Art Kendall wrote:
I am running Windows 7 64bit Home premium. with quad cpus and 8G
memory. I am using Python 2.6.2.
I have all the Federalist Papers concatenated into one .txt file.
Which is how big? Currently you (unnecessarily) load the entire thing
into memory with readlines(). And then you do confusing work to split
it apart again, into one list element per paper. And for a while
there, you have three copies of the entire text. You're keeping two
copies, in the form of alltext and papers.
You print out the len(papers). What do you see there? Is it correctly
87 ? If it's not, you have to fix the problem here, before even going on.
I want to prepare a file with a row for each paper and a column for
each term. The cells would contain the count of a term in that paper.
In the original application in the 1950's 30 single word terms were
used. I can now use NoteTab to get a list of all the 8708 separate
words in allWords.txt. I can then use that data in statistical
exploration of the set of texts.
I have the python program(?) syntax(?) script(?) below that I am using
to learn PYTHON. The comments starting with "later" are things I will
try to do to make this more useful. I am getting one step at at time
to work
It works when the number of terms in the term list is small e.g., 10.
I get a file with the correct number of rows (87) and count columns
(10) in termcounts.txt. The termcounts.txt file is not correct when I
have a larger number of terms, e.g., 100. I get a file with only 40
rows and the correct number of columns. With 8700 terms I get only 40
rows I need to be able to have about 8700 terms. (If this were FORTRAN
I would say that the subscript indices were getting scrambled.) (As I
develop this I would like to be open-ended with the numbers of input
papers and open ended with the number of words/terms.)
# word counts: Federalist papers
import re, textwrap
# read the combined file and split into individual papers
# later create a new version that deals with all files in a folder
rather than having papers concatenated
alltext = file("C:/Users/Art/Desktop/fed/feder16v3.txt").readlines()
papers= re.split(r'FEDERALIST No\.'," ".join(alltext))
print len(papers)
countsfile = file("C:/Users/Art/desktop/fed/TermCounts.txt", "w")
syntaxfile = file("C:/Users/Art/desktop/fed/TermCounts.sps", "w")
# later create a python program that extracts all words instead of
using NoteTab
termfile = open("C:/Users/Art/Desktop/fed/allWords.txt")
termlist = termfile.readlines()
termlist = [item.rstrip("\n") for item in termlist]
print len(termlist)
# check for SPSS reserved words
varnames = textwrap.wrap(" ".join([v.lower() in ['and', 'or', 'not',
'eq', 'ge',
'gt', 'le', 'lt', 'ne', 'all', 'by', 'to','with'] and (v+"_r") or v
for v in termlist]))
syntaxfile.write("data list file=
'c:/users/Art/desktop/fed/termcounts.txt' free/docnumber\n")
syntaxfile.writelines([v + "\n" for v in varnames])
syntaxfile.write(".\n")
# before using the syntax manually replace spaces internal to a string
to underscore // replace (ltrtim(rtrim(varname))," ","_") replace
any special characters with @ in variable names
for p in range(len(papers)):
range(len()) is un-pythonic. Simply do
for paper in papers:
and of course use paper below instead of papers[p]
counts = []
for t in termlist:
counts.append(len(re.findall(r"\b" + t + r"\b", papers[p],
re.IGNORECASE)))
if sum(counts) > 0:
papernum = re.search("[0-9]+", papers[p]).group(0)
countsfile.write(str(papernum) + " " + " ".join([str(s) for s in
counts]) + "\n")
Art
If you're memory limited, you really should sequence through the files,
only loading one at a time, rather than all at once. It's no harder.
Use dirlist() to make a list of files, then your loop becomes something
like:
for infile in filelist:
paper = " ".join(open(infile, "r").readlines())
Naturally, to do it right, you should use with... Or at least close
each file when done.
DaveA
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