When building automated systems that handle high-volume data, such as verifying Viber account registration for large lists of phone numbers, the architecture of your integration is just as important as the data itself. Because these operations are inherently asynchronous, treating them as a simple request-response cycle is a common pitfall that leads to incomplete data processing.
The Asynchronous Lifecycle
The Viber Bulk Number Checker API follows an asynchronous batch workflow. When you submit a file, the system does not return the results immediately. Instead, it provides a task_id. Your application must transition through specific states—pending, processing, and exported—before the result file is ready for consumption.
Attempting to access a result_url before the task reaches the exported state will lead to errors or empty datasets. A robust integration requires a polling loop that respects these state transitions.
Implementation Strategy
To build a reliable pipeline, follow these three stages:
1. Task Submission
Submit your file (CSV or TXT) via the POST https://api.checknumber.ai/v1/tasks endpoint. Ensure your input is normalized to E.164 format. Capture the task_id from the response, as this is your unique handle for the duration of the job.
2. The Polling Loop
Use the POST https://api.checknumber.ai/v1/gettasks endpoint to query the status of your task_id.
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Do not assume completion: If the status is
pendingorprocessing, your application should wait before checking again. - Configurable intervals: Implement a non-aggressive polling interval. Avoid tight loops that hammer the endpoint; the API has rate limits that restrict requests per minute and that concurrency is also limited. Please refer to the current API documentation for applicable limits.
3. Result Retrieval
Only once the status returns as exported should your application attempt to access the result_url. This file contains the final verification data, including the number and the activated status for each entry.
Best Practices for Data Integrity
- Schema Validation: As with any JSON-based data exchange, remember that JSON does not enforce data structure validation on its own. Always validate the structure of the retrieved data against your expected schema before injecting it into your downstream databases.
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Handle Failures: The
statusfield can also returnfailed. Ensure your pipeline includes logic to catch these states and log thetask_idfor manual inspection rather than assuming a successful export. - Preserve Metadata: When processing the downloaded result file, maintain the original column headers. This ensures that your downstream mapping logic remains compatible with future API updates.
Conclusion
By decoupling task submission from result retrieval, you create a resilient architecture capable of handling large-scale Viber verification tasks. Always design your polling logic to be state-aware, and ensure your integration handles the full lifecycle—from pending to exported—to maintain the integrity of your contact intelligence data.
This article was drafted with AI assistance and reviewed before publishing.
