py-veripy 0.1.1

A production-ready auto-active verification system for Python, similar to Dafny and Verus

Veripy

A production-ready auto-active verification system for Python, similar to Dafny and Verus.

Overview

Veripy transforms Python code verification from a work-in-progress into a production-ready system with automatic invariant inference, comprehensive error reporting, and a professional CLI.

Soundness note

Veripy is not sound for full Python today. The core VC engine is intended to be sound for a restricted, “verification-oriented” subset (roughly: side-effect-free code over int/bool plus mathematical arrays, with structured if/while, and user-supplied invariants), and it rejects or approximates many Python features (exceptions, dynamic dispatch, aliasing/mutation semantics of real lists/dicts/objects, etc.).

Recent work is moving toward a Dafny/Boogie-style explicit heap model for aliasing + mutation (lists/dicts/fields as references) and for exception safety (e.g., bounds and div/mod by zero become proof obligations). This is still a work in progress and many Python features remain unsupported.

Key Features

Auto-Active Verification

• Automatic loop invariant inference
• Type-based constraint generation
• Arithmetic lemma automation
• Multiple inference strategies (NONE, SIMPLE, AGGRESSIVE, FULL)

Production Readiness

• Professional CLI with multiple commands
• Rich terminal output with syntax highlighting
• JSON output for CI/CD
• Comprehensive error reporting with counterexamples
• Source location tracking

Recursive Functions

• Termination checking with decreases clauses
• Tail recursion detection
• Call graph analysis

Installation

pip install py-veripy

For development:

make install-dev

Usage

Basic Verification

import veripy as vp

vp.enable_verification()

@vp.verify(requires=['x > 0'], ensures=['ans == x * 2'])
def double(x: int) -> int:
    return x * 2

vp.verify_all()

Deppy-Style Contracts

import veripy as vp

vp.enable_verification()
vp.scope("demo")

@vp.verify()
@vp.requires("x > 0")
@vp.guarantee("result > x")
def succ(x: int) -> int:
    return x + 1

vp.verify_all()

Veripy normalizes Deppy-style result postconditions to its internal ans binding and also exposes lightweight sidecar metadata helpers such as @vp.about(...), @vp.proof_for(...), and @vp.z3_hint(...).

Lean4 Export

import veripy as vp

@vp.verify(requires=["x > 0"], ensures=["ans > x"])
def succ(x: int) -> int:
    return x + 1

cert = vp.compile_to_lean(succ)
print(cert.render())

# Optional, if Lean is installed locally:
# cert.verify_with_lean()

The Lean backend now exports Veripy's actual heap-lowered VC obligations rather than re-translating raw Python syntax. In practice that means the generated Lean theorems track the same pre => wp and side-condition formulas the SMT backend checks, including summary assumptions for verified callees and explicit heap state binders when lists/dicts/fields are involved.

CLI Usage

# Verify files
veripy verify file.py

# With counterexamples and statistics
veripy verify --counterexample --statistics file.py

# JSON output for CI/CD
veripy verify --output json file.py

Auto-Active Features

from veripy.auto_active import auto_infer_invariants

invariants = auto_infer_invariants({
    "loop_var": "i",
    "init": 0,
    "condition": "i < n",
    "body": []
})

Architecture

veripy/
├── core/           # Verification condition generation, AST transformation
├── auto_active/    # Auto-active features (invariant inference, lemmas)
├── cli/            # Command-line interface
├── parser/         # Syntax parsing
├── typecheck/      # Type checking
├── error_reporter.py
├── recursive.py
└── prettyprint.py

Development

make test          # Run tests
make test-cov      # With coverage
make lint          # Linting
make format        # Formatting
make typecheck     # Type checking
make check         # All checks

Dependencies

• z3-solver - SMT solver
• rich - Terminal output
• click - CLI framework
• pyparsing - Expression parsing
• apronpy - Abstract interpretation

Related Work

• Nagini: https://github.com/marcoeilers/nagini