A next-generation code optimization framework that combines quantum-inspired patterns with Unicode optimization to create highly efficient, machine-first Python code. QUMO leverages quantum computing principles, advanced AST/CST transformations, and Unicode patterns to optimize Python code for both machine processing and human readability.
- 🔄 Quantum-inspired code transformations
- 🔤 Unicode pattern optimization
- 📊 Graph-based flow analysis
- 🔍 AST and CST transformations
- 🎯 Machine-first optimization principles
- 🛠️ Command-line interface with rich output
# From GitHub
git clone https://github.com/abcdqfr/qumo.git
cd qumo
pip install -e .
# Or via pip
pip install git+https://github.com/abcdqfr/qumo.git
Optimize a Python file:
qumo optimize input.py -o output.py
Show diff between original and optimized code:
qumo optimize input.py --diff
Show version:
qumo version
from qumo import optimize_code
# Optimize code
source = '''
def calculate(x, y):
return x + y
'''
optimized = optimize_code(source)
print(optimized)
- Self reference:
ꜱ
- Path handling:
ᴘ
- Window/UI:
ᴡ
- List operations:
ʟ
- Quantum state:
ψ
- Bra-Ket notation:
⟨ψ|H|ψ⟩
- Tensor product:
⊗
- Direct sum:
⊕
- Conjugate:
†
- Implies:
⇒
- Maps to:
↦
- Composition:
∘
- Universal quantifier:
∀
- Existential quantifier:
∃
# Clone repository
git clone https://github.com/brandon/qumo.git
cd qumo
# Install dependencies
pip install -e ".[dev]"
pytest
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
MIT License - see LICENSE for details
- Inspired by quantum computing principles
- Built with modern Python tooling
- Powered by libcst, ast, sympy, and networkx