Knuckledragger, a Semi-Automated Python Proof Assistant
The "Knuckledragger" project is a semi-automated Python proof assistant based on Z3, focusing on usability and various mathematical theories, with open-source code and documentation available on GitHub.
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The "Knuckledragger" project is a semi-automated Python proof assistant based on the Z3 theorem prover, developed over the past six months. The project aims to create a lightweight framework that facilitates the chaining of calls to automated theorem provers while maintaining usability. Key features include the implementation of various mathematical theories such as natural numbers, complex numbers, and linear algebra, along with convenience systems for tactics and induction principles. The design leverages Z3's rich API, allowing users familiar with Z3 to easily adapt to Knuckledragger. The core of the system includes a Proof datatype, which is constructed through functions like axiom and lemma, and a mechanism for defining new functions. The project emphasizes an example-driven approach, focusing on practical applications of theorems and definitions. Current work involves refining the handling of natural numbers, lists, and real numbers, with considerations for induction principles and recursive definitions. The project is open-source, with documentation and tutorials available on its GitHub repository.
- Knuckledragger is a semi-automated proof assistant built on Z3.
- It focuses on usability by minimizing code while leveraging Z3's capabilities.
- The project includes various mathematical theories and convenience systems for theorem proving.
- It emphasizes an example-driven approach to development and application.
- The source code and documentation are available on GitHub.
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4 commentsIs this trying to prove things about Python code, or is it a Python interface to Z3, or something else?
All of these seem to find solutions to user-provided constraint sets. They must be appropriate for different classes of problems, but it’s not obvious to me how that breaks out.
It’s, uh, been a long time since I last hand-rolled an optimization algorithm…
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