Knacktus wrote:
Am 02.12.2010 02:51, schrieb Dana:
Hello,
I'm using Python to extract words from plain text files. I have a list
of words. Now I would like to convert that list to a dictionary of
features where the key is the word and the value the number of
occurrences in a group of files based on the filename (different files
correspond to different categories). What is the best way to represent
this data? When I finish I expect to have about 70 unique dictionaries
with values I plan to use in frequency distributions, etc. Should I use
globally defined dictionaries?
Depends on what else you want to do with the group of files. If you're
expecting some operations on the group's data you should create a class
to be able to add some more methods to the data. I would probably go
with a class.
Unless you're planning to have multiple "file groups" at once, or
intending to re-use this code for other modules, using a class is
probably overkill. This isn't Java where everything has to be a class :)
But also I think dictionaries can be fine. If you really only need the
dicts. You could create a function to create those.
Agreed.
One way or the other, a dict {word: count} is the natural data structure
to use for a concordance. Whether you store those dicts in a class, or
just operate directly on the dicts, is relatively unimportant.
--
Steven
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