Metadata-Version: 2.2
Name: skq
Version: 0.1.4
Summary: Scientific Toolkit for Quantum Computing
Author-email: Carlo Lepelaars <info@carlolepelaars.nl>
Requires-Python: <4,>=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy<=2.0.2
Requires-Dist: plotly>=5.22.0
Requires-Dist: nbformat>=5.10.4
Requires-Dist: qiskit>=1.2.0
Requires-Dist: matplotlib>=3.9.1
Requires-Dist: pylatexenc>=2.10
Requires-Dist: scipy>=1.14.0
Requires-Dist: pennylane>=0.37.0
Requires-Dist: pyquil==4.14.0
Provides-Extra: dev
Requires-Dist: pytest>=8.3.4; extra == "dev"
Requires-Dist: ruff>=0.8.4; extra == "dev"

# skq

Scientific Toolkit for Quantum Computing

This library is used in the [q4p (Quantum Computing for Programmers)](https://github.com/CarloLepelaars/q4p) course.

NOTE: This library is developed for educational purposes. While we strive for correctness of everything, the code is provided as is and not guaranteed to be bug-free. For sensitive applications make to check computations. 

## Why SKQ?

- Exploration: Play with fundamental quantum building blocks (NumPy).
- Education: Learn quantum computing concepts and algorithms.
- Integration: Combine classical components with quantum components.
- Democratize quantum for Python programmers and data scientists: Develop quantum algorithms in your favorite environment and easily export to your favorite quantum computing platform for running on real quantum hardware.

## Install

```bash
pip install skq
```
