One item I admire from Julia and miss in python/numpy, I often use the power of python list comprehension to process data. This data often needs to be converted to numpy for other operations, for example fancy indexing. The fact that operations using comprehensions (which produce lists) and operations on numpy arrays use different incompatible data structures requires conversions between lists and numpy arrays. Comprehensions in Julia produce arrays directly (I believe), removing the need for conversions.
I don't see any easy way to improve this. Any ideas? Thanks, Neal -- *Those who don't understand recursion are doomed to repeat it*
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