Learning Python

By M. Lutz. 1999

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix (2019, background): “The cctbx components are written both in a compiled language (C++) and a flexible scripting language (Python; Lutz & Ascher, 1999).”
SymPy: Symbolic computing in Python (2017, background): “SymPy is a full featured computer algebra system (CAS) written in the Python programming language [25].”
PyMC: Bayesian Stochastic Modelling in Python (2010, background): “Familiarity with Python is assumed, so if you are new to Python, books such as Lutz (2007) or Langtangen (2009) are the place to start.”
The ALPS project release 2.0: open source software for strongly correlated systems (2011, methodology): “This is remedied in ALPS 2.0 by basing data evaluation on the powerful Python language [50].”
AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility (2009, background): “15,16 The easy-to-use graphical user interface has a gentle learning curve and an effective self-taught tutorial is available online.”
MCCARD : MONTE CARLO CODE FOR ADVANCED REACTOR DESIGN AND ANALYSIS (2012, methodology): “A combination of hierarchical geometry options and the Python scripts [11] are adopted to input complex geometrical data efficiently and at the same time with as much simplicity as possible.”
OpenAlea: a visual programming and component-based software platform for plant modelling. (2008, unknown): “It is: (a) open source; (b) platform independent; (c) object-oriented; (d) user friendly; it has a simple-to-read syntax and is easy to learn, which allows even non-computer scientists to prototype rapidly new scripts or to transform existing ones (Ousterhout 1998; Ascher and Lutz 1999); (e) interac”
Experiences creating three implementations of the repast agent modeling toolkit (2006, methodology): “Repast for Python Scripting (Repast Py) is a rapid application development (RAD) tool for producing Repast simulations in which agent behavior is scripted using the Python computer language [Lutz and Ascher 1999].”
The Phenix Software for Automated Determination of Macromolecular Structures (2011, unknown): “Phenix builds upon Python[24], the Boost.”
IFEFFIT: interactive XAFS analysis and FEFF fitting. (2001, background): “Special attention has been given to ensure that this library can also be used from high-level scripting languages such as Tcl(Ousterhout, 1994), Perl(Wall et al. , 1997), and Python(von Rossum, 1995; Lutz & Ascher, 1999).”