I'm working with several huge CSV files - over 5 million rows total - and I ran into a problem: it turned out there were a few lines in those files that imported incorrectly because they were not correctly escaped.
Here's an example of an invalid line:
SAI Exempt,"Patty B"s Hats & Tees,LLC",,26 Broad St
The apostrophe in Patty B's Hats & Tees
is incorrectly represented here as a double quote, and since that's in a double quoted string it breaks that line of CSV.
I decided to filter out any rows that had an odd number of quotation marks in them - saving those broken lines to try and clean up later.
StackOverflow offered this regular expression for finding lines with an odd number of quotation marks:
[^"]*" # Match any number of non-quote characters, then a quote
(?: # Now match an even number of quotes by matching:
[^"]*" # any number of non-quote characters, then a quote
[^"]*" # twice
)* # and repeat any number of times.
[^"]* # Finally, match any remaining non-quote characters
I translated this into a ripgrep
expression, adding ^
to the beginning and $
to the end in order to match whole strings.
This command counted the number of invalid lines:
rg '^[^"]*"(?:[^"]*"[^"]*")*[^"]*$' --glob '*.csv' --count
04.csv:52
03.csv:42
02.csv:24
01.csv:29
Adding --invert-match
showed me the count of lines that did NOT have an odd number of quotes:
rg '^[^"]*"(?:[^"]*"[^"]*")*[^"]*$' --glob '*.csv' --count --invert-match
05.csv:2829
04.csv:812351
03.csv:961311
02.csv:994265
01.csv:995404
This shows that the invalid lines are a tiny subset of the overall files.
Removing --count
shows the actual content.
I used this for loop to import only the valid lines into a SQLite database:
for file in *.csv;
do rg --invert-match '^[^"]*"(?:[^"]*"[^"]*")*[^"]*$' $file | \
sqlite-utils insert my.db rows - --csv;
done;
To save the lines that contained odd numbers of double quotes I used this command:
rg '^[^"]*"(?:[^"]*"[^"]*")*[^"]*$' \
--glob '*.csv' \
--no-line-number \
--no-filename > saved.txt
Since I don't actually care which file they lived in - all of these CSV files share the same structure - I used --no-filename
to omit the filename from the results and --no-line-number
to omit the line number. The result is a saved.txt
file containing just the raw CSV data that I skipped from the import.
Created 2020-12-11T19:50:58-08:00, updated 2021-01-18T17:27:54-08:00 · History · Edit