SymPy: symbolic computing in Python

• Autor: Meurer, Aaron ; Smith, Christopher P ; Paprocki, Mateusz ; Certík, Ondrej ; Kirpichev, Sergey B ; Rocklin, Matthew ; Kumar, AMiT ; Ivanov, Sergiu ; Moore, Jason K ; Singh, Sartaj ; Rathnayake, Thilina ; Vig, Sean ; Granger, Brian E ; Muller, Richard P ; Bonazzi, Francesco ; Gupta, Harsh ; Vats, Shivam ; Johansson, Fredrik ; Pedregosa, Fabian ; Curry, Matthew J ; Terrel, Andy R ; Roucka, Stepán ; Saboo, Ashutosh ; Fernando, Isuru ; Kulal, Sumith ; Cimrman, Robert ; Scopatz, Anthony
• Assuntos: Applied mathematics ; Architectural engineering ; Architecture ; Authorship ; Computer algebra ; Computer algebra system ; Computer Science ; Laboratories ; Libraries ; Mathematical software ; MATHEMATICS AND COMPUTING ; Physics ; Programming languages ; Python ; Python (Programming language) ; Symbolics
• É parte de: PeerJ. Computer science, 2017-01, Vol.3, p.e103, Article e103
• Notas: SAND-2016-4832J; LA-UR-16-23820l
  USDOE National Nuclear Security Administration (NNSA)
  AC52-06NA25396; AC04-94AL85000
  
• Descrição: SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.
  
• Editor: San Diego: PeerJ. Ltd
  
• Idioma: Inglês