Skip to main content
SAT Dependency Resolver Banner

SAT Dependency Resolver

Universal dependency resolution using Boolean Satisfiability (SAT) solvers

PyPI version Python 3.8+ License: MIT Live API

Live Demo • Installation • Quick Start • API Reference • Examples


🎯 Overview

SAT Dependency Resolver is a lightweight, mathematically precise tool that solves any dependency problem using Boolean Satisfiability (SAT) solvers.

It answers the question:

Given these goals/requirements and these available options with their dependencies, is there a valid combination?

  • ✅ If yes: Show one (or more valid solutions)
  • ❌ If no: Prove it's impossible and explain why (with optional AI help)

Why SAT?

  • Guaranteed correctness — Finds a solution if one exists, or proves none does (no heuristics)
  • Universal — Not limited to software packages. Works for courses, books, hardware, teams, recipes, scheduling, and more
  • Fast & lightweight — Built on PySAT + Glucose3 solver

✨ Features

Feature Description
SAT-based exact solving Uses Glucose3 solver for exhaustive, provably correct results
Conflict detection Clear, human-readable explanations of incompatibilities
AI recommendations Optional Claude AI suggestions for constraint relaxations or fixes
Flexible constraints Supports "any", ==, >=, <=, >, <, comma-separated ranges
REST API Simple JSON POST endpoint — call from any language/tool
Python library Import and use directly in your Python code
Live demo Try instantly at Heroku

📦 Installation

# Basic installation
pip install sat-dependency-resolver

Option 2: Install from Source

# Clone the repository
git clone https://github.com/Apollo87z/sat-dependency-resolver.git
cd sat-dependency-resolver

# Create virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Install in development mode
pip install -e .

🚀 Quick Start

Using as a Python Library

from sat_dependency_resolver import DependencyResolver

# Define your requirements
requirements = {
    "django": ">=4.0"
}

# Define available packages with their dependencies
available_packages = {
    "django": [
        {"version": "4.0", "requires": {"sqlparse": ">=0.3"}},
        {"version": "4.1", "requires": {"sqlparse": ">=0.4"}},
    ],
    "sqlparse": [
        {"version": "0.3", "requires": {}},
        {"version": "0.4", "requires": {}},
    ]
}

# Solve
resolver = DependencyResolver()
result = resolver.solve(requirements, available_packages)

# Check result
if result.is_satisfiable:
    print(f"✅ Solution found: {result.solution}")
    # Output: ✅ Solution found: {'django': '4.1', 'sqlparse': '0.4'}
else:
    print(f"❌ No solution. Conflicts: {result.conflicts}")

Using the REST API

Start the API Server (Local)

# If installed from PyPI
python -m sat_dependency_resolver.api

# Or if cloned from source
python run_api.py

API will be available at http://localhost:8091

Make a Request

curl -X POST http://localhost:8091/resolve \
  -H "Content-Type: application/json" \
  -d '{
    "requirements": {"django": ">=4.0"},
    "available_packages": {
      "django": [
        {"version": "4.0", "requires": {"sqlparse": ">=0.3"}},
        {"version": "4.1", "requires": {"sqlparse": ">=0.4"}}
      ],
      "sqlparse": [
        {"version": "0.3", "requires": {}},
        {"version": "0.4", "requires": {}}
      ]
    }
  }'

Response:

{
  "satisfiable": true,
  "solution": {
    "django": "4.1",
    "sqlparse": "0.4"
  },
  "conflicts": []
}

📚 Use Cases

Software Package Management

Resolve version conflicts for Python, npm, Cargo, RubyGems, etc.

requirements = {
    "package-a": "==1.0",
    "package-b": "==2.0"
}

Course Prerequisites

Plan your academic path with prerequisite constraints.

requirements = {
    "machine-learning": ">=1.0"
}
available_packages = {
    "machine-learning": [{
        "version": "1.0",
        "requires": {
            "linear-algebra": ">=1.0",
            "calculus": ">=1.0",
            "python": ">=1.0"
        }
    }],
    # ... other courses
}

Book Series / Reading Order

Find valid reading sequences for book series.

