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PyRill

Asynchronous streams for Python.

PyRill builds asynchronous data pipelines in plain Python. You connect small elements (sources, stages and sinks) with >>, and the data flows through them one frame at a time, on top of asyncio and with no dependencies.

import asyncio

from pyrill.accumulators import ListAcc
from pyrill.mappers import Map
from pyrill.sinks import Last
from pyrill.sources import IterableSource


async def main() -> None:
    pipeline = (
        IterableSource(source=["alpha", "beta", "gamma"])
        >> Map(map_func=str.upper)
        >> ListAcc()
        >> Last()
    )
    print(await pipeline.get_frame())


asyncio.run(main())
['ALPHA', 'BETA', 'GAMMA']

Why PyRill

Programs that handle streams (files, sockets, API responses, queues) tend to grow hand-written loops that mix reading, parsing, filtering, timing and error handling. PyRill turns each of those concerns into a small, typed, reusable element that you can test alone and connect with the others.

  • Pull-based. Work happens only when a frame is needed, so a slow consumer slows the whole pipeline, and frames do not pile up in memory unless you add a buffer.
  • Streaming. A pipeline works on one frame at a time, so memory use depends on the size of the frames, not on the length of the stream.
  • Batteries included. Elements for files and asyncio streams, byte and text re-chunking, safe UTF-8 decoding, CSV, JSON, branching (Tee), pairing (Zip), merging (Union), timeouts and deadlines, pausing (Gate), buffering (Queue) and more.
  • Extensible. Write your own sources, stages and sinks, or package a chain of stages as a single reusable stage.
  • Typed. Elements are generic classes, so type checkers follow the frames through a pipeline.

Installation

PyRill needs Python 3.14 or later and has no other dependencies.

$ pip install pyrill

To work on PyRill itself, clone the repository, run uv sync, and run the tests with uv run pytest.

Documentation

Full documentation, including a quickstart, the core concepts, task-oriented guides and a catalog of every element, is at https://pyrill-framework.readthedocs.io/stable/. The same pages are in the docs/ folder.

The messages and monitoring guide explains how to observe lifecycle changes, rejected frames and file activity, and publish custom progress events through the pipeline's message bus.

Project

Metadata

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