https://github.com/bluegreen-labs/oneflux_containers
Containerized (docker) versions of the ONEFlux processing pipeline
https://github.com/bluegreen-labs/oneflux_containers
data ecosystem fluxes micrometeorology processing
Last synced: 8 months ago
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Containerized (docker) versions of the ONEFlux processing pipeline
- Host: GitHub
- URL: https://github.com/bluegreen-labs/oneflux_containers
- Owner: bluegreen-labs
- License: agpl-3.0
- Created: 2022-05-22T18:22:29.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-05-23T19:50:53.000Z (about 4 years ago)
- Last Synced: 2025-09-09T17:36:50.150Z (9 months ago)
- Topics: data, ecosystem, fluxes, micrometeorology, processing
- Language: Dockerfile
- Homepage:
- Size: 74.2 KB
- Stars: 3
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ONEFlux docker images
Automating deployment of the [ONEFlux processing pipeline](https://github.com/fluxnet/ONEFlux) 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.
```bash
# 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:
```bash
# 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.
```bash
# 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
```
