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Unix for Poets (2013) [pdf] (stanford.edu)
63 points by kercker on June 14, 2016 | hide | past | web | favorite | 14 comments



Aw. I thought this was going to be more about using Unix as a natural language to write poetry, the way poetry competitions are held for programming languages.

I think it would be interesting if more programs were written with an aesthetic or artistic goal in mind, rather than functional. Like network code that has feelings, or fonts that get blurry the longer you look at them, or programs that, instead of crashing, simply find something else to do. Maybe a program written so the source is a poem about lost love, and results in bugs that randomly corrupts your memory on your lover's birthday.

I'm weird.


"The music of streams" by Doug McIlroy, an inventor of Unix pipes - http://www.cs.dartmouth.edu/~doug/powser.html


Inspiration hits

You could write such a paper

Pearls in our code


Nice introduction. Though I disagree his opinion that it is not worth learning awk in 2013. For quick operations on DSV files it fits perfectly for the command line and learning its compact syntax is not hard for (most) Unix users.


I particularly disagree with anyone's opinion that Awk is not worth learning, if they proceed to whip out "cut" as an example of something worth learning.

Awk generates solutions to certain problems involving record and field delimited text whose succinctness cannot be approached by common scripting languages.


Scripting languages, not even Perl?

Cut provides massive bang for buck , just learning "-f -d" and "-c"


A friend of mine is a poet. He is creating an entire mythological saga with an exact pool of letters per stanza. The same letters must appear in the same amounts in every one. He has programmed his own tools. I think he uses Python. It brings a certain awesome vibe to the story. It's a bit like photography in colored versus natural light.


For comparison:

https://en.wikipedia.org/wiki/Eunoia_(book)

https://en.wikipedia.org/wiki/Constrained_writing

I recommend finding people with letter-related synesthesia and showing them your friend's poetry!


I've been encountering a lot of deep humanities types lately who nevertheless are not mathematically incompetent, have math knowledge up to (say) first-year and can code competent small-script Python just fine thank you. And frankly, we need more of this. The STEM/humanities divide is artificial, and any competent intelligent person needs to be able to sling both to at least a basic level.


It's kind of a big field by now: https://en.wikipedia.org/wiki/Digital_humanities

One of the earliest triumphs (from the scholarly point of view, although it's also super-scary for privacy) is the success of stylometry for authorship attribution of unknown books, letters, and manuscripts.

https://en.wikipedia.org/wiki/Stylometry

I had a high school teacher who (as an English grad student) used a concordance to make an argument about Mark Twain's vocabulary, showing either when a particular work was likely written or when Twain likely read some other work (I forgot which). But that kind of thing and even more impressive inferences would be pretty routine today using computer tools.


Yeah, this stuff is marvellous. These days it's not even "digital humanities", it's really just "humanities". All this human interaction stuff we do is what humanities people are there to understand, whether digital or not, and that too requires some understanding of the machine.


Does anyone know of a good collection of exercises for other UNIX tasks besides text-based ones like this?


The great trajedy of Unix -- and of of the greater trajedies of computation -- is that the composable, user-visible components that made Unix great have never been matched in later stuff, not even in Unix stuff.

We have lots of systems which make software modular and composable, but they are not for the end user. At best they end up being build-blocks for programmers who make gigantic black boxes. More often, programmers of gigantic black boxes struggle with tools and libraries that are themselves gigantic black boxes.


Who can post a copy of nyt_200811.txt somewhere? This resource looks great, but it seems you need shell access at Stanford to get a copy of the example data set used?




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