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As computer systems require more and more computing power, programmers have had to turn to concurrent computing. Concurrency is a difficult concept for people to deal with because they are serial by nature. Concurrency is also a real problem for programming styles that are highly dependent upon state (as in structured programs that rely on side effects). Functional programs that do not have side effects are often much easier to make concurrent than other styles because of the referential transparency that side effect free programming has. Theoretic ease is quite different from actual ease when implementations are concerned. Some functions are inherently parallelizable, such as the MapReduce function mentioned previously; others are not. Whether a function is inherently parallelizable is often linked very closely with I/O operations and is something outside the functional programmer s control. All things being equal, though, functional programs are often much more amenable to concurrent versions than other styles because of side effect free functions and the nature of functional evaluation. Concurrency is an issue that will become only more important as time goes on. Functional programs are easier to think about for humans than other styles in concurrent environments, which is a major factor in being able to produce defect-free code that actually does what it is supposed to do. If the programmer cannot intellectually process the problem effectively, that programmer has little hope of producing code to create a solution effectively.

This method loops through each of the CSV files and loads them. It does this by assuming that the first row of each file is a header, and it loops through it looking for a column named Symbol. This has the advantage of working with any CSV file whose first line is a header row and that has a Symbol column. If your CSV files have symbol columns labeled something else, you can add support for them by adding to the valid_symbol_ labels array. The end result of this is a @symbols array full of symbols, which you use next. You expose a single method, to_xml, which converts it into XML:

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The optimizations of function calls that are possible in functional languages also have an effect on concurrency. This is an area that is very active in research and something that will hopefully yield some very interesting parallelizing compilers in the future.

One of the benefits of Ajax technology is that it allows us to move some of the processing logic out to the client s computer, giving that computer the opportunity to help carry the load. Less strain on the server side of things can dramatically improve the scalability of your site. However, it is possible to overdo things. Bloated JavaScript is doing your users a grave injustice and will eventually lead to slower load times. Slower load times lead to angry users. Angry users will go somewhere else.

The to_xml method uses Remarkably s xml method to create a simple XML document. (You can use the xml method because you mixed in the Remarkably::Common framework using include.) You create a symbols node, and then a symbol node for each of your symbols. When you call a method that s not defined inside a call to the xml function, Remarkably uses it as a node name, so you can use the symbols and symbol methods to create nodes named symbols and symbol, respectively. (This approach is very similar to Markaby, and while it appears strange at first, it rapidly becomes more familiar.) Undefined methods are caught using Ruby s method_missing technique, and they are converted into XML tags.

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