---
id: claripy
version: "9.3.2"
license: BSD-2-Clause
license_treatment: permissive
maintenance: active
---

# claripy — An abstraction layer for constraint solvers

License: permissive · Maintenance: active · Downloads: 900.4K/mo

## What it is and what it does

Claripy is a constraint-solving abstraction layer that sits between your code and underlying solvers like Z3. It provides a unified interface for building and solving symbolic constraints over bit-vectors and other domains, shielding you from solver-specific APIs. The package is part of the angr ecosystem and is commonly used in symbolic execution, program analysis, and formal verification workflows.

You define symbolic variables and concrete values, add constraints to a solver, and then query the solver for satisfying assignments. The abstraction lets you swap solvers or combine multiple backends without rewriting constraint-building logic. With active maintenance, support for modern Python versions, and only two runtime dependencies, it integrates cleanly into analysis pipelines.

Use it for:

- Symbolic execution: Build and solve path constraints in program analysis without solver-specific code.
- Formal verification: Express and verify properties of systems using bit-vector constraints and symbolic reasoning.
- Constraint-based testing: Generate test inputs by solving constraints over program variables.
- Program analysis: Reason about reachability and feasibility of code paths in static or dynamic analysis.
- Reverse engineering: Solve for inputs that satisfy observed program behavior or constraints.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Claripy is an abstraction layer for constraint solvers that wraps Z3 and other backends, letting you build and solve symbolic constraints over bit-vectors and other domains without being tied to a specific solver implementation.

Yes, if you need constraint solving in program analysis, symbolic execution, or formal verification. The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive license. It is well-suited for researchers and practitioners working with symbolic reasoning or the angr framework. Not necessary for general-purpose applications.

## Install

pip install claripy
uv add claripy
poetry add claripy

## Installing claripy

Before you install: Installation is straightforward with only two runtime dependencies (cachetools and z3-solver). The package is actively maintained with a recent release and steady commit activity, supporting current Python versions (3.12, 3.13, 3.14).

License in practice: BSD-2-Clause is a permissive license allowing broad use, modification, and distribution with minimal restrictions—suitable for most projects including commercial ones.

Quickstart:

pip install claripy

import claripy
a = claripy.BVV(3, 32)
b = claripy.BVS('var_b', 32)
s = claripy.Solver()
s.add(b > a)
print(s.eval(b, 1)[0])

Requires Python 3.12 or later; z3-solver must be installed as a runtime dependency.

Verify before relying:

- Whether claripy supports constraint solvers other than Z3 as backends, or if Z3 is the primary/only solver currently wrapped.
- Performance characteristics when solving large constraint systems or handling complex symbolic expressions.

## Package facts

- License: BSD-2-Clause (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 900.4K/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

constraint solver wrapper, symbolic execution constraints, z3 abstraction layer, bit-vector constraint solving, solver-agnostic constraints, symbolic-execution, constraint-solving, program-analysis

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