Note that, as the docs say:

csvfile can be any object which supports the iterator protocol and returns a string each time its next() method is called — file objects and list objects are both suitable.

So, you can always stick a filter on the file before handing it to your reader or DictReader. Instead of this:

with open('myfile.csv', 'rU') as myfile:
    for row in csv.reader(myfile):

Do this:

with open('myfile.csv', 'rU') as myfile:
    filtered = (line.replace('\r', '') for line in myfile)
    for row in csv.reader(filtered):

That '\r' is the Python (and C) way of spelling ^M. So, this just strips all ^M characters out, no matter where they appear, by replacing each one with an empty string.

I guess I want to modify the file permanently as opposed to filtering it.

First, if you want to modify the file before running your Python script on it, why not do that from outside of Python? sed, tr, many text editors, etc. can all do this for you. Here's a GNU sed example:

gsed -i'' 's/\r//g' myfile.csv

But if you want to do it in Python, it's not that much more verbose, and you might find it more readable, so:

First, you can't really modify a file in-place if you want to insert or delete from the middle. The usual solution is to write a new file, and either move the new file over the old one (Unix only) or delete the old one (cross-platform).

The cross-platform version:

os.rename('myfile.csv', 'myfile.csv.bak')
with open('myfile.csv.bak', 'rU') as infile, open('myfile.csv', 'wU') as outfile:
    for line in infile:
        outfile.write(line.replace('\r'))
os.remove('myfile.csv.bak')

The less-clunky, but Unix-only, version:

temp = tempfile.NamedTemporaryFile(delete=False)
with open('myfile.csv', 'rU') as myfile, closing(temp):
    for line in myfile:
        temp.write(line.replace('\r'))
os.rename(tempfile.name, 'myfile.csv')

The strip() method removes whitespace, including newlines.

fileout.writerow(line.strip())

The same question was asked earlier today here. Please check my comments on that regarding whether that would actually be a problem and the resolution if you really must resolve it.

Using Miller (mlr), a CSV-aware multi-purpose processing utility for various structured document formats, to clean up the whitespace of all fields:

$ cat file
"host1","host1","linux
server",""
"host2","host2","linux server",""

$ mlr --csv -N clean-whitespace file
host1,host1,linux server,
host2,host2,linux server,

This reads the data in file as header-less CSV records and applies the clean-whitespace operation to each. The clean-whitespace operation trims flanking whitespace from each field's value and combines consecutive whitespace characters into single spaces.

To instead only replace newlines with spaces, you may iterate over the fields with a short put expression:

*) { $[k] = gssub(v, "\n", " ") }' file
host1,host1,linux server,
host2,host2,linux server,

The gssub() function acts like gsub() in Awk, but does not treat its query argument like a regular expression (Miller also has gsub()).

If you feel you need to have the fields quoted even though it's not strictly needed (Miller adds quotes automatically if a field's value requires it), then use mlr with its --quote-all option:

$ mlr --csv -N --quote-all clean-whitespace file
"host1","host1","linux server",""
"host2","host2","linux server",""

$ mlr --csv -N --quote-all put 'for (k,v in $*) { $[k] = gssub(v, "\n", " ") }' file
"host1","host1","linux server",""
"host2","host2","linux server",""