- Technical Development Guide
- Function Decorators
- Classes and Objects
- Classes and Objects, Descriptors
- Comprehensions
- 10 R packages I wish I knew about earlier
- Understanding Decorators
Python is a widely used general-purpose, high-level 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. The language provides constructs intended to enable clear programs on both a small and large scale. The standard library has extensive support for complex data structures and I/O through standard formats and protocols. As of January 2014, the Python Package Index, the official repository of third-party software for Python, contains more than 38,000 packages.
doctest is a module included in the Python programming language's standard library that allows the easy generation of tests based on output from the standard Python interpreter shell, cut and pasted into docstrings.
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. Julia is an ambitious language. It aims to be as fast as C, as easy to use as Python, and as statistically inclined as R (to name a few goals).
R is a free software environment for statistical computing and graphics. The language is widely used among statisticians and data miners for developing statistical software and data analysis.
The capabilities of R are extended through user-created packages, which allow specialized statistical techniques, graphical devices (ggplot2), import/export capabilities, reporting tools (knitr, Sweave), etc. These packages are developed primarily in R, and sometimes in Java, C and Fortran. A core set of packages is included with the installation of R, with more than 5,800 additional packages and 120,000 functions (as of June 2014) available at the Comprehensive R Archive Network (CRAN), Bioconductor, and other repositories.