django-compressor VS marked

In general, you can use almost any plain JS library by simply loading it in your view template. For forms specifically, you can write custom widgets and define dependencies to libraries via form assets. django-compressor might be worth a look if you go heavy on this.

Idk, it depends on how much you care about the page loading time. Even without the PurgeCSS filter, I would recommend the Django Compressor app. I use it on all my websites. It automatically merges your css/js files and minifies them (removes white spaces, comments, etc.). It also creates a unique name for the combined CSS so if you changed your CSS files, your users will always see the fresh version, not the cached by the browser one.

django_compressor - for merging and minimizing css and js assets

django-compressor with django-libsass for auto sass compilation

But isn't that what you have django-compressor for?

The external dependencies were downloaded into the static/ folder containing all frontend assets using yarn and a package.json. Other than that, yarn was not used. Next I ran a bash script that removed all files I did not need, keeping the javascript, css and font files that should be served. In html, these files where directly included. I knew that loading many files is bad, so I used django-compressor to combine them into one big file. Conveniently, this tool also provided me with a way to compile scss.

Next, install gray-matter to extract metadata from the front matter of markdown files, and marked to convert the markdown files to HTML:

📑 Marked Markdown parser. Use it to create your own markdown editor.

Vrite SDK provides a few built-in input and output transformers. These are functions, with standardized signatures to process the content from and into Vrite. In this case, gfmInputTransformer is essentially a GitHub Flavored Markdown parser, using Marked.js under the hood.

Another contestant in this realm is Bright[1]. It runs entirely on the server and doesn't increase bundle size as seen here[2]. Regarding parsing speed tree-sitter is without a doubt performant since it is written in Rust, but I don't have any problems "parsing on every keystroke" with a setup containing Marked[3], highlight.js[4] and a sanitizer. I did however experience performance issues with other Markdown parser libraries than Marked.

[1]: https://bright.codehike.org/

[2]: https://aihelperbot.com/test-suite

[3]: https://github.com/markedjs/marked

[4]: https://highlightjs.org/

The project uses markedJS to convert markdown into HTML, this is their GitHub page.

To handle pasting block Markdown content like this, I had to tap into ProseMirror and implement a custom mechanism (though somewhat based on TipTap’s paste rules), detecting starting and ending points of the blocks and parsing them with Marked.js.

I am using marked for markdown parsing together with marked-highlighting to handle syntax highlighting and everything is working as it should.

I'm trying to render user input using SvelteMarkdown (that uses marked).

GPT API returns data in markdown format. You can parse it using a Markdown library and string manipulation. On Electron app I developed https://jhappsproducts.gumroad.com/l/gpteverywhere, I used https://github.com/markedjs/marked and a code syntax highlighting package to display code blocks. And used JavaScript string manipulation to detect when code blocks start and end so I could add COPY/SAVE buttons to the blocks. I hope this helps, and happy coding! :)

Again, with streaming enabled, you’ll now receive new tokens as soon as they’re available. Given that OpenAI’s API uses Markdown in its response format, a full message will need to be put together from the incoming tokens and parsed to HTML, as accepted by the replaceContent function. For this purpose, I’ve used the Marked.js parser.