Installation¶

Requirements¶

Python 3.12 or higher
uv (recommended) or pip for package management

Python version

ProgridPy requires Python 3.12+ due to its use of PEP 695 type parameter syntax and modern standard-library features. Earlier versions are not supported.

Install ProgridPy¶

uvpip

uv add git+https://github.com/progridanalytics/ProgridPy.git

pip install git+https://github.com/progridanalytics/ProgridPy.git

Development Setup¶

Clone the repository and install all dependency groups (runtime, dev, docs):

uvpip

git clone https://github.com/progridanalytics/ProgridPy.git
cd ProgridPy
uv sync --all-groups

git clone https://github.com/progridanalytics/ProgridPy.git
cd ProgridPy
pip install -e ".[dev]"

uv is the recommended package manager

The CI pipeline runs uv sync --locked --group dev and uv run pytest. Using uv locally ensures your lockfile stays consistent with CI.

Core Dependencies¶

Package	Purpose
`polars`	High-performance DataFrame processing
`boto3` / `botocore`	AWS S3 data transfers
`pandas`	Auxiliary data manipulation
`plotly`	Interactive metric visualizations
`streamlit`	Analytics dashboard
`requests`	HTTP downloads from ISO sources
`loguru`	Structured logging
`rich`	Terminal progress bars and formatting
`pyarrow` / `fastexcel`	Parquet and Excel I/O
`pydantic`	Data validation
`python-dotenv`	`.env` file loading
`scipy`	Statistical computations in the metrics engine

Verification¶

Confirm the installation is working:

uvpip

uv run python -c "import progridpy; print('OK')"

python -c "import progridpy; print('OK')"

A successful installation prints OK with no errors.

Next Steps¶

Proceed to the Configuration guide to set up AWS credentials, ERCOT API keys, and local data directories before downloading ISO data.