Seth Bunce
                                                                     2008-05-01

	The Right Tool For the Job

	In this context the tool is a programming language and the job is the
problem to be solved. Everyone knows this rule and how to apply it. The problem
is not that people don't know the rule. Writing a paper about the rule will not
further clarify the rule for anyone. Focusing on what the right tool for the job
is is missing the point. Often the ideal right tool is not the practical right
tool.
	The safe assumption will be made that all the tools in your shed are Turing
Complete meaning they're all equally capable of computing any computable
problem. The assumption will also be made that the problem is computable. These
assumptions are so basic they're almost not worth stating but they do happen to
be in direct contradiction to the idea of Linguistic Determinism as it's applied
to programming languages. As such the idea of Linguistic Determinism will be
considered wrong and will not be addressed further.
	There's a humorous saying that works for any programming language, "A good X
programmer can program X in any language". This is not meant as a complement,
it's meant to be ironic and to describe a "good" (meaning bad) programmer who
refuses to adapt his thought process to take full advantage of the language he's
working in.
	Programming languages encourage you to change how you think about solving
problems in that particular languages offer easier ways of solving certain
problems. This could be called shaping thought but that would be obfuscation of
a very simple idea. The idea is that given two ways of solving a problem, both
of which yield identical results, the easier way will naturally be chosen.
	The same idea applies between languages. For example, assume you had someone
who was equally knowledgeable in two radically different languages. If you told
this person to solve the same problem in each of the two languages they would
naturally choose the easiest way in each language. However, the two solutions
they come up with could be different.
	Pragmatically, picking the right tool isn't so clear cut. Choosing the right
tool is not a function of the capability of the tool to solve a given problem,
it's a function of your knowledge of the tool with respect to it's ability to
solve a given problem. Meaning, if you don't know how to use the ideal right
tool then perhaps a non-ideal tool is right for you.
	The solution, if you want to call it that, is to learn more languages. If
you have more tools to select from then you're more likely to have a tool that
is ideal to the problem.