requirements = {
    "lotr-return-of-king": "any"
}
available_packages = {
    "lotr-return-of-king": [{
        "version": "1.0",
        "requires": {
            "lotr-two-towers": ">=1.0"
        }
    }],
    "lotr-two-towers": [{
        "version": "1.0",
        "requires": {
            "lotr-fellowship": ">=1.0"
        }
    }],
    # ... other books
}

Hardware Compatibility

Check if PC parts are compatible.

requirements = {
    "gpu": "rtx-4090",
    "cpu": "i9-13900k"
}
available_packages = {
    "gpu": [{
        "version": "rtx-4090",
        "requires": {
            "psu": ">=850w",
            "pcie": ">=4.0"
        }
    }],
    # ... other components
}

🌐 API Reference

Base URLs

  • Live (Production): https://sat-dependency-resolver.shehan.io
  • Local Development: http://localhost:8091

Endpoints

GET /health

Check if the API is running.

Response:

{
  "status": "ok",
  "message": "SAT Dependency Resolver API"
}

GET /info

Get API information and version.

Response:

{
  "name": "SAT Dependency Resolver",
  "version": "0.1.1",
  "description": "Universal dependency resolver using SAT solvers"
}

POST /resolve

Resolve dependencies and return a solution or conflicts.

Headers:

  • Content-Type: application/json (required)
  • X-API-Key: sk-ant-... (optional, required only if use_ai: true)

Request Body:

{
  "requirements": {
    "package-name": "constraint"
  },
  "available_packages": {
    "package-name": [
      {
        "version": "1.0.0",
        "requires": {
          "dependency": "constraint"
        }
      }
    ]
  },
  "use_ai": false
}

Constraint Syntax:

  • "any" — No restriction
  • "==1.2.3" — Exact version
  • ">=1.0" — Greater than or equal
  • "<=2.0" — Less than or equal
  • ">1.5" — Greater than
  • "<2.0" — Less than
  • ">=1.0,<2.0" — Range (comma = AND)

Response (Success):

{
  "satisfiable": true,
  "solution": {
    "package-name": "1.0.0",
    "dependency": "2.0.0"
  },
  "conflicts": []
}

Response (Conflict):

{
  "satisfiable": false,
  "solution": null,
  "conflicts": [
    "package-a requires dependency==1.0 but package-b requires dependency==2.0"
  ],
  "recommendation": "Try relaxing constraint on dependency to >=1.0,<3.0"
}

🧪 Examples

Example 1: Basic Resolution

from sat_dependency_resolver import DependencyResolver

requirements = {"A": ">=2.0"}
available_packages = {
    "A": [
        {"version": "1.0", "requires": {}},
        {"version": "2.0", "requires": {"B": ">=1.0"}},
        {"version": "3.0", "requires": {"B": ">=2.0"}}
    ],
    "B": [
        {"version": "1.0", "requires": {}},
        {"version": "2.0", "requires": {}}
    ]
}

resolver = DependencyResolver()
result = resolver.solve(requirements, available_packages)
print(result.solution)
# Output: {'A': '3.0', 'B': '2.0'}

Example 2: Conflict Detection

requirements = {
    "package-a": "==1.0",
    "package-b": "==1.0"
}
available_packages = {
    "package-a": [
        {"version": "1.0", "requires": {"shared": "==1.0"}}
    ],
    "package-b": [
        {"version": "1.0", "requires": {"shared": "==2.0"}}
    ],
    "shared": [
        {"version": "1.0", "requires": {}},
        {"version": "2.0", "requires": {}}
    ]
}

resolver = DependencyResolver()
result = resolver.solve(requirements, available_packages)
print(f"Satisfiable: {result.is_satisfiable}")
print(f"Conflicts: {result.conflicts}")
# Output: Satisfiable: False
#         Conflicts: ["can't resolve - probably circular deps or version mismatch"]

Example 3: Using AI Recommendations

from sat_dependency_resolver import DependencyResolver

requirements = {"django": ">=5.0"}  # No version 5.0 available
available_packages = {
    "django": [
        {"version": "4.0", "requires": {}},
        {"version": "4.1", "requires": {}}
    ]
}

resolver = DependencyResolver()
result = resolver.solve(
    requirements, 
    available_packages,
    use_ai=True,
    api_key="sk-ant-your-key-here"
)

if not result.is_satisfiable:
    print(f"AI Recommendation: {result.recommendation}")
    # Output: AI suggestions for fixing the constraint

