obsidian-file-path-to-uri VS obsidian-import-json

I can use obsidian-file-path-to-uri to convert them easily once they are in Obsidian but it's a manual process that has to be repeated 1800 times.

Install File Path to URI plugin

I'm not sure if this is the correct solution to your answer but there is a way to put images without Obsidian making a duplicate note of it inside the vault. You need to install the community plugin called File Path to URI. Then you need to follow these steps.

I found this. May that help? https://github.com/MichalBures/obsidian-file-path-to-uri

And ideally, i'd like to merge all these attachments into one attachment group or so. I don't really want to create new folder and load it all there as it is still a folder. Do you guys have better idea or 3rd party plugin to fix this? i found file path to URI but it doesn't solve my problem as i directly screenshot something and load it into the Obsidian without physically saving it onto the drive.

I haven't tried it, but theoretically it is possible - you can export actor as json, and then use Obsidian JSON/CSV importer plugin But you will need manually write template, that will be used to generate markdown from foundry json.

I am using obsidian-import-json to bring in a csv export of my Calibre ebook library (1800 books) into Obsidian where each row is a new book-specific markdown file with data like tags, ISBN, comments, ratings, and cover image location using a template. If you could help me convert the the windows file paths in either the individual markdown files after import or in the csv before import, that would be a great.

Hi! You could export your Google Sheets in csv format and try this plugin.

I looked into solutions some more, and came across https://github.com/farling42/obsidian-import-json. I'm not sure how well it will work yet, but looks like it can convert spreadsheet rows into separate files inside a folder. I tried your method of converting my spreadsheet into a markdown table by using this plugin to do it automatically. The markdown table was actually pretty laggy with that many rows though (unlike dataview which can show a lot of rows with no lag).