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by lignuist 4400 days ago
I was referencing to "What if the character separating fields is not a comma?".

And there it clearly works. I used this technique a few times with success. If you find a CSV file that has mixed field separator types, then you probably found a broken CSV file.
1 comments
zAy0LfpBZLC8mAC 4400 days ago
No, it doesn't. What if there is #COMMA# in one of the fields?
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lignuist 4400 days ago
You just choose a placeholder that does not appear in the data. You could even implement it in a way that a placeholder is automatically selected upfront that does not appear in the data.

When it comes to parsing, the thing is that you usually have to make some assumptions about the document structure.

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zAy0LfpBZLC8mAC 4400 days ago
What if there is #COMMA, in one of the fields (but no #COMMA#)?

Yes, the assumption you have to make is called the grammar, and you better have a parser that always does what the grammar says, and global text replacement is a technique that is easy to get wrong, difficult to prove correct, and completely unnecessary at that.

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lignuist 4400 days ago
> What if there is #COMMA, in one of the fields (but no #COMMA#)?

What should happen? Since #COMMA is not #COMMA#, it gets not replaced, because it does not match.

Please keep in mind, that I replied to suni's very specific question and did not try to start a discussion about general parser theory. In practice, we find a lot of files that do not respect the grammar, but still need to find a way to make the data accessible.

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zAy0LfpBZLC8mAC 4400 days ago
What would happen is that you first would replace #COMMA, with #COMMA#COMMA# and then later replace that with ,COMMA# , thus garbling the data.

The way to make the data accessible is to request the producer to be fixed, it's that simple. If that is completely impossible, you'll have to figure out the grammar of the data that you actually have and build a parser for that. Your suggested strategy does not work.

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dbro 4399 days ago
Usually the person parsing the CSV data doesn't have control over the way the data gets written. If he did, he would probably prefer something like protocol buffers. CSV is the lowest common denominator, so it's a useful format for exchanging data between different organizations that are producing and consuming the data.

https://github.com/dbro/csvquote is a small and fast script that can replace ambiguous separators (commas and newlines, for example) inside quoted fields, so that other text tools can work with a simple grammar. After that work is done, the ambiguous commas inside quoted fields get restored. I wrote it to use unix shell tools like cut, awk, ... with CSV files containing millions of records.

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lignuist 4400 days ago
I used that strategy for parsing gigabytes of CSVs containing arbitrary natural language from the web - try to get these files fixed, or figure out a grammar for gigabytes of fuzzy data...

My approach never failed for me, so telling me that my strategy does not work is a strong claim, where it reliably did the job for me.

Your examples are all valid, but what you are describing are theoretical attacks on the method, while the method works in almost all cases in practice. We are talking about two different viewpoints: dealing with large amounts of messy data on one hand and parser theory in an ideal cosmos on the other hand.

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