Generate Test Data

Generate similar test data using our AI-powered service, Data Amplifier. You can provide sample data in your request and specify the desired number of rows to be generated, available through both SDKs and APIs.

Usage 🚀

Refer to Setup Guide for installing dependecies for both Java and Python.

JAVA

There are 2 clients available with the Java SDK: SyncClient and AsyncClient

Java Client Code

# for async client 
import org.qyrus.ai_sdk.Clients.AsyncClient;
AsyncClient client = new AsyncClient(<API_TOKEN>, null);

# for sync client
import org.qyrus.ai_sdk.Clients.SyncClient;
SyncClient client = new SyncClient(<API_TOKEN>, null);

Using SyncClient

Here's an example of utilizing Data Amplifier with SyncClient.

Java SyncClient Code

private static void testDataAmplification() {

        Dotenv dotenv = Dotenv.load();
        String QYRUS_AI_SDK_API_TOKEN = dotenv.get("QYRUS_AI_SDK_API_TOKEN");

        // Assuming SyncClient is similar to the provided NovaJira code and has a 'data_amplifier' field and an 'amplify' method
        SyncClient client = new SyncClient(QYRUS_AI_SDK_API_TOKEN, null);

        
        List<Map<String, Object>> example_data = List.of(
            Map.of(
                "column_name", "name",
                "column_description", "name",
                "column_restriction", "no restrictions",
                "column_values", List.of("Sameer Seikh", "Sunil Dutt")
            ),
            Map.of(
                "column_name", "email",
                "column_description", "email",
                "column_restriction", "no restrictions",
                "column_values", List.of("[email protected]","[email protected]")
            )
            
        );

        int data_count = 10;

        long startTime = System.currentTimeMillis();
        int numberOfRequests = 2;

        for (int i = 0; i < numberOfRequests; i++) {

            try {
                // Accessing the data_amplifier's amplify method the same way as it's described in the input
                DataAmplifier.DataAmplifierResponse response = client.data_amplifier.amplify(example_data, data_count);
                System.out.println("Amplification Status: " + response.isStatus());
                System.out.println("Amplification Message: " + response.getMessage());

                // Assuming DataAmplifierResponse contains a 'getData' method to access generated data
                Map<String, List<String>> amplifiedData = response.getData();
                
                // Iterate over the map to display generated data
                for (Map.Entry<String, List<String>> entry : amplifiedData.entrySet()) {
                    System.out.println("Column: " + entry.getKey());
                    System.out.println("Values: " + entry.getValue());
                }
                
            } catch (Exception e) {
                e.printStackTrace();
            }
        }

        long endTime = System.currentTimeMillis();
        System.out.println("Total time for Data Amplification request: " + (endTime - startTime) + " ms");
    }

Using AsyncClient

Here's an example of utilizing Data Amplifier with AsyncClient.

Java AsyncClient Code

private static void asyncTestDataAmplification() {

        Dotenv dotenv = Dotenv.load();
        String QYRUS_AI_SDK_API_TOKEN = dotenv.get("QYRUS_AI_SDK_API_TOKEN");

        // Assuming SyncClient is similar to the provided NovaJira code and has a 'data_amplifier' field and an 'amplify' method
        AsyncClient client = new AsyncClient(QYRUS_AI_SDK_API_TOKEN, null);
        int numberOfRequests = 2;
        List<Map<String, Object>> example_data = List.of(
            Map.of(
                "column_name", "name",
                "column_description", "name",
                "column_restriction", "no restrictions",
                "column_values", List.of("Sameer Seikh", "Sunil Dutt")
            ),
            Map.of(
                "column_name", "email",
                "column_description", "email",
                "column_restriction", "no restrictions",
                "column_values", List.of("[email protected]","[email protected]")
            )
            
        );

        int data_count = 10;

        long startTime = System.currentTimeMillis();

        List<CompletableFuture<AsyncDataAmplifier.DataAmplifierResponse>> futures = new ArrayList<>();

        for (int i = 0; i < numberOfRequests; i++) {

        
            // Accessing the data_amplifier's amplify method the same way as it's described in the input
            CompletableFuture<AsyncDataAmplifier.DataAmplifierResponse> responseFuture = client.data_amplifier.amplify(example_data, data_count);

            responseFuture.thenAccept(response -> {
            if (response.isStatus()) {
                System.out.println("Amplification Status: " + response.isStatus());
                System.out.println("Amplification Message: " + response.getMessage());

