This release is a pre-release and may not be stable for production use.
Divi
Generate, parallelize, and execute quantum programs at scale.
Divi is a Python library by Qoro Quantum for building and running quantum programs at scale. It handles circuit generation, job parallelization, and cloud execution — with built-in support for variational algorithms, custom workflows, and more — so you can focus on the quantum problem, not the plumbing.
⚡ Quick Start
pip install qoro-divi
Nightly Builds
To install the latest development build (published daily from main):
pip install qoro-divi --pre
Run a VQE energy minimization in a few lines:
import numpy as np
import pennylane as qml
from divi.qprog import VQE, HartreeFockAnsatz
from divi.backends import QiskitSimulator
from divi.qprog.optimizers import ScipyOptimizer, ScipyMethod
# Define an H₂ molecule
molecule = qml.qchem.Molecule(
symbols=["H", "H"],
coordinates=np.array([(0, 0, 0), (0, 0, 0.5)]),
)
vqe = VQE(
molecule=molecule,
ansatz=HartreeFockAnsatz(),
n_layers=2,
backend=QiskitSimulator(shots=5000),
optimizer=ScipyOptimizer(method=ScipyMethod.COBYLA),
seed=42,
)
vqe.run()
print(f"Ground state energy: {vqe.best_loss:.6f}")
🌐 Cloud Execution with Qoro Service
Run the same programs on Qoro's cloud platform with tensor-network simulators — no code changes needed:
from divi.backends import QoroService
service = QoroService() # reads QORO_API_KEY from .env or environment
vqe = VQE(molecule=molecule, backend=service)
vqe.run()
Get started for free → Sign up at dash.qoroquantum.net and receive $100 worth of credits to run your first quantum programs on our cloud.
🧩 Key Features
| Feature | Description |
|---|---|
| VQE & QAOA | Built-in variational algorithms with pluggable ansätze and optimizers |
| Circuit Pipelines | Expand → execute → reduce pattern for complex circuit workflows |
| Program Batching | Automatic Pauli grouping, circuit packing, and parallel execution |
| Dual Backends | Local QiskitSimulator for dev, QoroService for cloud production |
| Execution Config | Control bond dimension, simulator type, and simulation method per job |
| Live Reporting | Real-time dashboards and convergence tracking via callbacks |
🏗️ Architecture
divi/
├── qprog/ # Quantum programs: VQE, QAOA, base classes, optimizers
├── backends/ # Execution backends: QiskitSimulator, QoroService
├── circuits/ # MetaCircuit templates and Circuit instances
├── pipeline/ # Circuit pipeline stages (expand, execute, reduce)
├── hamiltonians # Molecular Hamiltonian generation
└── reporting/ # Live reporting and visualization callbacks
📚 Documentation
Full documentation, user guides, and API reference: docs.qoroquantum.net/divi
Hands-on examples are in the tutorials/ folder.
� Contributing
Contributions are welcome! See CONTRIBUTING.md for development setup, testing, and code style guidelines.
📄 License
Apache 2.0 — see LICENSE for details.
2 maintainers
Metadata
2 maintainers
Release files for qoro-divi 0.11.0.dev20260331
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| qoro_divi-0.11.0.dev20260331.tar.gz | 187.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| qoro_divi-0.11.0.dev20260331-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 421.8 kB
Release files / qoro_divi-0.11.0.dev20260331.tar.gz
| Download URL | qoro_divi-0.11.0.dev20260331.tar.gz |
|---|---|
| Size | 187.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a261ef15846fe44d89381f988b425cdc9d317ff4117c760b18133517ce56ac5e
|
|
BLAKE2b-256 checksum How to use checksums |
1b5080efc7f4e2f25f325efc503d98a8331a5c35b935acdf5de1e707d474dfba
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 31, 2026.
Transparency logRelease files / qoro_divi-0.11.0.dev20260331-py3-none-any.whl
| Download URL | qoro_divi-0.11.0.dev20260331-py3-none-any.whl |
|---|---|
| Size | 234.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
74ab439d744e7a27850cbcd1937749f56aa2398c5f8000da42ba67d1c7391117
|
|
BLAKE2b-256 checksum How to use checksums |
0e5cf6aa09188bd04bc96b41d250e3e9406548c85e9d6d9875a8996661671c70
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 31, 2026.
Transparency log
