Installation

Prerequisites

• Python 3.8 or higher
• NumPy 1.21 or higher
• pandas 1.3 or higher

Install from PyPI

pip install econometrust

Install from Source

Prerequisites for Building

• Rust toolchain (1.70+)
• maturin build tool

Steps

1. Install Rust (if not already installed):

   curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
   source ~/.cargo/env
   

2. Clone the repository:

   git clone https://github.com/wdeligt/econometrust.git
   cd econometrust
   

3. Install build dependencies:

   pip install maturin
   

4. Build and install:

   maturin develop
   

Development Installation

For development work:

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

Verify Installation

import econometrust
import numpy as np

# Quick test
X = np.random.randn(100, 2)
y = X @ [1.0, -0.5] + np.random.randn(100) * 0.1

model = econometrust.OLS()
model.fit(X, y)
print("Installation successful!")
print(f"Coefficients: {model.coefficients}")

Performance Notes

Econometrust is built with Rust for maximum performance:

• Compiled Native Code: Orders of magnitude faster than pure Python implementations
• Memory Optimized: Minimal allocation overhead during computation
• SIMD Instructions: Automatic vectorization for supported operations
• Cache-Friendly: Data structures optimized for modern CPU architectures

Troubleshooting

Common Issues

1. Rust toolchain not found:

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

2. maturin build fails:

   # Update maturin
   pip install --upgrade maturin
   

3. NumPy compatibility:

   # Update NumPy
   pip install --upgrade numpy
   

Platform-Specific Notes

macOS: Requires Xcode command line tools:

xcode-select --install

Windows: Requires Microsoft C++ Build Tools or Visual Studio.

Linux: Requires standard development tools (gcc, make, etc.).

Dependencies

Econometrust has minimal dependencies:

• NumPy: Array operations and linear algebra
• pandas: Optional, for DataFrame support in examples
• pytest: Testing framework (development only)
• ruff: Code formatting (development only)

The core library only requires NumPy for basic functionality.