PRAW VS NLTK

I'm... not sure I understand the question? PRAW still works just fine for "personal use" of the reddit API.

Thank you for pointing out. So there is no need then for the access token? Only with the refresh token is enough? To be honest I took a look at it but I did not expect that to be under authentication as strictly speaking, the user already made the authentication. Also I took a look at the code at https://github.com/praw-dev/praw/blob/master/praw/reddit.py and I did not get a hint whether was possible to pass it or not. I am just saying this to let you know I tried to search for the answer before asking. Again thank you for the help.

To get the relevant IDs, you can use something like PRAW to query the subreddit for the top 1000 posts for example.

Huge thanks to the contributors to PRAW, which is the Python package that does all the heavy lifting relating to Reddit's API that I need for this script.

However, in practice duplicate items were yielded with these smaller numbers. So I increased the limit briefly to 250 in October 2016, and then increased it finally to 301 in December 2016 in order to resolve https://github.com/praw-dev/praw/issues/673. That issue provides an explanation for how 301 came to be.

Why? You gotta be ready for any status code. Even 777.

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.