Miguel Tavares

Hey, @deanishe!

I just wanted to let you know that I found this awesome python module and with just a few tweaks I've managed to plug it into my workflow. It's now around 400 kB (!!)

Thank you for pointing me in the right direction. Sqlite was indeed the way to go.

Cheers!

50 minutes ago, deanishe said:

Here are the full-text search docs: https://www.sqlite.org/fts5.html

Thanks! This looks promising.

51 minutes ago, deanishe said:

I usually use a custom ranking function to apply different weightings to different columns (e.g. title vs tags vs body).

That's precisely one of the things that I'd like to implement.

2 minutes ago, deanishe said:

 

I have no idea if it's any use for your "related documents" feature.

It probably is, I think. If it has porter stemming (something I'd never imagine), I assume that stop word removal will be trivial. Then I can just feed a full text search with the "input document" and see what comes out. Right?

Just now, deanishe said:

As I indicated, I didn't really understand what you're doing with gensim and NLTK.

Neither did I, apparently. 

I had no idea sqlite did those things. I'll be looking into it after all.

Cheers!

You're right. The workflow is bigger that Obsidian itself.

There's a "Related Notes" feature that looks for similar text files. It initially used the simpler Jaccard similarity algorithm, but then I thought "Hey, let's do it properly with TF-IDF". So I imported NTLK for word tokenisation and Gensim for vectorization. It worked fine (on my computer), but everything else went sideways.

I don't know a thing about sqlite (or even what role a database would have in this feature), so I'll probably just go back to Jaccard and try to keep things simple.

Thanks for your help and advice.

Thanks, @deanishe!

Any tips on how I could package the workflow neatly and make it work with the default Python3 of macOS?

Hi! I've put together a workflow to interact with Obsidian. It relies heavily on some Python libraries like NLTK and Gensim, and I've done my best to package them, following advice from @deanishe found elsewhere on this forum.

However, I get an error when I try to run it on a different computer:

```
import regex._regex as _regex "ModuleNotFoundError:" No module named ‘regex._regex’

```

For what I've gathered, that may have something to do with the fact that Regex (required by NLTK) comes with a precompiled binary that may not play well with the other system or its python interpreter. 
 

All my scripts have a shebang pointing to `/usr/bin/python3` and I'm comfortable with it as a minimum requirement, but is there any hope of properly packaging Regex with the workflow?

Hi!

This is the first workflow that I share. I called it Glass Dome and its purpose is to prevent link rot inside markdown notes.

Basically, it uses the Internet Archive's Wayback Machine to take snapshots of web pages and the user's Dropbox account to save copies of images and other files.

It then returns markdown-formatted links to those.

You can download it here: https://github.com/macedotavares/Glass-Dome

Comments are very welcome, of course.

Cheers!