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    1. COEvery SPSS reader/importer I've run across seems to target the `.sav` format, so I'm guessing that's your better bet. R also has a specialized `sas7bdat` [reader](http://cran.r-project.org/web/packages/sas7bdat/index.html) as well, but if you have the same content in both formats, the `.sav` file seems better supported.
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    2. COI haven't found any python packages that can parse an SPSS `.sav` file without SPSS itself, but I have noticed a [few](http://code.activestate.com/recipes/577811-python-reader-writer-for-spss-sav-files-linux-mac-/) code snippets that might be robust enough for your needs. Beyond this, you might have better luck with reading the SPSS file with [R](http://stat.ethz.ch/R-manual/R-devel/library/foreign/html/read.spss.html) and then dumping out a CSV or some other easy-to-parse format. R uses [PSPP](http://www.gnu.org/software/pspp/)'s SPSS reader, which (I expect) is more mature.
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    3. COThat's a good, though separate question. Consider, for example, if `y=10` was not a simple assignment, but actually a very expensive operation that `child_function` needed. Consider also that, instead of one `child_function`, you had many. Instead of having to put this very expensive computation in each separate function, and have it computed on every function call, you can wrap it in a closure and have it precomputed for this hypothetical set of `child_functions`. Check out [this](http://stackoverflow.com/questions/1305570/closures-why-are-they-so-useful) for a few helpful answers.
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