At ActiveState we are addressing similar issues around the misconceptions of open-source software in general and dynamic languages in particular with whitepapers like 10 Myths About Running Open Source Software in Your Business. (PDF)
Holden: Don't discount scripting languages in general or Python in particular because of a lack of explicit typing or assumptions of poor performance. Requiring the declaration of types only catches a minor set of potential bugs that are easily discovered by typical unit testing. As for performance, Python might just surprise you.
And on the off-chance something is not fast enough, you have the option to go back and rewriting it in C/C++ (or in Java or any .Net language if you use Jython or IronPython) as needed, allowing you to still benefit from Python's high level of productivity.
Scripting languages in general and Python in particular can offer massive increases in productivity with little or no negative effects on eventual system performance. Where performance gains are required extensions can be crafted in compiled languages if necessary.
Lam: Dynamic languages offer better productivity in many cases. Future programs will be written using a mix of static and dynamic typed languages. Use each language where it is best suited: dynamic languages to define DSLs, and static languages where you want to leverage the power of a strong type system for things like static verification of programs or increased performance.
Pall: Dynamic languages improve productivity and reduce complexity leading to simpler less error-prone solutions. PHP has a large, helpful, intelligent community that offers a mature product, without too many surprises.
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