The csv module currently implements four quoting rules for dialects: QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC and QUOTE_NONE. These rules treat values of None the same as an empty string, i.e. by outputting two consecutive quotes. I propose the addition of two new rules, QUOTE_NOTNULL and QUOTE_STRINGS. The former behaves like QUOTE_ALL while the later behaves like QUOTE_NONNUMERIC, except that in both cases values of None are output as an empty field. Examples follow.

Current behavior (which will remain unchanged)

>>> csv.register_dialect('quote_all', quoting=csv.QUOTE_ALL)
>>> csv.writer(sys.stdout, dialect='quote_all').writerow(['foo', None, 42])
"foo","","42"

>>> csv.register_dialect('quote_nonnumeric', quoting=csv.QUOTE_NONNUMERIC)
>>> csv.writer(sys.stdout, dialect='quote_nonnumeric').writerow(['foo', None, 42])
"foo","",42

Proposed behavior

>>> csv.register_dialect('quote_notnull', quoting=csv.QUOTE_NOTNULL)
>>> csv.writer(sys.stdout, dialect='quote_notnull').writerow(['foo', None, 42])
"foo",,"42"

>>> csv.register_dialect('quote_strings', quoting=csv.QUOTE_STRINGS)
>>> csv.writer(sys.stdout, dialect='quote_strings').writerow(['foo', None, 42])
"foo",,42

As an enhancement, this could be added only to 3.5. The proposal sounds reasonable to me.

David: That's not a problem for me.

Sorry I can't provide real patches, but I'm not in a position to compile (much less test) the C implementation of _csv. I've looked at the code online and below are the changes that I think need to be made. My use cases don't require special handing when reading empty fields, so the only changes I've made are to the code for writers. I did verify that the reader code mostly only checks for QUOTE_NOTNULL when parsing. This means that completely empty fields will continue to load as zero-length strings, not None. I won't stand in the way of anyone wanting to "fix" that for these new rules.

typedef enum {
QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE,
QUOTE_STRINGS, QUOTE_NOTNULL
} QuoteStyle;

static StyleDesc quote_styles[] = {
{ QUOTE_MINIMAL, "QUOTE_MINIMAL" },
{ QUOTE_ALL, "QUOTE_ALL" },
{ QUOTE_NONNUMERIC, "QUOTE_NONNUMERIC" },
{ QUOTE_NONE, "QUOTE_NONE" },
{ QUOTE_STRINGS, "QUOTE_STRINGS" },
{ QUOTE_NOTNULL, "QUOTE_NOTNULL" },
{ 0 }
};

        switch (dialect->quoting) {
        case QUOTE_NONNUMERIC:
            quoted = !PyNumber_Check(field);
            break;
        case QUOTE_ALL:
            quoted = 1;
            break;
        case QUOTE_STRINGS:
            quoted = PyString_Check(field);
            break;
        case QUOTE_NOTNULL:
            quoted = field != Py_None;
            break;
        default:
            quoted = 0;
            break;
        }

" csv.QUOTE_MINIMAL means only when required, for example, when a\n"
" field contains either the quotechar or the delimiter\n"
" csv.QUOTE_ALL means that quotes are always placed around fields.\n"
" csv.QUOTE_NONNUMERIC means that quotes are always placed around\n"
" fields which do not parse as integers or floating point\n"
" numbers.\n"
" csv.QUOTE_STRINGS means that quotes are always placed around\n"
" fields which are strings. Note that the Python value None\n"
" is not a string.\n"
" csv.QUOTE_NOTNULL means that quotes are only placed around fields\n"
" that are not the Python value None.\n"

Samwyse, are these suggestions just based on ideas of what could be done or have you encountered real-world CSV data exchanges that couldn't be handled by the CSV module?

It doesn't look like a difficult change, but is it really needed? I guess my reaction is the same as Raymond's. Are there real-world uses where the current set of quoting styles isn't sufficient?

Used function PyUnicode_Check instead of PyString_Check

Yes, it's based on a real-world need. I work for a Fortune 500 company and we have an internal tool that exports CSV files using what I've described as the QUOTE_NOTNULL rules. I need to create similar files for re-importation. Right now, I have to post-process the output of my Python program to get it right. I added in the QUOTE_STRINGS rule for completeness. I think these two new rules would be useful for anyone wanting to create sparse CSV files.

If I understand correctly, your software needs to distinguish between

# wrote ["foo", "", 42, None] with quote_all in effect
"foo","","42",""

and

# wrote ["foo", None, 42, ""] with quote_nonnull in effect
"foo",,"42",""

so you in effect want to transmit some type information through a CSV file?

