QuestPDF VS NLTK

What is QuestPDF? QuestPDF is an open-source .NET library for PDF document generation. It uses a fluent API approach to compose together many simple elements to create complex documents.

QuestPDF looks really good (I haven't used it) but I believe they changed their license recently.

I used that same library it worked great the only issue I had was the users would often have to manually set the scaling to fit to a page. I'm sure I could've fixed this in other ways if I was more competent with CSS but ended up just switching to use https://github.com/QuestPDF/QuestPDF in a backend instead of doing everything in front end.

Give this a try: QuestPDF

I think you should ask these questions in related discussion on Github: https://github.com/QuestPDF/QuestPDF/discussions/491

May I introduce you to QuestPDF!

➡️ James Newton-King ♔ on Twitter: "Coming in .NET 8: Route tooling for ASP.NET Core" / Twitter ➡️ Announcing .NET Community Toolkit 8.1 ➡️ Uno Platform 4.7 – New Project Template, Performance Improvements and more ➡️ C# Advent 2022 Awards | Cross Cutting Concerns ➡️ GitHub - QuestPDF ➡️ DNF Summit 2023 ➡️ .NET Frontend Day

Like many have suggested, I also cast my vote on QuestPDF. No more +50MB library including a Chrome browser to render HTML so a PDF of it can be created, which took 2-3 seconds each time. But with QuestPDF, it's so much faster!

Also, the library is open-source, so you can take a look at the exact implementation of the layout engine. It is inspired by Flutter and WPF, though optimized for pageable content: https://github.com/QuestPDF/QuestPDF/tree/main/Source/QuestPDF/Elements

alternatively, could we not simply split by common characters such as newlines and periods, to split it within sentences? it would be fragile with special handling required for numbers with decimal points and probably various other edge cases, though.

there are also Python libraries meant for natural language parsing[0] that could do that task for us. I even see examples on stack overflow[1] that simply split text into sentences.

[0]: https://www.nltk.org/

Check out https://www.nltk.org/ and work through it, it'll give you a foundational understanding of how all this works, but very basically it's just a fancy auto-complete.

NLTK Documentation

If this is True, then you need also Natural Language Toolkit to process the words.

In that case, you should definitely have a look at Python's nltk library which stands for Natural Language Toolkit. They have a rich corpus collection for all kinds of specialized things like grammars, taggers, chunkers, etc.

If not, start with Python's Natural Language Toolkit.

Try https://www.nltk.org it runs you through the basics. The book is here

In terms of programming languages, Python is a great first programming language. the learnpython subreddit has lots of good recommendations for resources to get started. Once you're comfortable with the language, NLTK would be a good place to start, and the docs have heaps of examples. Check it out https://www.nltk.org/

The most popular library to do this is NLTK though I believe you can use some of the popular AI API services today as well. Bloomberg launched one.