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AI Flow, an extend operators library for airflow, which helps AI engineer to write less, reuse more, integrate easily.

Project description

AI Flow


AI Flow, which offers various reusable operators & processing units in AI modeling, helps AI engineer to write less, reuse more, integrate easily.


pip install aiflow


Operators VS. Units

Ideally, we agree:

  • An Operator would contain lot of units, which will be integrated into airflow for building non-realtime processing workflow;
  • A Unit is a small calculation unit, which could be a function, or just a simple modeling logic, and it could be picked as bricks to build an operator. Besides, it could be reused anywhere for realtime calculation.









Tests & Examples

Example: Use Units to Build Your Castle

Example: Working with Airflow

In tests/docker/ folder, we provide examples on how to use aiflow with airflow. It is a docker image, you could simply copy and start to use it!

In project root directory, run commands first:

docker-compose up --build aiflow

Then open localhost:8080 in your browser, you can see all the examples aiflow provided! Note: both the default username & password are admin



Project details

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