Python

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 1319 articles , 3 standard articles )

Showing results 1 to 20 of 1319.
Sorted by year (citations)

1 2 3 ... 64 65 66 next

  1. Bayen, Alexandre; Kong, Qingkai; Siauw, Timmy: Python programming and numerical methods. A guide for engineers and scientists (to appear) (2021)
  2. Ignatyev, Mikhail V.; Shevchenko, Aleksandr A.: Centrally generated primitive ideals of (U(\mathfrakn)) for exceptional types (2021)
  3. Loehr, Nicholas A.; Warrington, Gregory S.: Abacus-histories and the combinatorics of creation operators (2021)
  4. Adam Pluta; Ontje Lunsdorf: esy-osmfilter - A Python Library to Efficiently Extract OpenStreetMap Data (2020) not zbMATH
  5. Aguirre-Mesa, Andres M.; Garcia, Manuel J.; Millwater, Harry: MultiZ: a library for computation of high-order derivatives using multicomplex or multidual numbers (2020)
  6. 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
  7. 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
  8. Albuquerque, Yuri Flores; Laurain, Antoine; Sturm, Kevin: A shape optimization approach for electrical impedance tomography with point measurements (2020)
  9. Alcobaça, Edesio; Siqueira, Felipe; Rivolli, Adriano; Garcia, Luís P. F.; Oliva, Jefferson T.; de Carvalho, André C. P. L. F.: MFE: towards reproducible meta-feature extraction (2020)
  10. Alexander M. Rush: Torch-Struct: Deep Structured Prediction Library (2020) arXiv
  11. Alexandrov, Alexander; Benidis, Konstantinos; Bohlke-Schneider, Michael; Flunkert, Valentin; Gasthaus, Jan; Januschowski, Tim; Maddix, Danielle C.; Rangapuram, Syama; Salinas, David; Schulz, Jasper; Stella, Lorenzo; Türkmen, Ali Caner; Wang, Yuyang: GluonTS: probabilistic and neural time series modeling in Python (2020)
  12. Andreux, Mathieu; Angles, Tomás; Exarchakis, Georgios; Leonarduzzi, Roberto; Rochette, Gaspar; Thiry, Louis; Zarka, John; Mallat, Stéphane; Andén, Joakim; Belilovsky, Eugene; Bruna, Joan; Lostanlen, Vincent; Chaudhary, Muawiz; Hirn, Matthew J.; Oyallon, Edouard; Zhang, Sixin; Cella, Carmine; Eickenberg, Michael: Kymatio: scattering transforms in Python (2020)
  13. Andrew R. Bennett; Joseph J. Hamman; Bart Nijssen: MetSim: A Python package for estimation and disaggregation of meteorological data (2020) not zbMATH
  14. Andrew R. McCluskey; Tim Snow: uravu: Making Bayesian modelling easy(er) (2020) not zbMATH
  15. Anjalika Nande, Andrew Ferdowsian, Eric Lubin, Erez Yoeli, Martin Nowak: DyPy: A Python Library for Simulating Matrix-Form Games (2020) arXiv
  16. António Ramires, Gilberto Bernardes, Matthew E. P. Davies, Xavier Serra: TIV.lib: an open-source library for the tonal description of musical audio (2020) arXiv
  17. Aravind Krishnamoorthy, Ankit Mishra, Deepak Kamal, Sungwook Hong, Ken-ichi Nomura, Subodh Tiwari, Aiichiro Nakano, Rajiv Kalia, Rampi Ramprasad, Priya Vashishta: EZFF: Python Library for Multi-Objective Parameterization and Uncertainty Quantification of Interatomic Forcefields for Molecular Dynamics (2020) arXiv
  18. Archis S. Joglekar; Matthew C. Levy: VlaPy: A Python package for Eulerian Vlasov-Poisson-Fokker-Planck Simulations (2020) not zbMATH
  19. Armin Moin, Stephan Rössler, Marouane Sayih, Stephan Günnemann: From Things’ Modeling Language (ThingML) to Things’ Machine Learning (ThingML2) (2020) arXiv
  20. Arora, Rajat; Zhang, Xiaohan; Acharya, Amit: Finite element approximation of finite deformation dislocation mechanics (2020)

1 2 3 ... 64 65 66 next