README.md

metadata

title: Python Dependency Compatibility Board
emoji: 🐍
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.0.0
app_file: app.py
pinned: false
license: mit

🐍 Python Dependency Compatibility Board

A powerful tool to analyze and resolve Python package dependencies. Check for version conflicts, compatibility issues, and generate clean requirements.txt files.

✨ Features

• Multiple Input Methods: Library list, requirements.txt paste, or file upload
• Conflict Detection: Automatically detects version conflicts and compatibility issues
• 🤖 AI-Powered Explanations: Uses LLM to generate intelligent, natural language explanations for conflicts (with fallback to rule-based)
• Dependency Resolution: Uses pip's resolver to find compatible versions
• Environment Aware: Configure Python version, device (CPU/GPU), and OS
• Analysis Modes: Quick (top-level) or Deep (with transitive dependencies)
• Resolution Strategies: Latest compatible, stable/pinned, keep existing, or minimal changes
• Spell Checking: Auto-corrects common spelling mistakes in package names
• Validation Utilities: Benchmark against the bundled synthetic dataset and generate perturbed requirements for stress testing

🚀 How to Use

Input Your Dependencies

You can provide dependencies in three ways:

1. Library List: Enter package names one per line

   pandas
   torch
   langchain
   fastapi
   

2. Requirements Text: Paste your existing requirements.txt

   pandas==2.0.3
   torch>=2.0.0
   langchain==0.1.0
   

3. File Upload: Upload a requirements.txt file directly

Configure Environment

• Python Version: Select your target Python version (3.8-3.12)
• Device: CPU only, NVIDIA GPU (CUDA), Apple Silicon (MPS), or Custom
• Operating System: Any, Linux, Windows, or macOS

Analysis & Resolution

1. Choose Analysis Mode:

   • Quick: Fast analysis of top-level dependencies
   • Deep: Complete dependency tree with transitive dependencies

2. Select Resolution Strategy:

   • latest_compatible: Resolve to latest compatible versions
   • stable/pinned: Prefer stable, pinned versions
   • keep_existing_pins: Preserve your existing version pins
   • minimal_changes: Make minimal changes to resolve conflicts

3. Click "Analyze & Resolve Dependencies"

4. Review the results and download your resolved requirements.txt

🔍 What It Detects

The tool automatically detects:

• Duplicate Packages: Same package specified multiple times with conflicting versions
• PyTorch Compatibility: Ensures pytorch-lightning>=2.0 works with torch>=2.0
• FastAPI/Pydantic: Checks version compatibility (e.g., fastapi 0.78.x requires pydantic v1)
• TensorFlow/Keras: Validates TensorFlow/Keras version pairs
• Version Conflicts: Identifies incompatible version specifications

🤖 AI Explanations

When enabled, the tool uses LLM reasoning to provide:

• Clear Explanations: Natural language descriptions of what the conflict is
• Why It Happens: Technical reasons behind the conflict
• How to Fix: Actionable solutions with specific version recommendations

The LLM explanations use Hugging Face Inference API (free tier) and automatically fall back to rule-based explanations if the API is unavailable.

📋 Example

Input:

torch==1.8.0
pytorch-lightning==2.2.0
pandas==2.0.3

Output:

⚠️ Compatibility Issues Found:
- pytorch-lightning>=2.0 requires torch>=2.0, but torch<2.0 is specified

Resolved requirements.txt:
torch==2.1.0
pytorch-lightning==2.2.0
pandas==2.0.3
...

🛠️ Technical Details

• Built with Gradio
• Uses packaging library for version parsing
• Leverages pip's dependency resolver
• Supports PEP 508 requirement specifications

📝 Notes

• Full dependency resolution requires pip >= 22.2
• Deep mode may take longer for large dependency sets
• The tool works best with packages available on PyPI
• Platform-specific dependencies (e.g., CUDA) are detected but resolution may vary
• Run python validation_tools.py to benchmark the built-in compatibility checks against synthetic cases.
• Use python scripts/perturb_requirements.py --help to generate noisy/invalid requirements for robustness testing.

🤝 Contributing

Feel free to test the tool and report any issues! This tool is designed to help developers manage Python dependencies more effectively.

📄 License

MIT License - feel free to use and modify as needed.

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Made with ❤️ for the Python community