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Installation

This page describes how to install SmartKNN in a clean, reproducible, and production-safe manner.

SmartKNN is designed to run efficiently on CPU-only environments and does not require GPU support.

System Requirements

Before installing SmartKNN, ensure the following:

  • Python: 3.8 or newer
  • Operating System: Linux, macOS, or Windows
  • Architecture: x86_64 (ARM support may be limited)
  • Memory: Sufficient RAM for dataset size

SmartKNN does not require CUDA or GPU drivers.

It is strongly recommended to install SmartKNN inside a virtual environment.

Create a Virtual Environment

Install SmartKNN

pip install smart-knn
This installs the latest stable release.

Option 2: Install from Source (Development)

Use this option if you want the latest development version or plan to contribute.

git clone https://github.com/thatipamula-jashwanth/smart-knn.git
cd smart-knn
pip install -e .

Verify Installation

After installation, verify that SmartKNN is available:

python -c "from smart_knn import SmartKNN; print(SmartKNN)"

You should see a reference to the SmartKNN class without errors.

Quick Sanity Check

Run a minimal example to confirm everything works:

python - <<EOF
from smart_knn import SmartKNN
import numpy as np

X = np.random.rand(100, 5)
y = np.random.rand(100)

model = SmartKNN()
model.fit(X, y)

pred = model.predict(X[:1])
print("Prediction:", pred)
EOF
If this runs without errors, SmartKNN is installed correctly.

Common Installation Issues

Python Version Errors

Ensure you are using Python 3.8 or newer:

python --version

Permission Errors

  • Avoid global installs.
  • Always use a virtual environment if you encounter permission issues.

Numba Compilation Warnings

  • The first execution may trigger JIT compilation warnings.
  • This is expected and typically occurs only once per environment.

Updating SmartKNN

pip install --upgrade smart-knn

Uninstallation

pip uninstall smart-knn