[Tutor] Is the difference in outputs with different size input lists due to limits on memory with PYTHON?

[Art Kendall]

On 5/6/2010 11:14 AM, Dave Angel wrote:
> 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
>
>

Thank you for getting back to me. I am trying to generalize a process 
that 50 years ago used 30 terms on the whole file and I am using the 
task of generalizing the process to learn python.   In the post I sent 
there were comments to myself about things that I would want to learn 
about.  One of the first is to learn about processing all files in a 
folder, so your reply will be very helpful.  It seems that dirlist() 
should allow me to include the filespec in the output file which would 
be very helpful.

to rephrase my questions.
Is there a way to tell python to use more RAM?

Does python use the same array space over as it counts the occurrences 
for each input document? Or does it keep every row of the output 
someplace even after it has written it to the output? If it does keep 
old arrays, is there a way to "close" the output array in RAM between 
documents

I narrowed down the problem.  With 4035 terms it runs OK.  With 4040 the 
end of the output matrix is messed up.  I do not think it is a limit of 
my resources that gets in the way.  I have 352G of free hard disk if it 
goes virtual.   I have 8G of RAM.  Even if python turns out to be 
strictly 32Bit I think it would be able to use 3G of RAM.  The input 
file is 1.1M so that should be able to fit in RAM many times.

P.S. I hope I remembered correctly that this list put replies at the bottom.
Art