aeventkit

What it is and what it does

aeventkit is an event-driven framework for building asynchronous data pipelines in Python. It lets you emit events that trigger multiple listeners, compose async operations on data streams, and integrate seamlessly with asyncio. The package offers a Pythonic API for connecting loosely-coupled components and supports both synchronous event emission and async iteration.

The framework is suitable for real-time data processing and distributed computing workflows. It abstracts away boilerplate asyncio code while preserving full control over scheduling and async behavior, with numpy as its sole runtime dependency.

Use it for:

• Build real-time data pipelines that transform and filter streams of events or sensor data
• Connect independent components in an application without tight coupling via event listeners
• Compose async iterators and streams with operators like map, filter, and zip
• Process continuous data with async analysis stages in event-driven architectures
• Distribute compute-heavy pipeline stages across multiple cores or machines

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

aeventkit provides event-driven data pipelines and loosely-coupled event messaging using asyncio, with a Pythonic interface for composing async data flows and connecting event listeners.

Yes, if you are building event-driven or async data pipeline applications and want a Pythonic abstraction over asyncio. The low install friction, active maintenance, and permissive license support adoption. However, the Beta status and recent first release mean you should evaluate it in a non-critical context first and clarify the license ambiguity with the maintainer before using it in proprietary code.

Install

aeventkit on PyPI

pip install aeventkit

uv add aeventkit

poetry add aeventkit

Installing aeventkit

Before you install

Low install friction with a pure-Python wheel. Active maintenance with recent commits; however, the package is in Beta status and has been in its first release cycle for under a year, so stability and API maturity remain unproven.

License in practice

BSD license is permissive and poses no restrictions on use or redistribution. However, the classifiers also list 'Other/Proprietary License', creating ambiguity about the actual license terms—clarification from the maintainer would be prudent before relying on it in proprietary projects.

Quickstart

pip install aeventkit

import aeventkit as ev

event = ev.Event()
event += lambda a, b: print(a * b)
event.emit(10, 5)

Python 3.10 or later is required.

Verify before relying

• Whether the 'Other/Proprietary License' classifier is a documentation error or indicates dual licensing
• Actual test coverage and production readiness despite Beta status
• Performance characteristics under high-throughput or large-scale pipelines

Package facts

Evidence: aeventkit-2.1.0-py3-none-any.whl

Keywords: python, asyncio, event, driven, data, pipelines

Tags

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