Python and Scientific Computing

Scientists and engineers often have needs for high-performance computation tools which are also easy to use and modify. Many also wish to be able to use a general-purpose language instead of a specialized tool, allowing them to integrate networking, GUI's etc. in their high-performance work. Several tools have been developed to address these needs around the Python language. The Numeric Python extensions is the foremost among these tools.

This topic guide presents links to resources which have proven to be of great help in allowing this user community to use Python in their research work. The guide is divided into four sections.

• The first section covers the NumPy extensions, which provide efficient operations on large multidimensional arrays.
• The second section covers all of the other tools available, including array-manipulation code, general numerical analysis code, tools for visualizing and storing data, and links to field-specific tools.
• The third section provides information on books and literature on topics of interest to scientific Python users but which may not be directly related to Python.
• The final section consists of links to the Matrix and Plotting Special Interest Groups, which are good for a for discussing topics in scientific computing in Python.