Getting Started¶

Pysic-rs is a high-performance mathematical physics engine written in Rust with Python bindings via PyO3. This page walks you through prerequisites, installation, a first import, and running the test suite.

Prerequisites¶

Tool

Version

Purpose

Rust toolchain

stable ≥ 1.70

compiles the core (via rustup)

Python

3.8+

bindings / usage

maturin

≥ 1.0

builds the Python extension

num-complex, ndarray, rustfft

crates.io

dependency resolution is automatic

No system C compiler or BLAS/LAPACK is required — the library is pure Rust.

Installation¶

1. Clone the repository¶

git clone https://github.com/ThotDjehuty/pysic-rs.git
cd pysic-rs

2. Install maturin¶

pip install maturin

3. Build & install the Python package (editable, into your active venv)¶

maturin develop --release        # release build — fast

For a debug, faster-to-compile cycle during development:

maturin develop                  # debug build

4. Verify the import¶

import pysicrs
print(pysicrs.__version__)      # 0.1.0
print(pysicrs.constants()["c"]) # 2.997925e+08

Note for CI / headless builds: every binary artifact is compiled locally; there are no prebuilt wheels published yet (see Changelog).

Quick test¶

from pysicrs import gamma, schwarzschild_metric, rk4_solve

print(gamma(5.0))                      # 24.0
print(schwarzschild_metric(10.0, 1.0)) # [[-0.8, ...]]

Run the full test suite to validate your build:

cargo test                  # 57 tests: 45 unit + 12 integration

Jupyter note (workspace convention)¶

If you develop inside companion notebooks, use the rhftlab kernel (Python 3.11 + hft_lab_core + polars + ccxt) and verify the kernel before executing:

# inside the notebook — always confirm the imported build
import pysicrs
assert pysicrs.__version__ == "0.1.0", pysicrs.__version__

Next steps¶

  • Quickstart — runnable examples for each module

  • Algorithms — mathematical foundations

  • Installation — detailed build recipes, conda & Rust toolchain setup