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Source channel @githubtrending · Post #15534 · Mar 1

#python#agent_skills#ai_scientist#bioinformatics#chemoinformatics#claude#claude_skills#claudecode#clinical_research#computational_biology#data_analysis#drug_discovery#genomics#materials_science#metabolomics#proteomics#scientific_computing#scientific_visualization Claude Scientific Skills offers 148+ ready-to-use tools for AI agents like Cursor or Claude Code, covering biology, chemistry, drug discovery, clinical research, ML, and 250+ databases (PubMed, ChEMBL, etc.). Easy setup: clone the GitHub repo and copy folders to your skills directory for automatic use in complex workflows like single-cell analysis or virtual screening. You save days on setup, get reliable code, and run multi-step science faster on your desktop. https://github.com/K-Dense-AI/claude-scientific-skills

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djangoproject

@djangoproject · Post #336 · 05/09/2017, 05:24 AM

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https://dzone.com/articles/pyflakes-passive-checker There are several code #analysis tools for Python. The most well known is pylint. Then there’s pychecker and now we’re moving on to #pyflakes. The pyflakes project is a part of something known as the Divmod Project. Pyflakes doesn’t actually execute the code it checks, unlike #pychecker. Of course, #pylint also doesn’t execute the code. Regardless, we’ll take a quick look at it and see how pyflakes works and if it’s better than the competition.

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#analysis #pyflakes #pychecker #pylint