---
title: QuPrep
emoji: ⚡
colorFrom: blue
colorTo: purple
sdk: gradio
pinned: true
license: apache-2.0
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/6390b2d90aea681d3f3fd6b7/wZZeHlOwjImqGL6xBG65U.png
---

# QuPrep — Quantum Data Preparation

**The missing preprocessing layer between classical datasets and quantum computing.**

QuPrep converts classical tabular datasets into quantum-circuit-ready format. It sits between your data and whichever quantum framework you use — Qiskit, PennyLane, Cirq, TKET, Amazon Braket, Q#, or IQM — without locking you into any one of them.

Think of it as the **pandas of quantum data preparation**: focused, composable, framework-agnostic.

```
CSV / DataFrame / NumPy  →  QuPrep  →  circuit-ready output for your framework
```

## What it does

- **11 encoding methods** — Angle, Amplitude, Basis, IQP, Entangled Angle, Data Re-uploading, Hamiltonian, ZZFeatureMap, PauliFeatureMap, Random Fourier, Tensor Product
- **8 export targets** — Qiskit, PennyLane, Cirq, TKET, Amazon Braket, Q#, IQM, OpenQASM 3.0
- **Intelligent recommendation** — dataset-aware encoding selection with ranked alternatives
- **Hardware-aware reduction** — auto-reduces features to fit a backend's qubit budget
- **QUBO / Ising** — formulate and solve combinatorial optimization problems (Max-Cut, TSP, Knapsack, Portfolio, and more)
- **Plugin registry** — register custom encoders and exporters that work with the same one-liner API

## Install

```bash
pip install quprep
```

## Quick example

```python
import quprep as qd

result = qd.prepare("data.csv", encoding="angle", framework="qiskit")
print(result.circuit)   # qiskit.QuantumCircuit
print(result.cost)      # gate count, depth, NISQ safety
```

## Links

- 📦 PyPI: [pypi.org/project/quprep](https://pypi.org/project/quprep/)
- 📖 Docs: [docs.quprep.org](https://docs.quprep.org)
- 🌐 Website: [quprep.org](https://quprep.org)
- 💻 Source: [github.com/quprep/quprep](https://github.com/quprep/quprep)
- 🎯 Demo: [huggingface.co/spaces/quprep/demo](https://huggingface.co/spaces/quprep/demo)

---

*Apache 2.0 license · Python ≥ 3.10 · Independent research project*