async-graph-data-flow is a Python library for executing asynchronous functions
that pass data along a directed acyclic graph (DAG).
Functions organized as a graph 🕸
Your asynchronous functions are nodes in the DAG. Each node yields data to its destination nodes.
Let data flow along the graph 🥂
It’s like how champagne flows along a champagne tower. Graph execution continues as long as there’s still data between two connected nodes.
Customizable start nodes 🧨
By default, graph execution begins with nodes that have no incoming nodes, but you can choose to start the graph execution from any nodes.
Data flow statistics ⏳
Utilities are available to keep track of data volumes at each node and optionally log such info at a regular time interval.
Exception handling 💥
Choose whether to halt execution at a specific node or any node.
The source code is only about 400 lines!
Single-machine Usage 💻
We love Big Data™ and distributed computing, though deep down we all know that practically we accomplish a ton of work on single machines without those big guns.
Pure Python 🐍
The library is built on top of
asyncio from the Python standard library, with no third-party dependencies.
Download and Install#
pip install async-graph-data-flow
Start with Quickstart, and then get inspired by More Examples. Don’t forget to check out the API Reference as well.
Under the Hood#
async-graph-data-flow chains asynchronous functions together
Queue instance between two functions in the graph.
A queue keeps track of the data items yielded from a source node and feeds them
into its destination node.
BSD 3-Clause License.
Blog post introducing this package
Table of Contents#
- More Examples
- API Reference