Parallelism and preemptive concurrency for sporadic workloads
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Updated
Dec 2, 2024 - Python
Parallelism and preemptive concurrency for sporadic workloads
A Python Process Pool Executor implementation that is harder to break
asyncio executors, clean and simple.
Dynapipeline is a framework designed for building and managing data pipeline workflows
A high-performance Python utility for batch-converting standard images into retro, stylized pixel art with custom palettes and CRT scanline effects.
Parallel process pool that throttles the task producer thread to avoid out-of-memory issues
Patches asyncio to add to_process — offload CPU-bound work to a separate process, get back an awaitable ProcessTask with full metadata, graceful cancellation, and first-class type support.
A process pool that yields to the human at the keyboard.
Project for Parallel Algorithms course at Faculty of Computing
Conways' Game of life multi-core implementation
Use Python multiprocessing (Pool) to speed up a CPU-bound task, compare sequential vs parallel map, implement cpu_intensive_task, run and record timings, and explain why processes bypass the GIL compared with threads.
Zero-dependency parallel script runner for Python — define tasks, run them in parallel, stream results.
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