I have a text file (.txt) which could be in tab separated format or pipe separated format, and I need to convert it into CSV file format. I am using python 2.6. Can any one suggest me how to identify the delimiter in a text file, read the data and then convert that into comma separated file.
Thanks in advance
I fear that you can't identify the delimiter without knowing what it is. The problem with CSV is, that, quoting ESR:
the Microsoft version of CSV is a textbook example of how not to design a textual file format.
The delimiter needs to be escaped in some way if it can appear in fields. Without knowing, how the escaping is done, automatically identifying it is difficult. Escaping could be done the UNIX way, using a backslash '\', or the Microsoft way, using quotes which then must be escaped, too. This is not a trivial task.
So my suggestion is to get full documentation from whoever generates the file you want to convert. Then you can use one of the approaches suggested in the other answers or some variant.
Edit:
Python provides csv.Sniffer that can help you deduce the format of your DSV. If your input looks like this (note the quoted delimiter in the first field of the second row):
a|b|c "a|b"|c|d foo|"bar|baz"|qux You can do this:
import csv csvfile = open("csvfile.csv") dialect = csv.Sniffer().sniff(csvfile.read(1024)) csvfile.seek(0) reader = csv.DictReader(csvfile, dialect=dialect) for row in reader: print row, # => {'a': 'a|b', 'c': 'd', 'b': 'c'} {'a': 'foo', 'c': 'qux', 'b': 'bar|baz'} # write records using other dialect Your strategy could be the following:
In the following example you find the simpler statistic (total number of fields)
import csv piperows= [] tabrows = [] #parsing | delimiter f = open("file", "rb") readerpipe = csv.reader(f, delimiter = "|") for row in readerpipe: piperows.append(row) f.close() #parsing TAB delimiter f = open("file", "rb") readertab = csv.reader(f, delimiter = "\t") for row in readerpipe: tabrows.append(row) f.close() #in this example, we use the total number of fields as indicator (but it's not guaranteed to work! it depends by the nature of your data) #count total fields totfieldspipe = reduce (lambda x,y: x+ y, [len(f) for f in piperows]) totfieldstab = reduce (lambda x,y: x+ y, [len(f) for f in tabrows]) if totfieldspipe > totfieldstab: yourrows = piperows else: yourrows = tabrows #the var yourrows contains the rows, now just write them in any format you like Like this
from __future__ import with_statement import csv import re with open( input, "r" ) as source: with open( output, "wb" ) as destination: writer= csv.writer( destination ) for line in input: writer.writerow( re.split( '[\t|]', line ) ) I would suggest taking some of the example code from the existing answers, or perhaps better use the csv module from python and change it to first assume tab separated, then pipe separated, and produce two output files which are comma separated. Then you visually examine both files to determine which one you want and pick that.
If you actually have lots of files, then you need to try to find a way to detect which file is which.
One of the examples has this:
if "|" in line: This may be enough: if the first line of a file contains a pipe, then maybe the whole file is pipe separated, else assume a tab separated file.
Alternatively fix the file to contain a key field in the first line which is easily identified - or maybe the first line contains column headers which can be detected.
for line in open("file"): line=line.strip() if "|" in line: print ','.join(line.split("|")) else: print ','.join(line.split("\t"))