Text File Parsing with Python

file-io, parsing, python, python-2.7, text

Solution

I would use a `for` loop to iterate over the lines in the text file:

for line in my_text:
    outputfile.writelines(data_parser(line, reps))

If you want to read the file line-by-line instead of loading the whole thing at the start of the script you could do something like this:

inputfile = open('test.dat')
outputfile = open('test.csv', 'w')

# sample text string, just for demonstration to let you know how the data looks like
# my_text = '"2012-06-23 03:09:13.23",4323584,-1.911224,-0.4657288,-0.1166382,-0.24823,0.256485,"NAN",-0.3489428,-0.130449,-0.2440527,-0.2942413,0.04944348,0.4337797,-1.105218,-1.201882,-0.5962594,-0.586636'

# dictionary definition 0-, 1- etc. are there to parse the date block delimited with dashes, and make sure the negative numbers are not effected
reps = {'"NAN"':'NAN', '"':'', '0-':'0,','1-':'1,','2-':'2,','3-':'3,','4-':'4,','5-':'5,','6-':'6,','7-':'7,','8-':'8,','9-':'9,', ' ':',', ':':',' }

for i in range(4): inputfile.next() # skip first four lines
for line in inputfile:
    outputfile.writelines(data_parser(line, reps))

inputfile.close()
outputfile.close()

Problem

I am trying to parse a series of text files and save them as CSV files using Python (2.7.3). All text files have a 4 line long header which needs to be stripped out. The data lines have various delimiters including " (quote), - (dash), : column, and blank space. I found it a pain to code it in C++ with all these different delimiters, so I decided to try it in Python hearing it is relatively easier to do compared to C/C++. I wrote a piece of code to test it for a single line of data and it works, however, I could not manage to make it work for the actual file. For parsing a single line I was using the text object and "replace" method. It looks like my current implementation reads the text file as a list, and there is no replace method for the list object. Being a novice in Python, I got stuck at this point. Any input would be appreciated! Thanks! ``` # function for parsing the data def data_parser(text, dic): for i, j in dic.iteritems(): text = text.replace(i,j) return text # open input/output files inputfile = open('test.dat') outputfile = open('test.csv', 'w') my_text = inputfile.readlines()[4:] #reads to whole text file, skipping first 4 lines # sample text string, just for demonstration to let you know how the data looks like # my_text = '"2012-06-23 03:09:13.23",4323584,-1.911224,-0.4657288,-0.1166382,-0.24823,0.256485,"NAN",-0.3489428,-0.130449,-0.2440527,-0.2942413,0.04944348,0.4337797,-1.105218,-1.201882,-0.5962594,-0.586636' # dictionary definition 0-, 1- etc. are there to parse the date block delimited with dashes, and make sure the negative numbers are not effected reps = {'"NAN"':'NAN', '"':'', '0-':'0,','1-':'1,','2-':'2,','3-':'3,','4-':'4,','5-':'5,','6-':'6,','7-':'7,','8-':'8,','9-':'9,', ' ':',', ':':',' } txt = data_parser(my_text, reps) outputfile.writelines(txt) inputfile.close() outputfile.close() ```

Original source