Installation¶
Requirements¶
Python: 3.11 or higher
Operating System: Windows, macOS, or Linux
Memory: At least 4GB RAM recommended
Install from PyPI¶
Using uv (Recommended)¶
uv add ethnicolr2
Using pip¶
pip install ethnicolr2
Install from Source¶
For development or to get the latest features:
# Clone the repository
git clone https://github.com/appeler/ethnicolr2.git
cd ethnicolr2
# Install with uv
uv sync
# Or install with pip in development mode
pip install -e .
Verify Installation¶
Test that the installation worked correctly:
import ethnicolr2
print(ethnicolr2.__version__)
# Quick test
import pandas as pd
from ethnicolr2 import census_ln
df = pd.DataFrame({'last_name': ['Smith', 'Zhang']})
result = census_ln(df, 'last_name')
print(result)
Dependencies¶
ethnicolr2 automatically installs these key dependencies:
PyTorch 2.8.0: Neural network framework
pandas: Data manipulation and analysis
NumPy 2.x: Numerical computing
scikit-learn 1.5.1: Machine learning utilities
joblib: Model serialization
Development Dependencies¶
For contributors and developers:
# Install all development dependencies
uv sync --all-groups
# Install specific groups
uv sync --group test # Testing tools
uv sync --group dev # Development tools
uv sync --group docs # Documentation tools
Troubleshooting¶
Common Issues¶
ImportError: No module named ‘numpy.exceptions’
# Update to NumPy 2.x
pip install --upgrade "numpy>=2.3.5"
CUDA/GPU Issues
# Check if CUDA is available
import torch
print(torch.cuda.is_available())
Memory Issues
Ensure you have at least 4GB RAM
Models are loaded on-demand to minimize memory usage
Getting Help¶
What’s Next?¶
5-Minute Quickstart: Learn the basics in 5 minutes
Key Concepts: Understand the key concepts
Examples and Use Cases: See practical examples