Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java. The language provides constructs intended to enable clear programs on both a small and large scale. Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library. Python interpreters are available for installation on many operating systems, allowing Python code execution on a wide variety of systems. Using third-party tools, such as Py2exe or Pyinstaller, Python code can be packaged into stand-alone executable programs for some of the most popular operating systems, allowing the distribution of Python-based software for use on those environments without requiring the installation of a Python interpreter. (wikipedia)

References in zbMATH (referenced in 328 articles , 3 standard articles )

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  1. Alexander J. Titus, Shashwat Kishore, Todd Stavish, Stephanie M. Rogers, Karl Ni: PySEAL: A Python wrapper implementation of the SEAL homomorphic encryption library (2018) arXiv
  2. Birk, Lothar; McCulloch, T.Luke: Robust generation of constrained B-spline curves based on automatic differentiation and fairness optimization (2018)
  3. Charles Truong, Laurent Oudre, Nicolas Vayatis: ruptures: change point detection in Python (2018) arXiv
  4. Minjie Zhu, Frank McKenna, Michael H. Scott: OpenSeesPy: Python library for the OpenSees finite element framework (2018)
  5. Oliver Laslett, Jonathon Waters, Hans Fangohr, Ondrej Hovorka: Magpy: A C++ accelerated Python package for simulating magnetic nanoparticle stochastic dynamics (2018) arXiv
  6. Osais, Yahya Esmail: Computer simulation. A foundational approach using Python (2018)
  7. Rafael M. O. Cruz, Luiz G. Hafemann, Robert Sabourin, George D. C. Cavalcanti: DESlib: A Dynamic ensemble selection library in Python (2018) arXiv
  8. Rubio-Sánchez, Manuel: Introduction to recursive programming (2018)
  9. Ryan, Nathan C.; Wallace, Dorothy: Applications of calculus to biology and medicine. Case studies from Lake Victoria (2018)
  10. Ahmed Attia, Adrian Sandu: DATeS: A Highly-Extensible Data Assimilation Testing Suite (2017) arXiv
  11. Alexandre Refregier, Lukas Gamper, Adam Amara, Lavinia Heisenberg: PyCosmo: An Integrated Cosmological Boltzmann Solver (2017) arXiv
  12. Amina Asif, Wajid Arshad Abbasi, Farzeen Munir, Asa Ben-Hur, Fayyaz ul Amir Afsar Minhas: pyLEMMINGS: Large Margin Multiple Instance Classification and Ranking for Bioinformatics Applications (2017) arXiv
  13. Andrew C. Heusser, Kirsten Ziman, Lucy L. W. Owen, Jeremy R. Manning: HyperTools: A Python toolbox for visualizing and manipulating high-dimensional data (2017) arXiv
  14. Bart van Merrienboer, Alexander B. Wiltschko, Dan Moldovan: Tangent: Automatic Differentiation Using Source Code Transformation in Python (2017) arXiv
  15. Bell, Mark C.; Schleimer, Saul: Slow north-south dynamics on $\mathcalPML$ (2017)
  16. Benjamin Guedj, Bhargav Srinivasa Desikan: Pycobra: A Python Toolbox for Ensemble Learning and Visualisation (2017) arXiv
  17. Bob Carpenter and Andrew Gelman and Matthew Hoffman and Daniel Lee and Ben Goodrich and Michael Betancourt and Marcus Brubaker and Jiqiang Guo and Peter Li and Allen Riddell: Stan: A Probabilistic Programming Language (2017)
  18. Bryan W. Weber, Chih-Jen Sung: UConnRCMPy: Python-based data analysis for rapid compression machines (2017) arXiv
  19. Bugliesi, Michele; Calzavara, Stefano; Focardi, Riccardo: Formal methods for web security (2017)
  20. Carmen Moret-Tatay, Daniel Gamermann, Esperanza Navarro-Pardo, Pedro Fernandez de Cordoba: ExGUtils: A python package for statistical analysis with the ex-gaussian probability density (2017) arXiv

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