PyPM - Python Package Manager

True version isolation with zero duplication - Multiple package versions coexist, environments use specific versions!

🚀 Quick Start

# Install PyPM
pip install pypm-manager

# Create environment  
pypm create myproject

# Activate it
pypm activate myproject  # Shows activation command
# Run the activation command shown

# Install packages with version isolation
pypm install pandas numpy scikit-learn

# Deactivate when done
deactivate

✨ The Problem PyPM Solves

Problem 1 - Duplication:

project1/venv/ → pandas 1.5.0 (100 MB)
project2/venv/ → pandas 1.5.0 (100 MB)  [DUPLICATE!]
project3/venv/ → pandas 1.5.0 (100 MB)  [DUPLICATE!]
Total: 300 MB wasted

Problem 2 - Version Conflicts:

project1 needs requests 2.28.0
project2 needs requests 2.31.0
❌ Can't have both with venv/conda!

With PyPM v2.1:

~/.pypm_central/packages/
  ├── requests/2.28.0/  [Version 1]
  ├── requests/2.31.0/  [Version 2]
  └── pandas/1.5.0/     [Shared dependency - stored once!]

✅ Both versions coexist
✅ Environments use specific versions
✅ Shared dependencies stored once
Total: Zero duplication + True isolation!

🎯 How It Works

1. Create: pypm create myenv - Creates lightweight environment
2. Activate: pypm activate myenv - Shows activation command
3. Install: pypm install pandas==1.5.0 - Stores in version-specific directory
4. Isolation: Each environment's PYTHONPATH points to its specific package versions

📦 Installation

pip install pypm-manager

🔧 Commands

# Environment Management
pypm create <name>         # Create environment
pypm activate <name>       # Show activation command
pypm install <package>     # Install with version isolation
deactivate                 # Deactivate current environment
pypm delete <name>         # Delete environment
pypm list                  # List all environments
pypm info <name>           # Show environment details

# Central Store
pypm store-info            # View central store stats

💡 Complete Example

# Create data science environment
pypm create datascience
pypm activate datascience
# Run activation command shown (e.g., C:\...\datascience\Scripts\Activate.ps1)

# Install packages with specific versions
pypm install pandas==2.1.0 numpy scikit-learn

# Work on your project...
python my_analysis.py

# Deactivate
deactivate

# Create another project with different pandas version
pypm create ml-project
pypm activate ml-project
# Activate...

pypm install pandas==2.3.0 tensorflow
# ✅ Both pandas 2.1.0 and 2.3.0 coexist!
# ✅ numpy/scikit-learn shared between projects

🌟 Features

• ✅ True version isolation - Multiple package versions coexist
• ✅ Environment-specific versions - Each env uses its own package versions
• ✅ Zero duplication - Shared dependencies stored once
• ✅ Familiar workflow - Similar to venv activation
• ✅ Cross-platform - Windows, macOS, Linux
• ✅ No dependencies - Pure Python stdlib

🆚 vs Other Tools

📁 Storage Locations

• Environments: ~/.pypm_envs/
• Versioned packages: ~/.pypm_central/packages/{name}/{version}/
• Environment configs: {env}/.pypm_requirements.json

🤝 Contributing

https://github.com/Avishek8136/pypm

📜 License

MIT License

PyPM v2.1 - True version isolation with zero duplication! 🎉