Skip, I don't have any visibility into how the Java program I'm feeding data into works, I'm just trying to replicate the csv files that it exports as accurately as possible. It has several other quirks, but I can replicate all of them using Dialects; this is the only "feature" I can't. The files I'm looking at have quoted strings and numbers, but there aren't any quoted empty strings. I'm using a DictWriter to create similar csv files, where missing keys are treated as values of None, so I'd like those printed without quotes. If we also want to print empty strings without quotes, that wouldn't impact me at all.

Besides my selfish needs, this could be useful to anyone wanting to reduce the save of csv files that have lots of empty fields, but wants to quote all non-empty values. This may be an empty set, I don't know.

Thanks for the update berker.peksag. I'm still not convinced that the csv module should be modified just so one user (sorry samwyse) can match the input format of someone's Java program. It seems a bit like trying to make the csv module type-sensitive. What happens when someone finds a csv file containing timestamps in a format other than the datetime.datetime object will produce by default? Why is None special as an object where bool(obj) is False?

I think the better course here is to either:

• subclass csv.DictWriter, use dictionaries as your element type, and have its writerow method do the application-specific work.

• define a writerow() function which does something similar (essentially wrapping csv.writerow()).

If someone else thinks this is something which belongs in Python's csv module, feel free to reopen and assign it to yourself.

The csv module is already type-sensitive (with QUOTE_NONNUMERIC). I agree, that we shouldn't modify the csv module just for one user and one program.

If a standard CVS library in Java (or other popular laguages) differentiates between empty string and null value when read from CSV, it would be a serious argument to support this in Python. Quick search don't find this.

I was thinking adding a more flexible API like:

...
spamwriter = csv.writer(csvfile, quoting_callable=lambda field: field is not None)
...

But that would require too much change in the csv module (or at least its implementation wouldn't be trivial).

I agree that subclassing DictWriter is a much better way to achieve this.

The correct handling of None values belongs to the csv module.

There is a use case to migrate a DB2 database to PostgreSQL.
DB2 has a command line tool "db2 export ..." which produces csv-files.
A row
['Hello', null, 'world']
is exported to
"Hello,,"world".

I would like to read in these exports with python and put it to PostgreSQL.

But with the csv library I can't read it in correctly. The input is converted to:
['Hello', '', 'world']
It should read as:
['Hello', None, 'world']

It is pretty easy to write a correct CSV reader with ANTLR but it's terribly slow.

And last but not least: if someone writes a list the reading should the identity.
Thats not True for the csv libraray.

Example:

import csv
hello_out_lst = ['Hello', None, 'world']
with open('hello.csv', 'w') as ofh:
    writer = csv.writer(ofh, delimiter=',')
    writer.writerow(hello_out_lst)

with open('hello.csv', 'r') as ifh:
    reader = csv.reader(ifh, delimiter=',')
    for row in reader:
        hello_in_lst = row

is_equal = hello_out_lst == hello_in_lst
print(f'{hello_out_lst} is equal {hello_in_lst} ?  {is_equal}')

The result is:
['Hello', None, 'world'] is equal ['Hello', '', 'world'] ? False

There is a real requirement for csv to handle an empty field vs a empty string """". csv.QUOTE_NOTNULL could be useful.

I have another use case. I want to import data into PostgreSQL using the COPY FROM command. This command can read a CSV input and it needs to distinguish empty string from null values.

Could we reconsider this issue and the proposed solution?

Okay, I'll reopen this, at least for the discussion of QUOTE_NONNULL. @erdnaxeli please given an example of how PostgreSQL distinguishes between the empty string and None cases. Is it a quoted empty string vs an empty field? If so, modifying @samwyse's original example, is this what you are after?

>>> csv.register_dialect('quote_notnull', quoting=csv.QUOTE_NOTNULL)
>>> csv.writer(sys.stdout, dialect='quote_notnull').writerow(['', None, 42])
"",,"42"

? Can you modify the original two patches to restrict to QUOTE_NONNULL?

Missed tweaking a couple settings.

Ugh... s/QUOTE_NONNULL/QUOTE_NOTNULL/

Not, Non, None... Perl would treat them all the same, right? <wink>

The MS Synapse has a CSV support in its COPY command that would benefit from the proposed csv.QUOTE_NOTNULL as it can be used when preparing data for import. As they reference the same RFC the CSV modul should support, both the proposed modifications would extend the RFC functionality with support for NULL/None values in the data.
The csv.QUOTE_STRINGS would enable a smaller file size.
Our case is that we are moving data into Synapse and have to resort to risk prone string replace functionality to provide the MS Synapse COPY a proper support for empty string and NULL

Python's csv module always returns strings. The Pandas CSV file read does infer types though.

