Python: An Ecosystem for Scientific Computing

Authors:
Fernando Perez;Brian E. Granger;John D. Hunter
Affiliations:
University of California, Berkeley;California Polytechnic State University, San Luis Obispo;TradeLink Securities
Venue:
Computing in Science and Engineering
Year:
2011

Citing 0
Cited 3

Enhancing the BYG gridification tool with state-of-the-art Grid scheduling mechanisms and explicit tuning support

Advances in Engineering Software
The SEEDS platform for evolutionary and ecological simulations

Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Map algebra and model algebra for integrated model building

Environmental Modelling & Software

Quantified Score

Hi-index	0.00

Visualization

Abstract

As the relationship between research and computing evolves, new tools are required to not only treat numerical problems, but also to solve various problems that involve large datasets in different formats, new algorithms, and computational systems such as databases and Internet servers. Python can help develop these computational research tools by providing a balance of clarity and flexibility without sacrificing performance.