Аннотация
This accessible and self-contained guide provides a comprehensive introduction to the popular programming language Python, with a focus on applications in chemistry and chemical physics. Ideally suited to students and researchers of chemistry learning to employ Python for problem-solving in their research, this fast-paced primer first builds a solid foundation in the programming language before progressing to advanced concepts and applications in chemistry. The required syntax and data structures are established, and then applied to solve problems computationally. Popular numerical packages are described in detail, including NumPy, SciPy, Matplotlib, SymPy, and pandas. End of chapter problems are included throughout, with worked solutions available within the book. Additional resources, datasets, and Jupyter Notebooks are provided on a companion website, allowing readers to reinforce their understanding and gain confidence applying their knowledge through a hands-on approach.




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All of these new features, which I’ll refer to under the single name Asyncio, have been received by the Python... Using Asyncio in Python [Understanding Python’s Asynchronous Programming Features]](https://www.rulit.me/data/programs/images/using-asyncio-in-python-understanding-python-s-asynchronous_606937.jpg)


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