Parsers and algorithms for computational chemistry logfiles
The main features of cclib/cclib are: Scientific Computing.
Open-source alternatives to cclib/cclib include: colour-science/colour — Colour Science for Python. manimcommunity/manim — Manim is a scriptable, code-driven framework designed for generating precise technical visualizations and mathematical… atsushisakai/pythonrobotics — PythonRobotics is a comprehensive collection of modular robotics algorithms and educational simulations designed for… biopython/biopython — Biopython is a bioinformatics library for Python providing tools to parse, manipulate, and analyze biological… astropy/astropy — Astropy is a core Python library for astronomy, providing a unified framework for astronomical data analysis,… mesa/mesa — Mesa is a Python framework for agent-based modeling and complex systems simulation. It provides a toolkit for creating…
Biopython is a bioinformatics library for Python providing tools to parse, manipulate, and analyze biological sequences, molecular structures, and phylogenetic trees. It serves as a biological sequence parser for genomic and proteomic data across multiple industry-standard file formats and acts as an interface for querying biological data and citations from NCBI Entrez repositories. The project distinguishes itself through specialized toolkits for protein structure analysis and phylogenetic tree construction. It includes a protein structure analyzer for processing PDB and mmCIF files to calcu
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PythonRobotics is a comprehensive collection of modular robotics algorithms and educational simulations designed for autonomous navigation, state estimation, and motion control. The project provides a library of standalone implementations for path planning, localization, mapping, and kinematics, serving as a resource for researchers and students to experiment with foundational and advanced robotic theories. The project distinguishes itself through an algorithm-centric design where each module functions as an isolated script, allowing for independent testing and clear pedagogical demonstration
Colour Science for Python