Skip to content

Latest commit

 

History

History
23 lines (18 loc) · 1.42 KB

README.md

File metadata and controls

23 lines (18 loc) · 1.42 KB

TED Meteorology Web App

Python/Flask backend for meteorological analysis and plotting, plus an archived Angular UI (meteorology-visualizer-angular). The old frontend/ prototype is unused and ignored.

Project layout

  • backend/: Flask API in app.py, using the local meteorology_calculator package. Data catalog lives in datasets_info.json and plotting definitions in plots.json.
  • meteorology-visualizer-angular/: Angular client kept for reference; not wired up to the current backend.
  • frontend/: Legacy static prototype (excluded via .gitignore).

Getting started (backend)

  1. Create and activate a virtual environment
    python -m venv .venv && .\\.venv\\Scripts\\activate
  2. Install dependencies (core runtime plus the local calculator package)
    pip install flask flask-cors pandas dask[complete] pyspark plotly
    pip install -e backend/meteorology_calculator
  3. Run the API
    cd backend && python app.py

The API expects the dataset metadata in backend/datasets_info.json and plotting config in backend/plots.json. Generated datasets are written to backend/saved_dfs/ (ignored in git).

Notes

  • Large raw datasets, saved calculation outputs, test utilities, and the unused frontend/ tree are excluded via .gitignore to keep the repo lightweight for GitHub.
  • If you need the Angular UI, install Node and the Angular CLI, then run npm install and npm start inside meteorology-visualizer-angular/.