CPMpy: Constraint Programming and Modeling in Python

Source code and issue tracker: https://github.com/CPMpy/cpmpy

CPMpy is ideal for solving combinatorial problems like assignment problems or covering, packing and scheduling problems. Problems that require searching over discrete decision variables.

Getting started:

• Modeling and solving with CPMpy
• Summary sheet

Supported solvers

Solver	Technology	Capabilities	Installation	Notes
OR-Tools	CP (LCG)	SAT ASAT ALLSAT - OPT - PAR	pip	The default solver
Pumpkin	CP (LCG)	SAT ASAT ALLSAT - OPT - PROOF	local install (maturin)
GCS	CP	SAT ISAT ALLSAT - OPT - PROOF	pip
Choco	CP	SAT ISAT ALLSAT - OPT	pip
CP Optimizer	CP	SAT - OPT - PAR	pip + local + (aca.) license
MiniZinc	CP	SAT - OPT	pip + local install	Communicates through textfiles
Z3	SMT	SAT ASAT ISAT - OPT	pip
Hexaly	Global Opt.	SAT ISAT ALLSAT - OPT IOPT	pip + local + (aca.) licence
Gurobi	ILP	SAT ISAT - OPT IOPT - PAR	pip + (aca.) license
CPLEX	ILP	SAT - OPT IOPT - PAR	pip + local + (aca.) license	No
Exact	Pseudo-Boolean	SAT ASAT ISAT ALLSAT - OPT IOPT - PROOF	pip >3.10 (Linux, Win)	Manual installation on Mac possible
RC2	MaxSAT	OPT	pip
Pindakaas	SAT	SAT ASAT ISAT	pip	Automatically encodes PB to SAT
PySAT	SAT	SAT ASAT ISAT	pip
PySDD	Decis. Diagram	SAT ISAT ALLSAT - KC	pip	only Boolean variables (CPMpy transformation incomplete)

Native capability abbreviations:

• SAT: Satisfaction, ASAT: Satisfaction under Assumptions+core extraction, ISAT: Incremental Satisfaction, ALLSAT: All solution enumeration

• OPT: Optimisation, IOPT: Incremental optimisation

• PAR: Parallel solving, PROOF: Proof logging, KC: Knowledge Compilation

Different solvers excel at different problems. Try multiple!

CPMpy’s transformations selectively rewrite only those constraint expressions that a solver does not support. While solvers can use any transformation they need, lower-level solvers largely reuse those of higher-level ones, creating a waterfall pattern:

Advanced guides:

• How to debug
• Obtaining multiple solutions
• Solving with assumptions
• Developer guide
• Adding a new solver
• Test Suite

Open Source

CPMpy is open source (Apache 2.0 license) and the development process is open too: all discussions happen on GitHub, even between direct colleagues, and all changes are reviewed through pull requests.

Join us! We welcome any feedback and contributions. You are also free to reuse any parts in your own project. A good starting point to contribute is to add your models to the examples folder.

Are you a solver developer? We are keen to integrate solvers that have a python API on pip. If this is the case for you, or if you want to discuss what it best looks like, do contact us!

API documentation:

• Model (cpmpy.model)
• Expressions (cpmpy.expressions)
• Expression transformations (cpmpy.transformations)
• Solver interfaces (cpmpy.solvers)
• Tools (cpmpy.tools)