I wrote an HTML parser in python used to extract data to look like this in a csv file:
itemA, itemB, itemC, Sentence that might contain commas, or colons: li
CSV files usually use double quotes "
to wrap long fields that might contain a field separator like a comma. If the field contains a double quote it's escaped with a backslash: \"
.
Yes, delimiters separate values within each line of a CSV file. There are two strategies to delimiting text that has a lot of punctuation marks. First, you can quote the values, e.g.:
Value 1, Value 2, "This value has a comma, <- right there", Value 4
The second strategy is to use tabs (i.e., '\t'
).
Python's built-in CSV module can both read and write CSV files that use quotes. Check out the example code under the csv.reader function. The built-in csv module will handle quotes correctly, e.g. it will escape quotes that are in the value itself.
As I suggested informally in a comment, unique just means you need to use some character that won't be in the data — chr(255)
might be a good choice. For example:
Note: The code shown is for Python 2.x — see comments for a Python 3 version.
import csv
DELIMITER = chr(255)
data = ["itemA", "itemB", "itemC",
"Sentence that might contain commas, colons: or even \"quotes\"."]
with open('data.csv', 'wb') as outfile:
writer = csv.writer(outfile, delimiter=DELIMITER)
writer.writerow(data)
with open('data.csv', 'rb') as infile:
reader = csv.reader(infile, delimiter=DELIMITER)
for row in reader:
print row
Output:
['itemA', 'itemB', 'itemC', 'Sentence that might contain commas, colons: or even "quotes".']
If you're not using the csv
module and instead are writing and/or reading the data manually, then it would go something like this:
with open('data.csv', 'wb') as outfile:
outfile.write(DELIMITER.join(data) + '\n')
with open('data.csv', 'rb') as infile:
row = infile.readline().rstrip().split(DELIMITER)
print row