8 articles tagged #Concurrency
asyncio.gather() makes it easy to run multiple coroutines concurrently, but improperly handling its exceptions can leave failures unnoticed or cancel unrelated tasks. Learn how asyncio.gather() propagates exceptions, what return_exceptions=True actually does, and how to build reliable asynchronous
ChatGPT can scaffold transaction code in seconds, but it routinely gets isolation levels wrong — leaving you exposed to phantom reads you won't catch until production. Here's how to prompt it correctly.
ChatGPT can draft distributed lock code fast, but split-brain bugs hide in the details — expiry races, unsafe release patterns, and missing fencing tokens. Learn the prompts that surface the real failure modes before they hit production.
ChatGPT can generate mutex and locking code that looks correct at a glance but silently deadlocks under load. Learn the prompting techniques that force it to produce safe, production-ready concurrency code.
ChatGPT can scaffold a background job scheduler in minutes, but the default output often ignores locking, duplicate execution, and concurrency edge cases. Here's how to prompt for code that actually holds up in production.
Running a SQLite query inside a Python thread and getting nothing back? The culprit is almost always connection sharing across thread boundaries. Here's exactly how to diagnose and fix it.
Getting 'database is locked' errors when multiple threads or processes write to the same SQLite file? This guide walks through every real fix — from timeout tuning to WAL mode — so your concurrent writes stop failing.
Async applications can appear responsive until a hidden deadlock causes tasks to wait forever. Learn how asyncio deadlocks happen, how to detect them early, and how to prevent application freezes in production.