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ONEFlux docker images

Automating deployment of the ONEFlux processing pipeline by BlueGreen Labs.

Interactive image

The interactive image is compiled without calling any additional scripts. It's sole purpose is to provide a consistent and functional environment in which the ONEFlux processing chain will run without having to deal with annoying python install. You can get access to the session by starting an interactive docker session.

# build the image (in the interactive folder)
docker build -t oneflux-interactive .

# drop into a command prompt with a functional
# ONEFlux install
docker run -ti oneflux-interactive:latest

Headless image

Using the headless image you can use oneflux using a rather long but easily understood command:

# build the image (in the headless folder)
docker build -t oneflux-headless .

# process the demo data
docker run -v /your/data/:/data oneflux-headless:latest all "/data" US-ARc "US-ARc_sample_input" 2005 2006 -l fluxnet_pipeline_US-ARc.log --mcr /opt/mcr/v94/ --recint hh

Here, docker run -v /your/data/:/data test:latest starts a docker image instance where you mount (connect) your data location /your/data/ to the virtual file system /data/ location. In the headless instance the onefluxprocessing.py python script is started by default and awaits its usual input parameters. Consequently, the remaining command as specified are the input parameters to the standard python script. The only difference is that you shouldn't specify your local file storage location but the virtual docker image location /data/.

ONEFlux docker App

To track progress more easily a streamlit GUI based wrapper is provided to the processing. Sadly, I have given up on developing this further than the state it is currently in (non-functional). Technically it should all work, yet it doesn't due to ONEFlux relying on old python 2.7 code, with no easy fix it seems. Below are the instructions to build the current image and a preview of the simple layout in Streamlit under python 3.5+. Any commits to resolve the issue by getting a functional image on python 3.5+ are welcome.

# build the image (in the headless folder)
docker build -t oneflux-app .

# start the service
docker run -p 8501:8501 -v /your/data/:/data oneflux-app:latest