app scans for all `DataProvider` beans registered in the Spring context
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2. For each provider, it generates sample data based on the provider's column type definitions
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3. Creates individual JSON files named after each provider (e.g., `devynbenson.json`, `anthonymays.json`, etc.)
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## Output Format
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Generated files are in JSON format with the following structure:
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```json
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[
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{
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"column1": "sample_value_1",
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"column2": "sample_value_2",
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"column3": "sample_value_3",
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...
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},
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// ... 9 more rows
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]
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```
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## Data Types Supported
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The bulk generator supports the following Java data types:
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- `Integer` - Whole numbers
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- `Double` - Decimal numbers
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- `String` - Text values
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- `Boolean` - True/false values
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- `Short` - Small integers
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- `Long` - Large integers
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- `Float` - Single-precision decimals
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## Implementation Details
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### Bulk Generator Class
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The bulk functionality is implemented in `DevynBensonBulkGenerator.java`, which:
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- Uses Spring's dependency injection to access all `DataProvider` beans
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- Maps each provider's column types to appropriate value generators
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- Generates realistic sample data for each column type
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- Outputs properly formatted JSON files
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### Usage in Main Application
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The main `Lesson9.java` class detects the `-bulk` flag and switches to bulk generation mode:
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```java
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if("-bulk".equals(providerName)) {
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var path = getDataPath();
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var fileGenerator = new DevynBensonBulkGenerator();
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fileGenerator.createTestFileForEveryProvider(path, dataProviders);
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return;
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}
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```
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## Testing and Validation
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After running the application, validate your implementation:
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```bash
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# Format code
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./gradlew spotlessApply
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# Run tests
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./gradlew check
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```
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## File Locations
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- **Generated Data Files:** `src/main/resources/data/`
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- **DataProvider Implementations:** `src/main/java/com/codedifferently/lesson9/dataprovider/`
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- **Bulk Generator:** `src/main/java/com/codedifferently/lesson9/generator/DevynBensonBulkGenerator.java`
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## Example Workflow
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1. Create your `DataProvider` implementation
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2. Run bulk generator to see sample data for all providers:
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```bash
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./gradlew bootRun --args="-bulk"
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```
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3. Examine the generated JSON file for your provider
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4. Verify the data types match your expectations
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5. Run tests to validate implementation

‎lesson_09/types/types_app/src/main/java/com/codedifferently/lesson9/Lesson9.java‎

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package com.codedifferently.lesson9;
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import com.codedifferently.lesson9.generator.SampleFileGenerator;
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import com.codedifferently.lesson9.generator.DevynBensonBulkGenerator;
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import java.io.File;
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import java.nio.file.Paths;
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import org.springframework.boot.CommandLineRunner;
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import org.springframework.boot.SpringApplication;
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import org.springframework.boot.autoconfigure.SpringBootApplication;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.beans.factory.annotation.Autowired;
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@Configuration
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@SpringBootApplication(scanBasePackages = "com.codedifferently")
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public class Lesson9 implements CommandLineRunner {
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@Autowired
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private List<DataProvider> dataProviders;
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public static void main(String[] args) {
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var application = new SpringApplication(Lesson9.class);
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application.run(args);
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throw new IllegalArgumentException("Provider name is required");
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}
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if("-bulk".equals(providerName)) {
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var path = getDataPath();
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var fileGenerator = new DevynBensonBulkGenerator();
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fileGenerator.createTestFileForEveryProvider(path, dataProviders);
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return;
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}
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String path = getDataPath();
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var fileGenerator = new SampleFileGenerator();
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fileGenerator.createTestFile(path, providerName);

‎lesson_09/types/types_app/src/main/java/com/codedifferently/lesson9/dataprovider/DevynBensonProvider.java‎

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package com.codedifferently.lesson9.dataprovider;
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import java.util.Map;
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import org.springframework.stereotype.Service;
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@Service
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public class DevynBensonProvider extends DataProvider {
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public String getProviderName() {
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return "devynbenson";
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}
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public Map<String, Class> getColumnTypeByName() {
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return Map.of(
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"column1", Boolean.class, // true/false values
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"column2", Float.class, // Scientific notation floats like 1.3605703E38
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"column3", String.class, // Text strings like "vqjy6zgi32lr"
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"column4", Long.class, // Very large integers like 649023162885324032
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"column5", Short.class, // Small integers like 4581 (fits in Short range)
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"column6", Integer.class, // Medium integers like 383252171
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"column7", Double.class); // Very large scientific notation like 1.7759E307
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}
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}

