OmdenaAI CordobaArgentinaChapter_MonitoringLandUseTransformation .cursorrules file for Jupyter Notebook (stars: 5)

name: "Land Use Change Detection Project"

description: |
  Land use change detection and monitoring system in Córdoba, Argentina, 
  using satellite imagery. The project uses pre-trained models and ensemble 
  learning techniques to analyze images at two time points (t1 and t2).

services:
  - name: "preprocessing_service"
    path: "preprocessing_service/**"
    description: "Satellite image preprocessing service"
    tags: ["python", "gdal", "rasterio", "numpy"]

  - name: "model_service"
    path: "model_service/**"
    description: "Pre-trained model inference service"
    tags: ["python", "pytorch", "tensorflow", "scikit-learn"]

  - name: "api_gateway"
    path: "api_gateway/**"
    description: "API Gateway implemented with FastAPI"
    tags: ["python", "fastapi", "pydantic"]

  - name: "queue_service"
    path: "queue_service/**"
    description: "Queue service using Redis and Celery"
    tags: ["python", "redis", "celery"]

  - name: "frontend"
    path: "frontend/**"
    description: "User interface implemented in React"
    tags: ["typescript", "react", "leaflet", "mapbox"]

  - name: "common"
    path: "common/**"
    description: "Shared code between services"
    tags: ["python", "typescript"]

conventions:
  python:
    - "Follow PEP 8"
    - "Google style docstrings"
    - "Mandatory type hints"
  
  typescript:
    - "ESLint Airbnb config"
    - "Prettier for formatting"
    - "TypeScript strict mode"

  git:
    - "Conventional Commits"
    - "Feature branches from develop"
    - "Mandatory pull requests"

key_concepts:
  - name: "Change Detection"
    description: "Detection of changes between two satellite images at different times"

  - name: "Pre-trained Models"
    description: "Use of pre-trained models to avoid manual data labeling"

  - name: "Queue System"
    description: "Redis queue system to handle multiple processing requests"

  - name: "Ensemble Learning"
    description: "Combination of multiple models to optimize results"

dependencies:
  python: "^3.11.8"
  node: "^18.0.0"
  redis: "^7.0.0"
  docker: "^24.0.0"
  docker_compose: "^2.0.0"

team_roles:
  - "Pre-Trained Models and Experimentation Team"
  - "Processing and Optimization Team"
  - "Data Preprocessing and Analysis Team"
  - "Front-End and Visualization Team"

documentation:
  architecture: "docs/architecture.md"
  api: "api-gateway/README.md"
  deployment: "docs/deployment.md"
  development: "docs/development.md"