https://github.com/sandialabs/pioneer_wec_dashboard
https://sandialabs.github.io/pioneer_wec_dashboard/
https://github.com/sandialabs/pioneer_wec_dashboard
scr-3358 snl-visualization
Last synced: 4 months ago
JSON representation
https://sandialabs.github.io/pioneer_wec_dashboard/
- Host: GitHub
- URL: https://github.com/sandialabs/pioneer_wec_dashboard
- Owner: sandialabs
- Created: 2026-03-12T16:11:14.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2026-03-30T05:22:40.000Z (4 months ago)
- Last Synced: 2026-03-30T07:46:36.144Z (4 months ago)
- Topics: scr-3358, snl-visualization
- Language: Python
- Homepage:
- Size: 69.3 MB
- Stars: 0
- Watchers: 0
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Pioneer WEC dashboard
A simple dashboard for viewing up-to-date data from the Pioneer WEC v1 prototype.
https://sandialabs.github.io/pioneer_wec_dashboard/
## Usage
Build the dashboard site locally with the steps below.
### Prerequisites
- Python 3.10+ (recommended)
- Ruby + Bundler (for Jekyll)
### 1) Install Python dependencies
```bash
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
```
### 2) Install Ruby/Jekyll dependencies
```bash
bundle install
```
### 3) Build the site
Run the full pipeline (fetch data, generate plots, and build the Jekyll site):
```bash
python app.py all
```
### 4) View build output
The generated site files are written to:
- `output/`
Open `output/index.html` in a browser to inspect the locally built site.
## Build options
Partial builds can be run by passing optional arguments when running `app.py`:
- `python app.py` or `python app.py all`: run the full pipeline (fetch data, generate plots, build site)
- `python app.py fetch-data --start-date YYYY-MM-DD`: fetch and cache raw data starting from a date (default: 2025-11-03)
- `python app.py generate-plots`: generate plot HTML files from cached data
- `python app.py build-site`: generate Jekyll includes and build/copy the site output
## Data caching
To alleviate the need to pull data during debugging and to speed up GitHub actions, raw data is cached locally in a `.cache` directory.
Additionally, processed data files are saved in `output/data/` to speed up partial builds and allow for the user to perform custom analyses.