xpress
FICO Xpress Optimizer Python interface
Decision gist · record as of 2026-08-14
Yes, if you need to solve mathematical optimization problems and have access to or can accept the Xpress license terms. The package is actively maintained, supports modern Python versions, and offers broad problem-class coverage. Install friction is moderate due to compiled binaries, but wheels are widely available. The main caveat is license clarity—review the Xpress Shrinkwrap License Agreement before production deployment, especially for commercial use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires FICO Xpress Optimizer library (xpresslibs); community license is included but commercial use or advanced features may require a separate license.
- Optional GPU support requires NVIDIA CUDA Runtime 13.0+ and drivers version 580+.
- Medium install friction due to compiled binary wheels; prebuilt wheels available for Python 3.10–3.14 across macOS (ARM64), Linux (x86_64, ARM64), and Windows.
License · maintenance · safety
(unclear) — License treatment is unclear; the package is governed by the Xpress Shrinkwrap License Agreement and includes a community license. A copy of the license is stored in LICENSE.txt in the dist-info directory. Users should review the shrinkwrap terms before deployment.
last release 2026-07-03 (42 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 214,414 downloads/mo, #9,417 on PyPI
Alternatives
Verify before relying
pip install xpress
import xpress as xp
p = xp.problem(name='myexample')
x1 = p.addVariable(vartype=xp.integer, name='x1', lb=-10, ub=10)
x2 = p.addVariable(name='x2')
p.setObjective(x1**2 + 2*x2)
p.addConstraint(x1 + 3*x2 >= 4)
p.optimize()
print(p.getSolution(x1), p.getSolution(x2))- Whether the community license has restrictions on problem size, solver features, or commercial use.
- Performance characteristics and solver algorithm selection for different problem classes.
- Support timeline and end-of-life dates for Python 3.10–3.14 versions.
What it is and what it does
Xpress is a Python binding to the FICO Xpress Optimizer, a commercial mathematical optimization solver. It lets you define and solve optimization problems—linear, quadratic, conic, and nonlinear, including mixed-integer variants—using Python syntax and NumPy integration. You construct problems by adding variables and constraints, set an objective function, and call optimize() to solve.
The package ships with precompiled binaries for modern Python versions and platforms (macOS, Linux, Windows). It includes a community license by default, so you can start solving problems without additional licensing setup. For GPU acceleration of the PDHG linear solver, you can install optional CUDA support. The underlying solver is the FICO Xpress library, which is maintained separately; this package is the Python interface to it.
Use it for
- Solve supply-chain optimization, production planning, or resource allocation problems modeled as linear or mixed-integer programs.
- Prototype and solve nonlinear optimization problems using Python without switching to a compiled language.
- Integrate optimization into data science workflows by combining NumPy arrays with Xpress problem definitions.
- Accelerate large-scale linear optimization on GPU-equipped systems using the PDHG solver with CUDA support.
- Develop and test optimization algorithms using Xpress callbacks and the Python interface for iterative refinement.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to solve mathematical optimization problems and have access to or can accept the Xpress license terms.
The package is actively maintained, supports modern Python versions, and offers broad problem-class coverage. Install friction is moderate due to compiled binaries, but wheels are widely available. The main caveat is license clarity—review the Xpress Shrinkwrap License Agreement before production deployment, especially for commercial use.
Install
xpress on PyPI
Before you install
Medium install friction due to compiled binary wheels; prebuilt wheels available for Python 3.10–3.14 across macOS (ARM64), Linux (x86_64, ARM64), and Windows. Maintenance is active with a release 42 days ago. Runtime dependency on numpy and xpresslibs (a compiled library package).
Requires FICO Xpress Optimizer library (xpresslibs); community license is included but commercial use or advanced features may require a separate license. Optional GPU support requires NVIDIA CUDA Runtime 13.0+ and drivers version 580+.
License in practice
License treatment is unclear; the package is governed by the Xpress Shrinkwrap License Agreement and includes a community license. A copy of the license is stored in LICENSE.txt in the dist-info directory. Users should review the shrinkwrap terms before deployment.
Quickstart
pip install xpress
import xpress as xp
p = xp.problem(name='myexample')
x1 = p.addVariable(vartype=xp.integer, name='x1', lb=-10, ub=10)
x2 = p.addVariable(name='x2')
p.setObjective(x1**2 + 2*x2)
p.addConstraint(x1 + 3*x2 >= 4)
p.optimize()
print(p.getSolution(x1), p.getSolution(x2))
Verify before relying
- Whether the community license has restrictions on problem size, solver features, or commercial use.
- Performance characteristics and solver algorithm selection for different problem classes.
- Support timeline and end-of-life dates for Python 3.10–3.14 versions.
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 2 packagesnumpyxpresslibs |
| Maintenance | Actively maintained 42 days since the last release |
| First released | |
| Downloads | 214,414 / month, #9,417 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: CProgramming Language :: C++Programming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Free Threading :: 2 - BetaTopic :: Scientific/EngineeringTopic :: Software Development |
Evidence: xpress-9.9.1-cp310-cp310-macosx_11_0_arm64.whl; xpress-9.9.1-cp310-cp310-manylinux1_x86_64.whl; xpress-9.9.1-cp310-cp310-manylinux2014_aarch64.whl; xpress-9.9.1-cp310-cp310-win_amd64.whl; xpress-9.9.1-cp311-cp311-macosx_11_0_arm64.whl; xpress-9.9.1-cp311-cp311-manylinux1_x86_64.whl; xpress-9.9.1-cp311-cp311-manylinux2014_aarch64.whl; xpress-9.9.1-cp311-cp311-win_amd64.whl; xpress-9.9.1-cp312-cp312-macosx_11_0_arm64.whl; xpress-9.9.1-cp312-cp312-manylinux1_x86_64.whl; xpress-9.9.1-cp312-cp312-manylinux2014_aarch64.whl; xpress-9.9.1-cp312-cp312-win_amd64.whl; xpress-9.9.1-cp313-cp313-macosx_11_0_arm64.whl; xpress-9.9.1-cp313-cp313-manylinux1_x86_64.whl; xpress-9.9.1-cp313-cp313-manylinux2014_aarch64.whl; xpress-9.9.1-cp313-cp313-win_amd64.whl; xpress-9.9.1-cp314-cp314-macosx_11_0_arm64.whl; xpress-9.9.1-cp314-cp314-manylinux1_x86_64.whl; xpress-9.9.1-cp314-cp314-manylinux2014_aarch64.whl; xpress-9.9.1-cp314-cp314t-macosx_11_0_arm64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “linear programming python”
- xpressPython interface to the FICO Xpress Optimizer for creating and…
- mipPython MIP models and solves mixed-integer linear programs (MIPs)…
- cvxoptcvxopt is a Python library for solving convex optimization problems,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Software Development packages
Provides backported and experimental type hints for Python 3.9+, allowing use of newer typing features on older Python versions and enabling early experimentation with type system PEPs before they enter the standard library.
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides a way to document function parameters, class attributes, return types, and variables inline using Python's `Annotated` type hint syntax instead of traditional docstrings.
Typer builds command-line applications from Python functions using type hints, automatically generating help text, argument parsing, and shell completion.
Install it if you are building CLIs in Python.
Distlib provides low-level packaging utilities for building, distributing, and managing Python software—including metadata handling, version specifiers, wheel support, script installation, and dependency resolution.
See also xpresslibs · pyomo · Mosek · optlang · amplpy · magiccube · cvxopt · docplex · PuLP · mip