Programming languages on the rise: Python There seems to be two sorts of people who love Python: those who hate brackets, and scientists. The former helped create the language by building a version of Perl that is easier to read and not as chock-full of opening and closing brackets as a C descendant. Fast-forward several years, and the solution was good enough to be the first language available on Google's AppEngine -- a clear indication Python has the kind of structure that makes it easy to scale in the cloud, one of the biggest challenges for enterprise-grade computing.
[ For a look at the wide-ranging flock of Python IDEs, see "InfoWorld review: Nine fine Python development tools." ]
Python's popularity in scientific labs is a bit hard to explain, given that, unlike Stephen Wolfram's Mathematica for mathematicians, the language never offered any data structures or elements explicitly tuned to meet the needs of scientists. Python creator Guido von Rossum believes Python caught on in the labs because "scientists often need to improvise when trying to interpret results, so they are drawn to dynamic languages which allow them to work very quickly and see results almost immediately."
Of course, a number of libraries that offer much of what a scientist could want are available for Python. NumPy and SciPy are just two of the most notable libraries nurtured as open source projects and tuned for scientific computation.
Scientific and engineering enterprises such as pharmaceutical companies aren't the only ones tapping Python for research. Many Wall Street firms now rely heavily on mathematical analysis and often hire university scientists who bring along their habit of coding in Python. Python is becoming so popular on Wall Street that there are even proposals to require the prospectus for a bond to include a Python algorithm for specifying who gets what return on the investment.