On Oct 31, 12:48 pm, Tim Chase <python.l...@tim.thechases.com> wrote:
> > PRJ01001 4 00100END
> > PRJ01002 3 00110END
>
> > I would like to pick only some columns to a new file and put them to a
> > certain places (to match previous data) - definition file (def.csv)
> > could be something like this:
>
> > VARIABLE FIELDSTARTS FIELD SIZE NEW PLACE IN NEW DATA FILE
> > ProjID ; 1 ; 5 ; 1
> > CaseID ; 6 ; 3 ; 10
> > UselessV ; 10 ; 1 ;
> > Zipcode ; 12 ; 5 ; 15
>
> > So the new datafile should look like this:
>
> > PRJ01 001 00100END
> > PRJ01 002 00110END
>
> How flexible is the def.csv format? The difficulty I see with
> your def.csv format is that it leaves undefined gaps (presumably
> to be filled in with spaces) and that you also have a blank "new
> place in new file" value. If instead, you could specify the
> width to which you want to pad it and omit variables you don't
> want in the output, ordering the variables in the same order you
> want them in the output:
>
> Variable; Start; Size; Width
> ProjID; 1; 5; 10
> CaseID; 6; 3; 10
> Zipcode; 12; 5; 5
> End; 16; 3; 3
>
> (note that I lazily use the same method to copy the END from the
> source to the destination, rather than coding specially for it)
> you could do something like this (untested)
>
> import csv
> f = file('def.csv', 'rb')
> f.next() # discard the header row
> r = csv.reader(f, delimiter=';')
> fields = [
> (varname, slice(int(start), int(start)+int(size)), width)
> for varname, start, size, width
> in r
> ]
> f.close()
> out = file('out.txt', 'w')
> try:
> for row in file('data.txt'):
> for varname, slc, width in fields:
> out.write(row[slc].ljust(width))
> out.write('\n')
> finally:
> out.close()
>
> Hope that's fairly easy to follow and makes sense. There might
> be some fence-posting errors (particularly your use of "1" as the
> initial offset, while python uses "0" as the initial offset for
> strings)
>
> If you can't modify the def.csv format, then things are a bit
> more complex and I'd almost be tempted to write a script to try
> and convert your existing def.csv format into something simpler
> to process like what I describe.
>
> -tkc
To your point about the non-stand csv encoding in the defs.csv file,
you could use a reg exp instead of the csv module to solve that:
import re
parse_columns = re.compile(r'\s*;\s*')
f = file('defs.csv', 'rb')
f.readline() # discard the header row
r = (parse_columns.split(line.strip()) for line in f)
fields = [
(varname, slice(int(start), int(start)+int(size), int(width) if
width else 0))
for varname, start, size, width in r
]
f.close()
which given the OP's csv produces for fields:
[('ProjID', slice(1, 6, 1)), ('CaseID', slice(6, 9, 10)), ('UselessV',
slice(10, 11, 0)), ('Zipcode', slice(12, 17, 15))]
and that should work with the remainder of your original code;
although perhaps the OP wants something else to happen when width is
omitted from the csv...
Cheers - Chas
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