mip
Python tools for Modeling and Solving Mixed-Integer Linear Programs (MIPs)
Decision gist · record as of 2026-08-14
Yes, if you need to model and solve mixed-integer linear programs in Python. The package is actively maintained, has low install friction, supports current Python versions, and offers a clean API with advanced solver features. The EPL-2.0 copyleft license requires compliance in derivative works. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or newer; cbcbox solver dependency must be available
- Low install friction with a pure-wheel distribution.
- The package is actively maintained (last commit 2026-06-09) and in production-stable status.
License · maintenance · safety
copyleft license (copyleft) — Licensed under Eclipse Public License 2.0 (EPL-2.0), a copyleft license. You may use and modify the package freely, but derivative works and distributions must carry the same license terms and include a copy of the EPL-2.0 agreement.
last release 2026-03-23 (144 days) · last repo commit 2026-06-09 · 597 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 605,067 downloads/mo, #5,800 on PyPI
Alternatives
Verify before relying
pip install mip
from mip import Model, xsum, BINARY
m = Model()
x = [m.add_var(var_type=BINARY) for _ in range(10)]
m.objective = xsum(x)
m.optimize()- Whether cbcbox is automatically installed or requires separate system-level solver setup
- Performance comparison claims and their test conditions
- Compatibility with Gurobi solver integration beyond CBC
What it is and what it does
Python MIP is a modeling and solving toolkit for mixed-integer linear programs, designed to make it easy to write optimization problems in Python using operator overloading and a high-level syntax. It communicates directly with native solver libraries via cffi, supporting both the open-source CBC solver and the commercial Gurobi solver with a single, solver-independent codebase.
The package provides advanced features like cut generation, lazy constraints, solution pools, and MIPStart heuristics for warm-starting searches. It requires Python 3.10 or newer and runs on CPython and PyPy. The main dependencies are cffi and cbcbox.
Use it for
- Model and solve supply chain optimization, production scheduling, or resource allocation problems using a Pythonic syntax
- Implement branch-and-cut algorithms with custom cut generators and lazy constraint callbacks for large-scale MIPs
- Migrate optimization models from existing codebases by leveraging compatible syntax and solver-agnostic code
- Explore multiple near-optimal solutions via solution pools during MIP search
- Accelerate MIP model creation on PyPy for performance-critical applications
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to model and solve mixed-integer linear programs in Python.
The package is actively maintained, has low install friction, supports current Python versions, and offers a clean API with advanced solver features. The EPL-2.0 copyleft license requires compliance in derivative works. No known security vulnerabilities.
Install
mip on PyPI
Before you install
Low install friction with a pure-wheel distribution. The package is actively maintained (last commit 2026-06-09) and in production-stable status. Runtime depends on cffi and cbcbox.
Requires Python 3.10 or newer; cbcbox solver dependency must be available
License in practice
Licensed under Eclipse Public License 2.0 (EPL-2.0), a copyleft license. You may use and modify the package freely, but derivative works and distributions must carry the same license terms and include a copy of the EPL-2.0 agreement.
Quickstart
pip install mip
from mip import Model, xsum, BINARY
m = Model()
x = [m.add_var(var_type=BINARY) for _ in range(10)]
m.objective = xsum(x)
m.optimize()Verify before relying
- Whether cbcbox is automatically installed or requires separate system-level solver setup
- Performance comparison claims and their test conditions
- Compatibility with Gurobi solver integration beyond CBC
Package facts
| License | copyleft license copyleft |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagescfficbcbox |
| Maintenance | Actively maintained 144 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 605,067 / month, #5,800 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/StableLicense :: OSI Approved :: Eclipse Public License 2.0 (EPL-2.0)Operating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Scientific/Engineering :: Mathematics |
Evidence: mip-1.17.6-py3-none-any.whl
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See also cylp · gurobipy · linopy · PuLP · ortools · cbcbox · pyomo · amplpy · docplex · clingo