🌤️ Lookout

Lookout is a modular weather station dashboard built with Streamlit, Ambient Weather API, and S3-compatible storage (Storj). It supports data collection, archiving, visualization, and CLI-based maintenance tasks.

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📁 Project Structure

lookout/
├── api/            # API clients (e.g. Ambient Weather)
├── core/           # Data processing and visualization
├── storage/        # S3/Storj integration
├── utils/          # Logging and shared utilities
├── cli/            # Command-line scripts (e.g. catchup)
├── config.py       # Shared config
├── __init__.py     # Package root
streamlit_app.py    # Main dashboard entry point

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⚙️ Setup

1. Clone the repository

git clone https://github.com/yourusername/lookout.git
cd lookout

2. Set up virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Optional: Use env_lookout_frozen.yml if you're managing with Conda.

3. Configure secrets

Create a .streamlit/secrets.toml file or use Streamlit CLI to store:

AMBIENT_API_KEY = "..."
AMBIENT_APPLICATION_KEY = "..."
AWS_ACCESS_KEY_ID = "..."
AWS_SECRET_ACCESS_KEY = "..."

# connnect to the lookout bucket on storj.io
[lookout_storage_options]
ACCESS_KEY_ID = "..."
SECRET_ACCESS_KEY = "..."
ENDPOINT_URL = "https://gateway.storjshare.io"

──

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🚀 Usage

Run the Streamlit dashboard

streamlit run streamlit_app.py

Run the catchup CLI script

PYTHONPATH=. python lookout/cli/catchup.py

Use with cron (with logging + jitter):

lookout/bin/cron_run.sh --sleep 300 lookout/cli/catchup.py

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🧪 Testing

Test files live in the test/ directory and mirror the lookout/ package structure.

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🛠 Developer Notes

• Code formatted with Black and Ruff
• Imports are fully qualified (lookout.api.ambient_client)
• Logging is centralized in log_util.py
• Follows standards defined in code_standards.md

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📡 Dependencies

• Streamlit
• Pandas / NumPy
• Requests
• Boto3 (for S3/Storj)
• Plotly
• Ambient Weather API

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🧠 Author & License

Maintained by @stonematt
Licensed under the MIT License