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 1378 articles , 3 standard articles )

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  1. Bayen, Alexandre; Kong, Qingkai; Siauw, Timmy: Python programming and numerical methods. A guide for engineers and scientists (to appear) (2021)
  2. D.C.L. Handler, P.A. Haynes: PeptideMind - Applying machine learning algorithms to assess replicate quality in shotgun proteomic data (2021) not zbMATH
  3. Huo, Zenan; Mei, Gang; Xu, Nengxiong: JuSFEM: a Julia-based open-source package of parallel smoothed finite element method (S-FEM) for elastic problems (2021)
  4. Ignatyev, Mikhail V.; Shevchenko, Aleksandr A.: Centrally generated primitive ideals of (U(\mathfrakn)) for exceptional types (2021)
  5. L. Capocchi, J.F. Santucci: A web-based simulation of discrete-event system of system with the mobile application DEVSimPy-mob (2021) not zbMATH
  6. Loehr, Nicholas A.; Warrington, Gregory S.: Abacus-histories and the combinatorics of creation operators (2021)
  7. Marcos Nieto, Orti Senderos, Oihana Otaegui: Boosting AI applications: Labeling format for complex datasets (2021) not zbMATH
  8. Partha Pratim Das, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan: RealPi2dDIC: A Low-cost and open-source approach to in situ 2D Digital Image Correlation (DIC) applications (2021) not zbMATH
  9. Rausand, Marvin; Barros, Anne; Hoyland, Arnljot: System reliability theory. Models, statistical methods, and applications (to appear) (2021)
  10. Rolf Bork, Jonathan Hanks, David Barker, Joseph Betzwieser, Jameson Rollins, Keith Thorne, Erik von Reis: advligorts: The Advanced LIGO real-time digital control and data acquisition system (2021) not zbMATH
  11. Sebastian Blauth: cashocs: A Computational, Adjoint-Based Shape Optimization and Optimal Control Software (2021) not zbMATH
  12. Sergio Cantero-Chinchilla, James L. Beck, Juan Chiachio, Manuel Chiachio, Dimitrios Chronopoulos: OptiSens - Convex optimization of sensor and actuator placement for ultrasonic guided-wave based structural health monitoring (2021) not zbMATH
  13. Victoria B. Stephens, David O. Lignell: One-dimensional turbulence (ODT): Computationally efficient modeling and simulation of turbulent flows (2021) not zbMATH
  14. Adam Pluta; Ontje Lunsdorf: esy-osmfilter - A Python Library to Efficiently Extract OpenStreetMap Data (2020) not zbMATH
  15. Aguirre-Mesa, Andres M.; Garcia, Manuel J.; Millwater, Harry: MultiZ: a library for computation of high-order derivatives using multicomplex or multidual numbers (2020)
  16. Aka, Menny; Einsiedler, Manfred; Ward, Thomas: A journey through the realm of numbers. From quadratic equations to quadratic reciprocity (2020)
  17. Alain Jungo, Olivier Scheidegger, Mauricio Reyes, Fabian Balsiger: pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis (2020) arXiv
  18. Alberto Paganini, Florian Wechsung: Fireshape: a shape optimization toolbox for Firedrake (2020) arXiv
  19. Albert Steppi; Benjamin M. Gyori; John A. Bachman: Adeft: Acromine-based Disambiguation of Entities from Text with applications to the biomedical literature (2020) not zbMATH
  20. Albuquerque, Yuri Flores; Laurain, Antoine; Sturm, Kevin: A shape optimization approach for electrical impedance tomography with point measurements (2020)

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