🎉 Excited to announce the release of Scikit-Mol 0.4.5! Big thanks to Anton Siomchen for contributing two amazing PRs that bring bug fixes, robustness improvements, and under-the-hood enhancements. 🧪 #Chemoinformatics #MachineLearning
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🔬 What’s Scikit-Mol?
It’s an open-source library that bridges #RDKit featurization with ML models. Think #Scikit-Learn -compatible classes for fingerprints and descriptors. Easy, efficient, and chemistry-savvy! 🌟
💡 Details from the PRs:
• Better handling of invalid SMILES and more robust SafeInferenceWrapper.
• Python 3.13 support, a new linter/formatter, and even a PyPI-visible logo! 🎨
Huge shoutout to Anton Siomchen for the excellent work! 🙌
Post 5:
📢 How Are You Using Scikit-Mol?
We’d love to hear how it’s helping your projects! Are there features you’re missing or ideas you’d like to see implemented? Drop us a line and share your thoughts. #OpenSource #Cheminformatics
Comments
It’s an open-source library that bridges #RDKit featurization with ML models. Think #Scikit-Learn -compatible classes for fingerprints and descriptors. Easy, efficient, and chemistry-savvy! 🌟
1️⃣ Bug fixes:
• Safe-inference now handles batches with invalid molecules seamlessly.
• Parallel execution fixed for small sample sizes.
2️⃣ Under-the-hood improvements:
• Automated formatting, pre-commit hooks, badges, and README fixes.
• Better handling of invalid SMILES and more robust SafeInferenceWrapper.
• Python 3.13 support, a new linter/formatter, and even a PyPI-visible logo! 🎨
Huge shoutout to Anton Siomchen for the excellent work! 🙌
📢 How Are You Using Scikit-Mol?
We’d love to hear how it’s helping your projects! Are there features you’re missing or ideas you’d like to see implemented? Drop us a line and share your thoughts. #OpenSource #Cheminformatics