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Honeybadger

Well-Known Member
AffKit Ninja
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Fresh motivation
lot to read

: new thread :)

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lot of useless fluff words in that IMHO machine reader thins that too ;P If the content is really new to you and not redundant ...

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about 572 words from that page I machine extracted the HTML to text

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Attached is a zip of 14 files 575~ words each

how i did it i can do this manually but this is better, and took 30 seconds of my time and 4 seconds of ChatGPT time
so, WTF :D "good grunt" go fetch boy :D
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I added:
Bash:
# You can add additional processing here if needed

done < "list"

html2text result.html > result.txt
echo "Done!"

I needed to 'learn this bit of code snippit

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Have fun ...
 

Attachments

  • linked-pages-text.zip
    25.6 KB · Views: 7
  • badger-reader.sh.zip
    573 bytes · Views: 7
Last edited:
You will have to apply this to your 'affiliate' use case but it still applies ...


and

Once you identify the biggest constraint in a project or process, you can iteratively improve on that constraint until it is no longer a limiting factor. After you solve the first constraint, there will be a new biggest constraint. You can then work to iteratively address that constraint, and so on. The goal of the theory of constraints is to address each of the weakest links until there are no more project limitations.


Solve the problems not create new ones ;)
 
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