Hey r/Python 👋

I’d like to share AsyncFlow, an open-source simulator I’m building to model asynchronous, distributed backends in Python.

🔹 What My Project Does

AsyncFlow lets you describe a system topology (client → load balancer → servers → edges) and run discrete-event simulationswith event-loop semantics:

Servers emulate FastAPI+Uvicorn behavior (CPU-bound = blocking, I/O = yields). Edges simulate network latency, drops, and even chaos events like spikes or outages. Out-of-the-box metrics: latency distributions (p95/p99), throughput, queues, RAM, concurrent connections. Input is YAML (validated by Pydantic) or Python objects.

Think of it as a digital twin of a service: you can run “what-if” scenarios in seconds before touching real infra.

🔹 Target Audience

Learners: people who want to see what happens in async systems (event loop, blocking vs async tasks, effects of failures). Educators: use it in teaching distributed systems or Python async programming. Planners: devs who want a quick, pre-deployment view of capacity, latency, or resilience trade-offs.

Repo: 👉 https://github.com/AsyncFlow-Sim/AsyncFlow

I’d love feedback on:

Whether the abstractions (actors, edges, events) feel useful. Which features/metrics would matter most to you. Any OSS tips on docs and examples.

Thanks, happy to answer questions! 🚀