public_domains's Introduction

public_domains

public_domains searches through a text (such as a novel like Moby Dick) and looks for possible host names to use. For more context about why such a thing was created see:

https://parkerhiggins.net/2022/11/public-sub-domains

Install

$ pip3 install public_domains

Use

Get a text, e.g. from Project Gutenberg:

wget https://www.gutenberg.org/files/2701/2701-0.txt

Run:

$ public_domains 2701-0.txt

tattooing.burned.like
fishermen.technically.call
violent.scraping.contact
irregular.between.here
verbally.developed.here
mizzen.rigging.like
eepeningly.contracted.like
tropic.whaling.life
trailing.behind.like
certain.fragmentary.parts
redundant.yellow.hair
personality.stands.here
wicked.miserable.world
...

Or if you prefer to do a "feeling lucky" search of gutenberg.org you can enter a title:

$ public_domains "Treasure Island"

famous.buccaneer.here
maroon.wriggling.like
keeping.better.watch
little.mountain.stream
admiral.benbow.black
breathing.loudly.like
breath.hanging.like
shirts.thrown.open
promontory.without.fail
feverish.unhealthy.spot
something.almost.like
following.important.news
lookout.shouted.land
spirits.eating.like
resumed.silver.here
stranded.beyond.help
trebly.worthless.life
including.checks.online
canvas.cracking.like
almost.entirely.exposed
flowers.ablowing.like
counting.hawkins.here
little.stranger.here
foliage.compact.like
strange.collection.like
seamen.aboard.here
creature.flitted.like
nighhand.fainting.doctor
crying.johnny.black
enough.little.place

If you'd like public_domains to check if the domain is available use the the --check option:

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public_domains's Issues

Consider improving performance

Perhaps it's overkill to change the ranking method, but I tested this on a 180 MB text file (probably not a good idea anyway) and it was still not done after some 20 hours of CPU time.

For comparison, an off-the-shelf BigramCollocationFinder.from_words(tokens).nbest(BigramAssocMeasures().pmi, 10000) takes about 5 minutes on the same machine and corpus, and it's probably easy to do better. (I cobbled together an example at https://framagit.org/nemobis/bots/-/blob/master/ngram_tlds.py .)

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