
Research
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A brand-squatted TanStack npm package used postinstall scripts to steal .env files and exfiltrate developer secrets to an attacker-controlled endpoint.
csvparse
Advanced tools
CSV Parse is a simple state-machine based approach to parsing CSV files. Its creation was motivated after dealing with some CSV parsers that could not properly handle strings with null bytes. It is not very fast, and definitely not very memory efficient, but if you want to explore simple CSV parsing, look no further. If you have CSV files that are incorrectly formatted, you can pretty easily modify the code to patch them up.
CSV parse supports reading from files or a buffer.
from csv_parse import read
data = read("/home/user/foo.txt")
from csv_parse import parse
my_string = 'foo,bar\nbaz,bat'
size = len(my_string)
data = parse(my_string, size)
CSV Parse also supports escaping, custom delimiters and newlines, and custom quoting.
data = read("/home/user/foo.txt", field_separator=',', null_as="", newline="\n", quote='"')
FAQs
A simple state-machine based CSV parser.
We found that csvparse demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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