Testing Your Integration: Building Reliable Fixtures for Telegram Registration Checks

When integrating a third-party service like TG Validator, relying solely on live API calls during development can be brittle. You risk hitting concurrency limits or incurring unnecessary costs while testing edge cases. A more robust approach is to implement contract-driven testing using local fixtures that mirror the documented API response envelope.

This guide demonstrates how to build a test suite that simulates various API states—such as successful registrations and undetermined statuses—without triggering live requests.

1. Defining the Contract

TG Validator uses a synchronous response envelope consisting of code, msg, and data. Your application logic should be decoupled from the transport layer so you can swap real API calls for local fixtures during testing.

The Documented Envelope Structure

When a check completes, the API returns a JSON object. Your integration layer should look for the registered boolean inside the data object.

// Example of a successful registration response fixture
{
 "code": 0,
 "msg": "success",
 "data": {
 "service_type": "tg",
 "identifier": "[phone]",
 "registered": true
 }
}

2. Mocking Undetermined States

It is critical to handle scenarios where the service cannot reach a definitive conclusion. According to the API documentation, an undetermined check (such as error 42200) returns a non-zero business code and no completed result object.

Create a Fixture for 42200

// Example of an undetermined status fixture
{
 "code": 42200,
 "msg": "unable to determine status",
 "data": null
}

Your application code should explicitly check for data === null or non-zero code values before attempting to access the registered field. This prevents runtime errors when the service is unable to provide a definitive result.

3. Implementing the Test Suite

By partitioning your logic into a "Service Adapter" and a "Business Logic" layer, you can inject fixtures during your test runs.

Step-by-Step Testing Strategy

1. Create a Mock Adapter: Build an interface that mimics the check_number or check_numbers method signature.
2. Fixture Injection: Use a library like nock (for Node.js) or standard dependency injection to intercept outgoing requests to the TG Validator endpoint.
3. Assert Logic: Verify that your application correctly toggles UI elements or database flags based on the registered boolean, while gracefully handling the null data state for errors.

4. Operational Considerations

• Concurrency: TG Validator documentation outlines specific per-user concurrency and timeout behaviors. Your tests should simulate these by asserting that your code handles 42901 (concurrency limit) errors without crashing.
• Batch Handling: Remember that the synchronous batch endpoint accepts up to 100 identifiers. Ensure your test fixtures include large arrays to verify that your application correctly parses the batch response structure.
• No Internal Fields: When writing your tests, ensure your assertions do not rely on fields like id or transaction_id. These are internal account-history concepts and are not part of the public API response.

Conclusion

By creating local fixtures that mirror the documented code/msg/data envelope, you create a safety net for your integration. This allows you to validate your error-handling logic for undetermined states and concurrency limits locally, ensuring your production code remains resilient when it eventually interacts with the live API.

For the latest details on error codes and concurrency guidance, always consult the official API documentation.

This article was drafted with AI assistance and reviewed before publishing.