Installation

This guide will help you install pytrees-rs on your system. We provide multiple installation methods to suit different needs and environments.

Prerequisites

Before installing pytrees-rs, ensure you have the following:

Python Requirements

• Python 3.10 or higher
• pip package manager
• NumPy (automatically installed with pytrees-rs)

For Source Installation

• Rust toolchain (1.70.0 or higher)
• Git (for cloning the repository)

Installing Rust

If you need to install Rust, use the official installer:

# Install Rust using rustup (recommended)
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Restart your shell or run:
source ~/.cargo/env

# Verify installation
rustc --version
cargo --version

Alternative methods:

• macOS: brew install rust
• Ubuntu/Debian: sudo apt install rustc cargo
• Windows: Download from rustup.rs

Installation Methods

Method 1: PyPI Installation

pip install pytrees-rs

Method 2: Building from Source (Current Method)

This is currently the primary installation method:

# Clone the repository
git clone https://github.com/haroldks/pytrees-rs.git
cd pytrees-rs

# Build the Rust binary
cargo build --release

# Install Python package
cd pytrees-rs  # Navigate to Python package directory
pip install .

Method 3: Binary Installation Only

If you only need the command-line interface:

# Clone and build
git clone https://github.com/haroldks/pytrees-rs.git
cd pytrees-rs
cargo build --release

# Create symbolic link (Unix-based systems)
ln -s $(pwd)/target/release/dtrees_rs $HOME/.local/bin/dtrees_rs

# Or copy to system path
sudo cp target/release/dtrees_rs /usr/local/bin/

Basic Usage

After installation, verify that PyTrees-RS is working:

Python Library Test

# Test basic import
import pytrees
from pytrees import DL85Classifier, LGDTClassifier

# Quick functionality test
from sklearn.datasets import make_classification
X, y = make_classification(n_samples=100, n_features=5, random_state=42)
X = (X > 0).astype(float)
clf = DL85Classifier(max_depth=2, min_sup=5)
clf.fit(X, y)
print(f"Accuracy: {clf.score(X, y):.3f}")

Command Line Test

# Test binary installation
dtrees_rs --help

Next Steps

Once installed successfully:

1. Quick Start Guide: Build your first optimal tree
2. Python Library: Explore the API
3. Examples: See real applications