PyCSP3: Modeling Combinatorial Constrained Problems in Python
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Abstract (arXiv)
In this document, we introduce PyCSP3, a Python library that allows us to write models of combinatorial constrained problems in a declarative manner. Currently, with PyCSP3, you can write models of constraint satisfaction and optimization problems. More specifically, you can build CSP (Constraint Satisfaction Problem) and COP (Constraint Optimization Problem) models. Importantly, there is a complete separation between the modeling and solving phases: you write a model, you compile it (while providing some data) in order to generate an XCSP3 instance (file), and you solve that problem instance by means of a constraint solver. You can also directly pilot the solving procedure in PyCSP3, possibly conducting an incremental solving strategy. In this document, you will find all that you need to know about PyCSP3, with more than 50 illustrative models.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Sep 2020.
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Citing papers per year: 2022: 1; 2023: 3; 2024: 0; 2025: 2; 2026: 3.
9 papers.
- 2025ConstraintLLM: A Neuro-Symbolic Framework for Industrial-Level Constraint Programmingcited by 10
- 2023ACE, a generic constraint solvercited by 3
- 2025DCP-Bench-Open: Evaluating LLMs for Constraint Modelling of Discrete Combinatorial Problemscited by 3
- 2022Proceedings of the 2022 XCSP3 Competitioncited by 2
- 2026Formalize, Don't Optimize: The Heuristic Trap in LLM-Generated Combinatorial Solverscited by 2
- 2023Proceedings of the 2023 XCSP3 Competitioncited by 1
- 2023Solving the Kidney-Exchange Problem via Graph Neural Networks with No Supervisioncited by 0
- 2026MathConstraint: Automated Generation of Verified Combinatorial Reasoning Instances for LLMscited by 0
- 2026PyCSP3-Scheduling: A Scheduling Extension for PyCSP3cited by 0
- 2026PyCSP3-Scheduling: A Scheduling Extension for PyCSP314 May 2026
- 2026Formalize, Don't Optimize: The Heuristic Trap in LLM-Generated Combinatorial Solvers12 May 2026
- 2026MathConstraint: Automated Generation of Verified Combinatorial Reasoning Instances for LLMs8 May 2026
- 2025ConstraintLLM: A Neuro-Symbolic Framework for Industrial-Level Constraint Programming7 Oct 2025
- 2025DCP-Bench-Open: Evaluating LLMs for Constraint Modelling of Discrete Combinatorial Problems6 Jun 2025
- 2023Proceedings of the 2023 XCSP3 Competition10 Dec 2023
- 2023Solving the Kidney-Exchange Problem via Graph Neural Networks with No Supervision19 Apr 2023
- 2023ACE, a generic constraint solver6 Jan 2023
- 2022Proceedings of the 2022 XCSP3 Competition2 Sep 2022