09-09, 14:00–14:20 (Asia/Jerusalem), Main Hall (30)
Language: עברית
Want to build faster Python apps without ditching Python? This talk shares how we supercharged a Python Valkey/Redis client by combining the power of asyncio with native speed via FFI.
We’ll begin by discussing a common challenge in Python apps—how to achieve high performance, particularly for I/O-heavy or async workloads, without abandoning the ecosystem. Then, we’ll dive into how we built key parts of a Valkey client to take advantage of asyncio powerful concurrency model while using FFI to offload key performance-sensitive tasks to native code. We’ll show profiling before and after, walk through code samples, and share lessons on safely mixing Python with lower-level languages. Finally, we'll explore how these patterns can generalize to other async Python projects.
Basic
Target audience –Developers, R&D, DevOps, Testers/QA
Over the past 5 years at AWS ElastiCache, I’ve been responsible for performance evaluation of Redis/Valkey and serverless offerings, developing automation tools for performance qualification and monitoring. I also lead the Valkey-glide open-source initiative, focused on building the best Valkey client. This work has given me deep experience with Python, especially in high-performance and async contexts. I’ve collaborated with open-source communities on Python client libraries, and I'm passionate about pushing the boundaries of Python performance.