Concurrency & performance, four ways — hand-drawn, interactive, example-heavy guides from first principles to scaling under load
The event loop, coroutines, and 10 production async patterns — semaphores, queues, timeouts, circuit breakers, batching, and cancellation.
Threads, the GIL, locks and races, pools, and 12 patterns — plus deep-dives on the GIL, threads-vs-processes, and the CPython memory model.
True parallelism across cores: process basics, pools, IPC & queues, shared memory, pickling, start methods, and CPU parallelism — plus a GIL-and-parallelism deep-dive.
Scaling Python under load across all three models — pooling, batching, backpressure, limits, caching, resilience, profiling, and worked case studies.
New to concurrency? Start with Async 101 or Threading 101 — they explain the same core idea (overlap the waiting) from two angles.
Need real CPU parallelism? Go to the Process Guides — multiprocessing is the only model that sidesteps the GIL and uses every core.
Deciding threads vs async vs processes? Read Threads vs Processes vs Async and the GIL deep-dive — they explain why each model exists.
Already shipping and hitting limits? Go straight to Optimizations — start with Optimizations 101 to find your bottleneck, then apply the technique pages.