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xpress

FICO Xpress Optimizer Python interface

With conditionsPyPI Software DevelopmentReleased Jul 2026214.4K downloads / moPlatform wheel

Decision gist · record as of 2026-08-14

platform wheels — 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
v9.9.1 · released 2026-07-03 · 2 runtime deps: numpy, xpresslibs

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

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.
Same gist for agents: .md · .json

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.

With conditions

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

LicenseNot declared unclear
Python supportNot specified
Install frictionMedium. Platform-specific wheel
Runtime dependencies
2 packages
numpyxpresslibs
MaintenanceActively maintained 42 days since the last release
First released
Downloads214,414 / month, #9,417 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone 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

Capabilities
mathematical optimization solverlinear programming pythonmixed-integer programmingnonlinear optimizationquadratic programming solverMILP MIQP solverconic programming
Topics
optimization-solvermixed-integer-programmingnumerical-computing
PyPI keywords
optimizationmipminlpxpress

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See also xpresslibs · pyomo · Mosek · optlang · amplpy · magiccube · cvxopt · docplex · PuLP · mip