eroman details how switching to uvloop as the default event loop in Azure Functions for Python 3.13+ delivers faster async performance with no code changes needed, supported by benchmark data and practical integration notes.

Boosting Python Performance on Azure Functions with uvloop

With Python 3.13+, Azure Functions makes significant strides in performance by adopting uvloop as the default event loop. This change delivers faster, more scalable async workloads—crucial for real-time APIs, event-driven automation, and high-concurrency serverless scenarios.

Introduction

Azure Functions is central to countless modern applications, especially for Python developers who rely on its I/O and async capabilities for scalability. The new default event loop, uvloop, replaces Python’s standard asyncio loop in Functions on Python 3.13+, improving request throughput and lowering latency without any configuration or code changes.

Why Are Event Loops Important?

In asynchronous Python apps, the event loop schedules coroutines and manages I/O events. For serverless workloads like Azure Functions, this loop handles:

Incoming HTTP requests
Async tasks (e.g., database queries, external service calls)
Parallel event processing (e.g., Event Hubs, Service Bus)

While the traditional UnixSelectorEventLoop is reliable, it’s not optimized for high-throughput demands. uvloop, built atop libuv in Cython, consistently outperforms it, making it an efficient choice for cloud environments.

Implementation: uvloop in Azure Functions

Starting with Python 3.13, Azure Functions Python worker sets the default as follows:

import uvloop
import asyncio
asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())

All asynchronous workloads—whether using async def, external API calls, or parallel async operations—immediately benefit from uvloop’s enhanced scheduling and I/O. No special configuration or requirements.txt edits are needed; uvloop is pre-installed in the Functions runtime for Python 3.13+.

Benchmarking Performance: Real-World Results

Three types of load tests were run using Azure’s Flex Consumption plan (2048 MB instance), comparing Python 3.12 (Unix event loop) and Python 3.13 (uvloop):

Test 1: 10k Requests, 50 Virtual Users

Local: uvloop saw +9.7% requests/sec over UnixSelectorEventLoop
Azure: uvloop achieved +4.8% improvement

Test 2: Sustained Load, 100 Virtual Users (5 min)

Local: uvloop gave +6.4% more requests/sec
Azure: uvloop delivered +2.9% improvement

Test 3: 500 Virtual Users, 5 Async Tasks per Request

Local: uvloop performed +7% better
Azure: uvloop resulted in +1% improvement

Notably, the Unix event loop encountered failure rates of around 2% at high loads, which uvloop mitigated.

Why Only Python 3.13+?

Although uvloop supports earlier Python versions, it’s the default only in 3.13 for:

Improved performance and stability
Simpler, risk-free rollout across all Azure Functions SKUs
Coordination with new features in Python 3.13, including a Proxy Worker for added performance

Older workers use the standard event loop to avoid compatibility issues.

Challenges & Lessons Learned

Compatibility: Ensured uvloop runs reliably across Azure’s Linux environments
Observability: Log updates confirm which event loop policy is active
Benchmarks: Designed to reflect real-world workloads, testing more than just microbenchmarks

Looking Ahead

Azure Functions will continue to optimize Python performance with:

Deeper asyncio and gRPC optimizations
Serialization enhancements (e.g., via orjson)
Faster cold starts for Python workers

Conclusion

Upgrading to Python 3.13+ on Azure Functions brings instantaneous, configuration-free performance improvements thanks to uvloop, with no changes needed to your existing code.