                // Assuming DataAmplifierResponse contains a 'getData' method to access generated data
                Map<String, List<String>> amplifiedData = response.getData();
                
                // Iterate over the map to display generated data
                for (Map.Entry<String, List<String>> entry : amplifiedData.entrySet()) {
                    System.out.println("Column: " + entry.getKey());
                    System.out.println("Values: " + entry.getValue());
                }
            
        }
            else {
                System.out.println("Creation failed with message: " + response.getMessage());
            }
        }).exceptionally(ex -> {
            System.out.println("An error occurred: " + ex.getMessage());
            ex.printStackTrace();
            return null;
        });

        // // Keep your program running until all futures are resolved
        // responseFuture.join(); // Block and wait for the future to complete
        futures.add(responseFuture);
        }
        CompletableFuture.allOf(futures.toArray(new CompletableFuture[0])).join();

        long endTime = System.currentTimeMillis();
        System.out.println("Asynchronous total time for Data Amplification" + numberOfRequests + " requests: " + (endTime - startTime) + " ms");
    }

---

PYTHON

There are two clients available with the Python SDK: SyncQyrusAI and AsyncQyrusAI.

Python Client Code

# for sync client
from qyrusai import SyncQyrusAI
client = SyncQyrusAI(api_key=QYRUS_API_TOKEN)

# for async client
from qyrusai import AsyncQyrusAI
client = AsyncQyrusAI(api_key=QYRUS_API_TOKEN)

Using SyncQyrusAI

Here's an example of utilizing Data Amplifier with SyncQyrusAI.

Python SyncQyrusAI Code

import os
import json
from qyrusai import SyncQyrusAI

QYRUS_API_TOKEN = os.environ.get("QYRUS_API_TOKEN")

client = SyncQyrusAI(api_key=QYRUS_API_TOKEN)
data = [
    {
        "column_name": "first name",
        "column_description": "first name",
        "column_restriction": "no restrictions",
        "column_values": [
            "john",
            "jane",
            "Michael",
            "Emily",
            "Shahwar"
        ]
    },
    {
        "column_name": "last name",
        "column_description": "last name",
        "column_restriction": "no restrictions",
        "column_values": [
            "doe",
            "doe",
            "Smith",
            "Johnson",
            "Alam"
        ]
    },
    {
        "column_name": "username",
        "column_description": "username",
        "column_restriction": "no restrictions",
        "column_values": [
            "johndoe",
            "jdoe",
            "msmith",
            "ejohnson",
            "Naqvi"
        ]
    }
]
data_count = 3
op = client.data_amplifier.amplify(data, data_count)
print(json.dumps(op.model_dump(), indent=4))
data = op.get("data")
print(data)

Using AsyncQyrusAI

Here's an example of utilizing Data Amplifier with AsyncQyrusAI.

Python AsyncQyrusAI Code

import os
import json
import asyncio
from qyrusai import AsyncQyrusAI

QYRUS_API_TOKEN = os.environ.get("QYRUS_API_TOKEN")

client = AsyncQyrusAI(api_key=QYRUS_API_TOKEN)

data = [
    {
        "column_name": "first name",
        "column_description": "first name",
        "column_restriction": "no restrictions",
        "column_values": [
            "john",
            "jane",
            "Michael",
            "Emily",
            "Shahwar"
        ]
    },
    {
        "column_name": "last name",
        "column_description": "last name",
        "column_restriction": "no restrictions",
        "column_values": [
            "doe",
            "doe",
            "Smith",
            "Johnson",
            "Alam"
        ]
    },
    {
        "column_name": "username",
        "column_description": "username",
        "column_restriction": "no restrictions",
        "column_values": [
            "johndoe",
            "jdoe",
            "msmith",
            "ejohnson",
            "Naqvi"
        ]
    }
]
data_count = 3
async def main():
    op = await client.data_amplifier.amplify(data, data_count)
    print(json.dumps(op.model_dump(), indent=4))
    data = op.get("data")
    print(data)

# Run the async function
asyncio.run(main())

---

Rest APIs

• Endpoint: POST {{GATEWAY_URL}}/synthetic-data-generator-sdk/v1/api/datagen

• Headers:

  • Authorization: [Your Authorization Token]

  • Custom: [Your Custom Header Value]

• Request Body:

• Response: