Metadata-Version: 2.4
Name: qubitflow
Version: 0.1.0
Summary: A modular and scalable quantum computing framework inspired by TensorFlow and PyTorch.
Home-page: https://github.com/qubit-flow/qubitflow
Author: G Sreejith
Author-email: Your Name <you@example.com>
License: MIT
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: matplotlib
Dynamic: author
Dynamic: home-page
Dynamic: requires-python

# QubitFlow

**QubitFlow** is an open-source quantum computing framework based on python designed to be intuitive, scalable, and modular — bringing the simplicity of TensorFlow and PyTorch to the quantum world.

🚧 **Currently Under Active Development**  
We are laying the foundations for a robust, user-friendly quantum programming interface. The initial push will be live soon!

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## 🔍 About the Project

QubitFlow aims to simplify quantum circuit design, simulation, and integration with classical machine learning workflows. Our mission is to:

- Make quantum programming **accessible** to developers and researchers
- Provide a **modular architecture** for rapid experimentation
- Support both **quantum simulation** and **real quantum hardware backends**
- Enable **hybrid quantum-classical models** in a seamless fashion

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## 📌 Planned Features

- Quantum Circuit API (Tensor-like syntax)
- Backend support for simulators and real quantum processors (Qiskit, Braket, etc.)
- Parameterized gates and optimization routines
- Integration with NumPy, PyTorch, and JAX
- Quantum datasets and benchmarking tools
- Visualization of quantum states and circuits

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## 📦 Installation

Coming soon: `pip install qubitflow`

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## 👷 Roadmap

- [x] Project Initialization
- [ ] Core Quantum Circuit API
- [ ] Backend Plugin System
- [ ] Hybrid Model Examples
- [ ] Documentation and Tutorials
- [ ] First Release (v0.1.0)

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## 🤝 Contributing

Interested in contributing? We'd love to collaborate! Stay tuned for contributing guidelines once the repo is live.

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## 📬 Stay Updated

Watch the repository for the first release, documentation, and usage examples.

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> _QubitFlow – Building the bridge between classical and quantum intelligence._

