Open Source · Python ≥3.8 · v1.8.8
Olympipe Parallel pipelines without boilerplate
Chain multiprocessing steps in Python with a fluent API. Bypass the GIL, saturate your CPU or GPU, without managing Pools or Queues.
Installation
$ pip install olympipe
Quick start
python
from olympipe import Pipeline
results = (
Pipeline(range(1000))
.task(heavy_compute, count=8) # 8 workers parallèles
.filter(lambda x: x > 0)
.batch(32)
.wait_for_result()
)Local performance
Each step runs in its own process — no GIL, no manual coordination.
8x
typical speedup with 8 workers
0
multiprocessing boilerplate
100x
faster with disk cache
Features
⚡ 🔍 📦 🔀 🧠 💾
Parallel tasks
Scale workers with a single parameter
Filtering
Prune your stream without breaking the pipeline
Batching
Group items to saturate your GPU or database
Split & Gather
Branch your pipeline into independent streams, merge them back
Stateful workers
One ML model per worker, loaded once
Disk cache
Replay an expensive step without recomputing
Browse all examples
Ready-to-paste examples for your real use cases