Handling CSV Files in Python
As a buddy of mine always says "the nice thing about standards is that there's so many to choose from". Take CSV files for example. CSV, of course, stands for "Comma Separated Values", more often than not though, it seems that CSV files use tabs to separate values rather than commas. And let's not even mention field quoting. If you deal with CSV files and you use Python the csv module can make your life a bit easier.
Dealing with CSV files in Python probably couldn't be much easier. For example purposes, let's use the following CSV file that contains 3 columns "A", "B", and "C D":
$ cat test.csv A,B,"C D" 1,2,"3 4" 5,6,7
The following python program reads it and displays its contents:
import csv ifile = open('test.csv', "rb") reader = csv.reader(ifile) rownum = 0 for row in reader: # Save header row. if rownum == 0: header = row else: colnum = 0 for col in row: print '%-8s: %s' % (header[colnum], col) colnum += 1 rownum += 1 ifile.close()
When run it produces:
$ python csv1.py A : 1 B : 2 C D : 3 4 A : 5 B : 6 C D : 7
In addition, the csv module provides writer objects for writing CSV files. The following Python program converts our test CSV file to a CSV file that uses tabs as a value separator and that has all values quoted. The delimiter character and the quote character, as well as how/when to quote, are specifed when the writer is created. These same options are available when creating reader objects.
import csv ifile = open('test.csv', "rb") reader = csv.reader(ifile) ofile = open('ttest.csv', "wb") writer = csv.writer(ofile, delimiter='\t', quotechar='"', quoting=csv.QUOTE_ALL) for row in reader: writer.writerow(row) ifile.close() ofile.close()
Running it produces:
$ python csv2.py $ cat ttest.csv "A" "B" "C D" "1" "2" "3 4" "5" "6" "7"
My first task when starting to use the csv module was to write a function to try to determine what format the CSV file was in before opening it so that I could deal with commas and tabs and different quoting conventions:
import os import sys import csv def opencsv(filename): tfile = open(filename, "r") line = tfile.readline() tfile.close() if line == '"': quote_char = '"' quote_opt = csv.QUOTE_ALL elif line == "'": quote_char = "'" quote_opt = csv.QUOTE_ALL else: quote_char = '"' quote_opt = csv.QUOTE_MINIMAL if line.find('\t') != -1: delim_char = '\t' else: delim_char = ',' tfile = open(filename, "rb") reader = csv.reader(tfile, delimiter=delim_char, quotechar=quote_char, quoting=quote_opt) return (tfile, reader)
Being new to the csv module and making the common mistake of not reading the whole "man" page, I of course failed to notice that the csv module already contains something to do this called the Sniffer class. I'll leave using it as an exercise for the reader (and in this case the writer also).
Mitch Frazier is an Associate Editor for Linux Journal.
Getting Started with DevOps - Including New Data on IT Performance from Puppet Labs 2015 State of DevOps Report
August 27, 2015
12:00 PM CDT
DevOps represents a profound change from the way most IT departments have traditionally worked: from siloed teams and high-anxiety releases to everyone collaborating on uneventful and more frequent releases of higher-quality code. It doesn't matter how large or small an organization is, or even whether it's historically slow moving or risk averse — there are ways to adopt DevOps sanely, and get measurable results in just weeks.
Free to Linux Journal readers.Register Now!
- August 2015 Issue of Linux Journal: Programming
- Django Models and Migrations
- Hacking a Safe with Bash
- Secure Server Deployments in Hostile Territory, Part II
- The Controversy Behind Canonical's Intellectual Property Policy
- Huge Package Overhaul for Debian and Ubuntu
- Shashlik - a Tasty New Android Simulator
- KDE Reveals Plasma Mobile
- Embed Linux in Monitoring and Control Systems
- diff -u: What's New in Kernel Development