PyQBPP: Python Interface for QUBO++
PyQBPP is a Python wrapper for the QUBO++ library, allowing you to model and solve combinatorial optimization problems using QUBO/HUBO formulations directly from Python.
Features
- Symbolic construction of QUBO/HUBO expressions in Python
- Access to QUBO++ solvers (Easy Solver, Exhaustive Solver, ABS3)
- Familiar Python syntax with the full power of the QUBO++ engine
Supported Environment
- Linux (Ubuntu 20.04 or later)
- x86_64 or arm64 (aarch64) CPUs
- CUDA-enabled NVIDIA GPUs
- Python 3.8 or later
Installation
PyQBPP is available on PyPI. We recommend using a Python virtual environment (venv) to install PyQBPP. No sudo privileges are required.
$ python3 -m venv ~/qbpp-env
$ source ~/qbpp-env/bin/activate
$ pip install pyqbpp
The wheel contains only the Python code. The shared libraries (about 330 MB)
are downloaded from GitHub Releases
the first time PyQBPP is used, verified against the SHA-256 recorded in the
wheel, and kept in ~/.cache/pyqbpp/ (set PYQBPP_CACHE_DIR to change it).
Run python -m pyqbpp download to fetch them in advance. For machines without
internet access, see the
installation guide.
Without a license key, the number of binary variables is limited to 100.
To remove this limit, register from the User Portal to obtain a trial license key.
Once you have a license key, activate it as follows:
$ qbpp-license -k YOUR-LICENSE-KEY -a
Quick Example
The following program solves a simple QUBO problem by expanding and minimizing the expression f = (a + 2b + 3c - 4)^2.
import pyqbpp as qbpp
a = qbpp.var("a")
b = qbpp.var("b")
c = qbpp.var("c")
f = qbpp.sqr(a + 2 * b + 3 * c - 4)
f = qbpp.simplify_as_binary(f)
print("f =", f)
solver = qbpp.EasySolver(f)
sol = solver.search(time_limit=10, target_energy=0)
print("sol =", sol)
Output:
f = 16 -7*a -12*b -15*c +4*a*b +6*a*c +12*b*c
sol = Sol(energy=0, {a: 1, b: 0, c: 1})
Documentation
Metadata
Release files for pyqbpp 2026.10.10
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyqbpp-2026.10.10-py3-none-manylinux_2_31_x86_64.whl | Python 3 | none | Linux glibc 2.31+ x86-64 | Details |
| pyqbpp-2026.10.10-py3-none-manylinux_2_31_aarch64.whl | Python 3 | none | Linux glibc 2.31+ ARM64 | Details |
Total release size: 3.8 MB
Release files / pyqbpp-2026.10.10-py3-none-manylinux_2_31_x86_64.whl
| Download URL | pyqbpp-2026.10.10-py3-none-manylinux_2_31_x86_64.whl |
|---|---|
| Size | 2.0 MB |
| Tags | Linux glibc 2.31+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.8.10
|
Release files / pyqbpp-2026.10.10-py3-none-manylinux_2_31_aarch64.whl
| Download URL | pyqbpp-2026.10.10-py3-none-manylinux_2_31_aarch64.whl |
|---|---|
| Size | 1.9 MB |
| Tags | Linux glibc 2.31+ ARM64 Python 3 |
|
SHA-256 checksum How to use checksums |
8dad5cfc8e90f1b0ee7804b060336a6e90c8f1ae4e4bbaf89a93cdc5fea91649
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.8.10
|
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