AI Flow, an extend operators library for airflow, which helps AI engineer to write less, reuse more, integrate easily.
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
airflowfor 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
tests/docker/ folder, we provide examples on how to use
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
localhost:8080 in your browser, you can see all the examples
Note: both the default username & password are
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