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optimiz-rs/LINKEDIN_POST.md
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ThotDjehuty e93d43f290 feat: Publish to crates.io and prepare PyPI publication
crates.io:

- Successfully published optimizr v1.0.0

- Available at: https://crates.io/crates/optimizr

PyPI Preparation:

- Renamed package to optimizr-rs (avoid name conflict)

- Updated pyproject.toml with new name

- Built wheel: optimizr_rs-1.0.0-cp38-abi3-macosx_10_12_x86_64.whl

- Ready for upload (need API token)

Documentation Updates:

- Updated RELEASE_NOTES with crates.io link

- Updated README.md installation instructions

- Updated LINKEDIN_POST.md with correct package names

- Created PYPI_PUBLISHING.md with token instructions

Next: Get PyPI API token and run twine upload
2026-02-17 09:30:20 +01:00

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🚀 OptimizR v1.0.0 is LIVE! 🚀

I'm thrilled to announce the first stable release of OptimizR - a high-performance Rust library for optimization and statistical inference! 🎉

📦 What is OptimizR?

OptimizR brings blazing-fast implementations of advanced algorithms to data science: • Differential Evolution (5 strategies with adaptive jDE) • Hidden Markov Models (Baum-Welch, Viterbi) • MCMC Sampling (Metropolis-Hastings) • Mean Field Games (PDE solvers) • Information Theory tools

The Performance Story: • 50-100× faster than pure Python • 95% memory reduction vs NumPy/SciPy • Production-ready with comprehensive testing

🔥 Real-World Benchmarks: • HMM Training: 0.03s (Rust) vs 2.4s (Python) = 80× speedup • Differential Evolution: 0.12s (Rust) vs 8.9s (SciPy) = 74× speedup • Mean Field Games: 0.4s (Rust) vs 45s (Python) = 112× speedup

📚 Learn More: → Complete documentation: https://optimiz-r.readthedocs.io → 6+ working tutorial notebooks → API reference with examples → Mathematical foundations

🛠️ Get Started:

Python:

pip install optimizr-rs

Rust:

cargo add optimizr

🌟 Why OptimizR?

Built for researchers and practitioners who need: Production-grade performance Stable, well-documented API Easy Python integration Robust numerical methods Active development roadmap

🤝 Join the Community!

This project is driven by the belief that high-performance optimization tools should be accessible to everyone. Whether you're: • A data scientist optimizing portfolios • A researcher working on Bayesian inference • An engineer building ML pipelines • Or just curious about Rust + Python!

I'd love your feedback, contributions, and star on GitHub!

📖 Explore the docs, try the tutorials, and let me know what you build with it!

#Rust #Python #DataScience #MachineLearning #Optimization #OpenSource #MCMC #HiddenMarkovModels #NumericalMethods #HighPerformanceComputing

🔗 GitHub: https://github.com/ThotDjehuty/optimiz-r 📚 Docs: https://optimiz-r.readthedocs.io 📦 PyPI: https://pypi.org/project/optimizr-rs/ (publishing soon) 📦 crates.io: https://crates.io/crates/optimizr