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Learn how to use Python 3.10+ asyncio to build high‑throughput, single‑threaded I/O services. The article walks through event‑loop setup, task scheduling, cancellation, structured concurrency, and common pitfalls with concrete code examples.
Learn how async/await lets a single Python thread handle many network requests concurrently, with a concrete web‑scraping example and practical guidance on trade‑offs.
A practical task guide for running I/O-bound work concurrently with Python asyncio: scheduling with create_task/gather, bounding with wait_for, offloading blocking calls, and clean shutdown with cancellation handling.
Learn how to set up SQLAlchemy 2.0’s AsyncEngine and AsyncSession for non‑blocking database access in FastAPI, including a working example, verification steps, and key limitations.
Python 3.11's asyncio.TaskGroup enforces structured concurrency: child tasks are awaited on exit, exceptions cancel siblings and re-raise as ExceptionGroup. Covers design, trust boundaries, failure modes, and when to use a supervised nursery instead.
SQLAlchemy 2.0’s async engine can cut latency for high‑concurrency workloads, but it adds complexity. This blog walks through the problem, setup, a worked example, trade‑offs, and actionable take‑aways for deciding whether to go async.
Learn how to implement a non-blocking database read/write path using SQLAlchemy 2.0 AsyncSession and QueuePool, including session lifecycle management and operational monitoring.
Discover when Python’s async/await is worth the extra complexity. A concrete aiohttp example shows real speedups for I/O‑bound tasks, plus a clear list of trade‑offs and actionable next steps.
Stop letting network latency freeze your Python apps. Learn how to use asyncio and aiohttp to handle concurrent I/O-bound tasks and increase application throughput.
python
fastapi