% cat names.csv
first_name,last_name,age
Eric,Idle,47
John,Cleese,99
% python
Python 3.12.0a7+ (heads/main-dirty:330a942b63, Apr 14 2023, 06:59:05) [Clang 14.0.3 (clang-1403.0.22.14.1)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import csv
>>> for row in csv.reader(open("names.csv")):
...   print(row)
... 
['first_name', 'last_name', 'age']
['Eric', 'Idle', '47']
['John', 'Cleese', '99']
>>> ^D

If I can add my pinch of salt. Here we colide data and programming world. In data world None is a value of a type. In Python None is a separate type.
Using a paradigm from data world Oracle will equate empty string in strings with None. MS would not.
On the reader side if you have a CSV to read and you want to preserve NULL values normally in non quoted there would be a special character combination (^N or something) to represent a NULL, so reader would be able to parse it.
Then came Microsoft where someone was not checking with others and used quoted values which are more expensive and thought that it was a good idea to use empty field for None. And for this a reader needs to infere None.
In Python using non quoted values in CSV is good, but there is an if, when users encounter MS produced CSV and want None values preserved. Maybe MS is not the only one, but they stepped on my toe.

I certainly understand the desire to interoperate with the MS CSV ecosystem, as that has traditionally been the de facto "spec" for what it means to read and write CSV files. Still, I think the topic would be too involved to deal with properly between now and May 1. I propose limiting the change for now to just the writer, fixing any doc bits which suggest there are any changes to the reader, then going through the usual PEP process to investigate making changes to the semantics of the reader.

Would someone like to work on a PEP regarding type conversion in the reader?

I'll try to summarise the state of this issue:

The proposed feature was to add more quoting rules to the csv writer. This has been implemented (with docs and tests)¹. @serhiy-storchaka requested in #67230 (comment) that the issue be held open:

Wait, #29469 only changes writer, not reader. There are no tests for reader with new quoting styles, so we cannot be sure that nothing is broken. [...]

@samwyse remarked in #67230 (comment):

[..] I can't really see an easy way [for csv reader] to distinguish between «,,» and «,"",». So unless someone more knowledgeable than I thinks that it's simple, I propose that we punt this down the road, making the two new quoting rules illegal for reader objects for the time being. [...]

@smontanaro #67230 (comment):

Thinking more about the problem, I think it's wrong to do anything to the reader. In its entire history, the reader has never done any sort of type inference. That would be exactly what distinguishing an empty field from a quoted empty field would be, a (small) bit of type inference. [...]

The better course at this point would be to adjust the docs to state that the two new quoting rules have no effect in the reader. [...]

@smontanaro #67230 (comment):

Would someone like to work on a PEP regarding type conversion in the reader?

I suggest to close this as completed (the csv writer feature was implemented) and to open up a new issue regarding what to do with the csv reader.

the reader has never done any sort of type inference.

But it does.

>>> next(csv.reader(['123,"123"']))
['123', '123']
>>> next(csv.reader(['123,"123"'], quoting=csv.QUOTE_NONNUMERIC))
[123.0, '123']

If quoting style is QUOTE_NONNUMERIC, it returns non-quoted field as numeric. I expect the same for None.

As I already wrote, I suggest to summarise the needed reader changes in a new issue.

the reader has never done any sort of type inference.

But it does.

>>> next(csv.reader(['123,"123"']))
['123', '123']
>>> next(csv.reader(['123,"123"'], quoting=csv.QUOTE_NONNUMERIC))
[123.0, '123']

If quoting style is QUOTE_NONNUMERIC, it returns non-quoted field as numeric. I expect the same for None.

That's not really inferring the type in my book. It's effectively being told by the programmer that unquoted numeric strings are to be returned as numbers. If it was inferring the type, your first example would also spit out a float as the first value.

Right, and I suggest that QUOTE_NOTNULL is told by the programmer that unquoted empty strings are to be returned as None.

Right, and I suggest that QUOTE_NOTNULL is told by the programmer that unquoted empty strings are to be returned as None.

Can you please suggest this csv reader change in a new issue?

It is perhaps too late to make this change in 3.12, so we can open a new issue.

Opened #113732.