goawk VS miller

TIL: GoAWK [1] - A POSIX-compliant AWK interpreter written in Go, with CSV support.

[1]: https://github.com/benhoyt/goawk

Another nice project that I have used from time to time (and a very good source for insight) is the awk interpreter written in go https://github.com/benhoyt/goawk

No, I want exactly the opposite - it should be a , b,c as a single string field containing a literal comma, and c. For example, https://github.com/benhoyt/goawk has csv support. https://github.com/benhoyt/goawk/blob/master/docs/csv.md - more info.

I've had a go at solving this in this PR -- feedback welcome. I don't love it, but oh well, it solves the problem at hand. Your comment pointed me in the right direction, thanks again.

There are quite a few re-implementations of scripting languages like Lua in Go. I've written an AWK interpreter in Go.

github.com/benhoyt/goawk -> this library lets you embed an AWK runtime in your applications, very easy to use and useful for enabling some powerful scripting in things you build

Yes, that's right. With my simplistic UTF-8-based implementation it turned length() -- for example -- from O(1) to O(N), turning O(N) algorithms which use length() into O(N^2). See this issue: https://github.com/benhoyt/goawk/issues/93

Similar with substr() and other string functions, which when operating as bytes are O(1), but become O(N) when trying to count the number of codepoints as UTF-8.

GNU Gawk has a fancier approach, which stores strings as UTF-8 as long as it can, but converts to UTF-32 if it needs to (eg: the string is non-ASCII and you call substr).

It looks like Brian Kernighan's code has the same issue with length() and substr(). I'm going to try to email him about this, as I think it's kind of a performance blocker.

I'm not sure if it was via my personal website or just my GitHub profile, but I got my current job at Canonical due to the CTO there reaching out about my GoAWK project (https://github.com/benhoyt/goawk). I get regular recruitment emails because I have my CV/resume online: most of them are very low-effort, but 1 in 20 or something are interesting emails where the recruiter has actually looked at my website and will tailor it personally. I also just enjoy technical writing, and get joy out of sharing it on HN. So it's "worth it" for me.

jq and miller[1] are essential parts of my toolbelt, right up there with awk and vim.

[1]: https://github.com/johnkerl/miller

> This works really well if your problem can be solved in one or two liners.

My personal comfort threshold is around the 100-line mark. It's even possible to write maintainable shell scripts up to 500 lines, but it mostly depends on the problem you're trying to solve, and the discipline of the programmer to follow best practices (use sane defaults, ShellCheck, etc.).

> It go bad very quickly when, say, you have two CSV files and want to join them the sql-way.

In that case we're talking about structured data, and, yeah, Perl or Python would be easier to work with. That said, depending on the complexity of the CSV, you can still go a long way with plain Bash with IFS/read(1) or tr(1) to split CSV columns. This wouldn't be very robust, but there are tools that handle CSV specifically[1], which can be composed in a shell script just fine.

So it's always a balancing act of being productive quickly with a shell script, or reaching out for a programming language once the tools aren't a good fit, or maintenance becomes an issue.

[1]: https://miller.readthedocs.io/

where mlr is from https://github.com/johnkerl/miller

if this class of problems (i.e., csv/tsv data) is your main target you may find miller (https://github.com/johnkerl/miller) much more useful in the long run

That said, you may be interested in Miller (https://github.com/johnkerl/miller) which provides similar capabilities for CSV, JSON, and XML files. It doesn't use a SQL grammar, but that's just the proverbial lipstick on the thing. I'm not the author, but I have used it and I see some parallels in use cases at the very least.

worth giving Miller a shot

CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller