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 224 articles , 3 standard articles )

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  1. Herman, Russell L.: An introduction to Fourier analysis (2017)
  2. Andersen, Jakob L.; Flamm, Christoph; Merkle, Daniel; Stadler, Peter F.: A software package for chemically inspired graph transformation (2016)
  3. Arai, Ryoya; Sato, Shigeyuki; Iwasaki, Hideya: A debugger-cooperative higher-order contract system in Python (2016)
  4. Brzeziński, Dariusz W.; Ostalczyk, Piotr: Numerical calculations accuracy comparison of the inverse Laplace transform algorithms for solutions of fractional order differential equations (2016)
  5. Caprara, Alberto; Carvalho, Margarida; Lodi, Andrea; Woeginger, Gerhard J.: Bilevel knapsack with interdiction constraints (2016)
  6. Coelho, Rodrigo C.V.; Neumann, Rodrigo F.: Fluid dynamics in porous media with Sailfish (2016)
  7. Cooper, Christopher D.; Barba, Lorena A.: Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code (2016)
  8. de Montjoye, Yves-Alexandre; Rocher, Luc; Pentland, Alex Sandy: bandicoot: a python toolbox for mobile phone metadata (2016)
  9. Diamond, Steven; Boyd, Stephen: CVXPY: a python-embedded modeling language for convex optimization (2016)
  10. Eppstein, David: Simple recognition of Halin graphs and their generalizations (2016)
  11. Garrido, José M.: Introduction to computational models with Python (2016)
  12. Gąsiorek, Marcin; Simson, Daniel; Zając, Katarzyna: A Gram classification of non-negative corank-two loop-free edge-bipartite graphs (2016)
  13. Haslwanter, Thomas: An introduction to statistics with Python. With applications in the life sciences (2016)
  14. Kimbrough, Steven Orla; Lau, Hoong Chuin: Business analytics for decision making (2016)
  15. Langtangen, Hans Petter: Finite difference computing with exponential decay models (2016)
  16. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- Python. A gentle introduction to numerical simulations with Python (2016)
  17. Linge, Svein; Langtangen, Hans Petter: Programming for computations -- MATLAB/Octave. A gentle introduction to numerical simulations with MATLAB/Octave (2016)
  18. Luukko, P.J.J.; Helske, J.; Räsänen, E.: Introducing libeemd: a program package for performing the ensemble empirical mode decomposition (2016)
  19. Maher, Stephen; Miltenberger, Matthias; Pedroso, João Pedro; Rehfeldt, Daniel; Schwarz, Robert; Serrano, Felipe: PySCIPOpt: mathematical programming in python with the SCIP optimization suite (2016)
  20. McAndrew, Alasdair: A computational introduction to digital image processing (2016)

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