zanpy 0.1.0

A high-performance N-dimensional array library built in Rust for macOS.

🚀 Zanpy

Zanpy is a high-performance N-dimensional array library built in Rust with a seamless Python interface. It leverages SIMD (Single Instruction, Multiple Data) and cache-efficient memory layouts to provide blazing-fast linear algebra operations.

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✨ Features

• Native Rust Engine: Memory-safe, high-speed core implementation.
• SIMD Acceleration: Matrix multiplication optimized with wide SIMD types (f64x2) and $i, k, j$ loop reordering.
• N-Dimensional Support: Sophisticated broadcasting for arrays up to 8 dimensions.
• Numpy-Compatible: Familiar Python syntax for reshape, transpose, arange, and identity.
• Linear Algebra: Built-in LU decomposition for matrix inversion and dot product support.

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📦 Installation

To install the latest release via pip:

pip install zanpy

Note: For local development, see the Development section.

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🛠 Usage

Basic Array Creation

import zanpy

# Create a 2x2 identity matrix
identity = zanpy.PyNdArray.identity(2)

# Create an array from a range and reshape it
a = zanpy.PyNdArray.arange(0, 4, 1).reshape([2, 2])

Arithmetic & Broadcasting

b = zanpy.PyNdArray.ones([2, 2])

# Element-wise addition using the + operator
c = a + b

# Matrix Multiplication using the @ operator
d = a @ identity

Reductions & Math

print(f"Matrix Sum: {a.sum()}")
print(f"Matrix Mean: {a.mean()}")
print(f"Matrix Max: {a.max()}")

# Invert a square matrix
a_inv = a.inv()

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🏗 Architecture

Zanpy is architected for speed by separating the math logic from the Python glue:

1. zanpy-core: The standalone Rust crate. It manages the NdArray struct, calculating memory offsets via strides and executing raw SIMD math.
2. zanpy-py: The bridge crate. Uses PyO3 and Maturin to expose Rust functionality as a Python module.

Why it's fast

The mat_mul implementation avoids the "cache-miss" penalty of naive triple-nested loops by using an $i, k, j$ traversal. This ensures that the CPU accesses memory in a linear, predictable fashion, maximizing cache hits.

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🛠 Development

Prerequisites

• Rust (1.70+ recommended)
• Python (3.9+)
• Maturin (pip install maturin)

Building from Source

# Clone the repository
git clone [https://github.com/yourusername/zanpy.git](https://github.com/yourusername/zanpy.git)
cd zanpy

# Compile and install in your current virtual environment
cd crates/zanpy-py
maturin develop --release

Testing

# Run Rust unit tests
cargo test

# Run Python integration tests
pytest tests/

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📜 License

Distributed under the MIT License. See LICENSE for more information.