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Added 9 digits zip support + cities db updates #4

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hlorofos
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Added 9 digits zip support in format xxxxx-xxxx
Cities database has been extended by merge with National Weather Service

@thetylerhayes
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Is this going to get reviewed? We'd also love 9-digit zip support

@hollanddd
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Not sure if morally correct. I copied this library minus the fluff as i needed it for a project. In doing so I included your 9digit zips logic - I think as it is untested. The work is far from done. Feel free to lend a hand @ https://github.com/hollanddd/gladdress

@joshgachnang
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Totally morally fine. Code is under New BSD License. You can basically use it any way you want. Yay open source!

@thetylerhayes
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Thanks for responding @pcsforeducation

@hollanddd, @hlorofos: does one of you want to merge the others' commits into your forked repo?

I ask because @pcsforeducation is one of the original maintainers of this repo but is no longer with @SwoopSearch so does not have admin rights on the repo. And it sounds like @SwoopSearch itself is no more: https://twitter.com/servercobra/status/404104202273583104. So we can't merge any pull requests in this repo and it'd be nice to have someone else offer their repo up as the new active version.

@thetylerhayes
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Actually it looks like https://github.com/hollanddd/gladdress (mentioned earlier in the thread) already has 9-digit zip support which was the only other thing @hlorofos's fork had committed. So gladdress should work.

@hollanddd
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The other issues are addressed with some tests. gladdress is currently broken as i was trying to extract pre and post directionals from street names. I put it on pause until I heard from someone. I would love have a conversation and to be able to get some more eyeballs on this. Thanks @thetylerhayes @pcsforeducation

@joshgachnang
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I'll take a look at it over my Thanksgiving break. I like the additional tests you added. Also, I'll likely pull all the merge requests/issues to my fork of it and go from there.

I do want to rework how this works. I think something along the lines of breaking into useful tokens, applying a probability for each category to each token ("Wisconsin" is x% a state, y% part of the street name, z% of part of the city name) and guessing from there. The project as it stands right now is a lot of guess work and really only works for the US. Basically dropping each one into a bucket (state, city, etc) based on its position, what's already filled in, etc, only works for well formed addresses in a rigid order and is prone to failure if anything is missing.

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4 participants