Boost Didit API Throughput with Python Asyncio

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Python’s asyncio framework can improve the efficiency and scalability of applications that make many I/O-bound API calls, such as identity verification workflows involving document checks, liveness detection, face matching, and AML screening. Didit’s API supports these services but applies global and endpoint-specific rate limits, returning 429 responses and headers such as Retry-After when limits are exceeded. The material describes using an asynchronous HTTP client such as aiohttp to issue concurrent requests, reuse client sessions, and retry rate-limited calls with backoff, while noting that production systems should use more advanced safeguards such as adaptive rate limiting and circuit breakers. It also recommends reducing polling through webhooks, monitoring errors and rate-limit usage, and adjusting concurrency dynamically based on remaining request capacity. Didit presents its modular APIs, sandbox, documentation, free KYC tier, and pay-per-successful-check model as features intended to support developers building high-throughput, cost-conscious identity verification systems.

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