Example 4: REST API with curl

Successful Resolution:

curl -X POST http://localhost:8091/resolve \
  -H "Content-Type: application/json" \
  -d '{
    "requirements": {"python": ">=3.8"},
    "available_packages": {
      "python": [
        {"version": "3.8", "requires": {}},
        {"version": "3.9", "requires": {}},
        {"version": "3.10", "requires": {}}
      ]
    }
  }'

With Conflicts:

curl -X POST http://localhost:8091/resolve \
  -H "Content-Type: application/json" \
  -d '{
    "requirements": {
      "app": "==1.0"
    },
    "available_packages": {
      "app": [
        {"version": "1.0", "requires": {"lib": "==1.0"}},
        {"version": "2.0", "requires": {"lib": "==2.0"}}
      ],
      "lib": [
        {"version": "2.0", "requires": {}}
      ]
    }
  }'

🧪 Running Tests

Basic Test Suite

# Run quick tests
python tests/test_quick.py

Create Your Own Test

Create test_custom.py:

from sat_dependency_resolver import DependencyResolver

def test_my_scenario():
    requirements = {
        "my-package": ">=1.0"
    }
    available_packages = {
        "my-package": [
            {"version": "1.0", "requires": {}}
        ]
    }
    
    resolver = DependencyResolver()
    result = resolver.solve(requirements, available_packages)
    
    assert result.is_satisfiable == True
    assert "my-package" in result.solution
    print("✅ Test passed!")

if __name__ == "__main__":
    test_my_scenario()

Run it:

python test_custom.py

🔧 Development

Project Structure

sat-dependency-resolver/
├── sat_dependency_resolver/
│   ├── __init__.py          # Package exports
│   ├── encoder.py           # SAT encoding logic
│   ├── resolver.py          # Main resolver
│   ├── api.py              # Flask REST API
│   └── ai_agent.py         # AI recommendations (optional)
├── examples/
│   ├── basic_usage.py
│   ├── courses.py
│   └── api_example.sh
├── tests/
│   └── test_quick.py
├── run_api.py              # API entry point
├── requirements.txt
├── setup.py
├── README.md
└── LICENSE

Running Locally

# Clone and setup
git clone https://github.com/Apollo87z/sat-dependency-resolver.git
cd sat-dependency-resolver
python -m venv venv
source venv/bin/activate
pip install -e ".[api,ai]"

# Run API
python run_api.py

# Run tests
python tests/test_quick.py

🤝 Contributing

Contributions are welcome! Here's how:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.


🙋 Support


🌟 Acknowledgments

  • Built with PySAT and Glucose3 solver
  • Optional AI powered by Anthropic Claude
  • Inspired by the need for universal, mathematically sound dependency resolution

Made by Shehan Horadagoda

⭐ Star this repo if you find it useful!

Metadata

Release files for sat-dependency-resolver 0.1.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sat-dependency-resolver 0.1.7
File Size Uploaded Provenance
sat_dependency_resolver-0.1.7.tar.gz 15.3 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for sat-dependency-resolver 0.1.7
File Interpreter ABI Platform
sat_dependency_resolver-0.1.7-py3-none-any.whl Python 3 none any Details

Total release size: 28.3 kB

Release files / sat_dependency_resolver-0.1.7.tar.gz

Download URL sat_dependency_resolver-0.1.7.tar.gz
Size 15.3 kB
Tags Source
SHA-256 checksum
How to use checksums
7558f353583c65bcbc4b5b70c8adac86c0ada7beeb64584e8965395d9113f2cf
BLAKE2b-256 checksum
How to use checksums
a2fc18b40519f149bb1eb4bb836c5cd9e57eb31188b436c6f2401fc368519c42
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.8

Release files / sat_dependency_resolver-0.1.7-py3-none-any.whl

Download URL sat_dependency_resolver-0.1.7-py3-none-any.whl
Size 13.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8e4fcc9f1e5cf0882d4f3182e3f0b511c16d884a0da316722b984f90b0704bfa
BLAKE2b-256 checksum
How to use checksums
da1ffcf49c23ee0b18d0a0d27aa072843332d974d3b17f76af7ff78dcebdba3a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.8

Security for sat-dependency-resolver 0.1.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page