‎lesson_09/types/types_app/src/main/java/com/codedifferently/lesson9/generator/DevynBensonBulkGenerator.java‎

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package com.codedifferently.lesson9.generator;
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import com.codedifferently.lesson9.dataprovider.DataProvider;
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import java.util.List;
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import org.springframework.beans.factory.annotation.Autowired;
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import com.codedifferently.lesson9.generator.Generators.*;
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import com.google.gson.GsonBuilder;
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import java.io.File;
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import java.io.FileWriter;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.LinkedHashMap;
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import java.util.List;
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import java.util.Map;
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/** A class to generate a sample file with random data. */
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public class DevynBensonBulkGenerator {
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@Autowired
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private List<DataProvider> dataProviders;
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private static final ValueGenerator[] GENERATORS = {
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new IntValueGenerator(),
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new StringValueGenerator(),
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new DoubleValueGenerator(),
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new ShortValueGenerator(),
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new LongValueGenerator(),
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new FloatValueGenerator(),
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new BooleanValueGenerator()
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};
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/**
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* Create a test file with sample data.
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*
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* @param path the path to the directory where the file will be created
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* @param providerName the name of the provider
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*/
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public void createTestFileForEveryProvider(String path, List<DataProvider> dataProviders) {
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for (var dataProvider : dataProviders) {
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var generators = getShuffledGenerators();
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ArrayList<Map<String, String>> rows = createSampleData(generators);
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saveToJsonFile(path, dataProvider.getProviderName(), rows);
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}
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}
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// Mapping of classes to value generators
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private static final Map<Class<?>, ValueGenerator> TYPE_TO_GENERATOR =
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Map.of(
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Integer.class, new IntValueGenerator(),
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Short.class, new ShortValueGenerator(),
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Long.class, new LongValueGenerator(),
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Float.class, new FloatValueGenerator(),
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Boolean.class, new BooleanValueGenerator(),
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String.class, new StringValueGenerator(),
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Double.class, new DoubleValueGenerator());
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/**
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* Creates a JSON provider file with generated sample data.
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*
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* @param path the file path where the provider file will be written
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* @param providerName the name of the provider
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* @param provider the {DataProvider} that defines columns
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* @throws IllegalArgumentException if no generator is found for a column type
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*/
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public void createProviderFile(String path, String providerName, DataProvider provider) {
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var generators = getGenerators(provider);
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ArrayList<Map<String, String>> rows = createSampleData(generators);
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// Writes the generated rows to a JSON file.
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saveToJsonFile(path, providerName, rows);
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}
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private List<ValueGenerator> getGenerators(DataProvider provider) {
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Map<String, Class> columnTypes = provider.getColumnTypeByName();
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ArrayList<ValueGenerator> generators = new ArrayList<>();
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for (int i = 1; i <= columnTypes.size(); i++) {
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String column = "column" + i;
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Class<?> type = columnTypes.get(column);
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// Look up the appropriate generator for this column type.
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ValueGenerator generator = TYPE_TO_GENERATOR.get(type);
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if (generator == null) {
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throw new IllegalArgumentException("No generator found for type: " + type);
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}
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generators.add(generator);
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}
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return generators;
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}
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private List<ValueGenerator> getdGenerators(DataProvider provider) {
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var generators = Arrays.asList(GENERATORS);
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Collections.shuffle(generators);
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return generators;
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}
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private ArrayList<Map<String, String>> createSampleData(List<ValueGenerator> generators) {
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var rows = new ArrayList<Map<String, String>>();
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for (var i = 0; i < 10; ++i) {
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Map<String, String> row = createRow(generators);
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rows.add(createRow(generators));
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}
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return rows;
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}
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private Map<String, String> createRow(List<ValueGenerator> generators) {
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var row = new LinkedHashMap<String, String>();
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for (int i = 0; i < GENERATORS.length; ++i) {
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var columnIndex = i + 1;
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row.put("column" + columnIndex, GENERATORS[i].generateValue());
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}
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return row;
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}
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private void saveToJsonFile(
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String path, String providerName, ArrayList<Map<String, String>> rows) {
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var file = new File(path + File.separator + providerName + ".json");
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file.getParentFile().mkdirs();
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var gson = new GsonBuilder().setPrettyPrinting().create();
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try (var writer = new FileWriter(file, false)) {
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writer.write(gson.toJson(rows));
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} catch (IOException e) {
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e.printStackTrace();
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}
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}
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}

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