The problem with CSV is that there's no clear standard, so even if you do reach for a library to parse it, that doesn't ensure compatibility.

Same for JSON though. What Python considers a valid JSON might not be that if you ask a Java library.

JSON has a clearly-defined standards: ISO/IEC 21778:2017, IETF RFC 7159, and ECMA-404. Additionally, Crockford has had a spec available on json.org since it's creation in 2001.

Do you have any examples of Python, Java, or any of the other Tiobe top 40 languages breaking the JSON spec in their standard library?

In contrast, for the few of those that have CSV libraries, how many of those libraries will simply fail to parse a large number of the .csv variations out there?

Not to mention that stuff like Excel loves to export CSV files in "locale specific ways".

Sometimes commas to delimiter, sometimes semicolons, floating point values might have dots or commas to separate fraction digits.

Not to mention text encodings, Ascii, western european character sets, or maybe utf-8 or whatever...

It's a bloody mess.

That’s why we just email the sheets around like it’s 1999 :)

You need more than a standard; that standard has to be complete and unambiguous. What you're looking for is https://github.com/nst/JSONTestSuite

EDIT: The readme's results are from 2016, but there's more recent results (last updated 5 years ago). Of the 54 parsers /versions tested, 7 gave always the expected result per the spec (disregarding cases where the spec does not define a result).

It falls down under very large integers -- think large valid uint64_t values.

JSON doesn't fail for very large values because they are sent over the wire as strings. Only parsers may fail if they or their backing language doesn't account for BigInts or floats larger than f64, but these problems exist when parsing any string to a number.

And indeed applies to CSV as well: it's just strings at the end of the day, its up to the parser to make sense of it into the data types one wants. There is nothing inherently stopping you from parsing a JSON string into a uint64: I've done so plenty!

Example? I know there's some ambiguity over whether literals like false are valid JSON, but I can't think of anything else.

That _shouldn't_ be ambiguous, `false` is a valid JSON document according to specification, but not all parsers are compliant.

There's some interesting examples of ambiguities here: https://seriot.ch/projects/parsing_json.html

Trailing commas, comments, duplicate key names, for a few examples.

Trailing commas and comments are plainly not standard JSON under any definition. There are standards that include them which extend JSON, sure, but I'm not aware of any JSON library that emits this kind of stuff by default.

I'm not aware of any CSV library that doesn't follow RFC4180 by default, and yet... this whole thread.

There is a clear standard and it's usually written on an old Word '97 doc in a local file server. Using CSV means that you are the compatibility layer, and this is useful if you need firm control or understanding of your data.

If that sounds like a lot of edge-case work keep in mind that people have been doing this for more than half a century. Lots of examples and notes you can steal.

https://datatracker.ietf.org/doc/html/rfc4180 exists

And does Excel fully comply and more imprtantly tell you when the CSV file is wrong

No. Excel's fault. Not CSV. There are plenty of busted CSV parsers (and serializers) too.

> It's just that people tend to use specialized tools for encoding and decoding it instead of like ",".join(row) and row.split(",")

You really super can't just split on commas for csv. You need to handle the string encodings since records can have commas occur in a string, and you need to handle quoting since you need to know when a string ends and that string may have internal quote characters. For either format unless you know your data super well you need to use a library.

Right, obviously.

Yes but people don't