I tried scraping Reddit in 2025... here's what happens when you fight the API

Source: Dev.to

Let’s be real for a second.

Ideally, we’d all just pip install praw, grab an API key, and pull unlimited JSON data for our NLP projects or market research. That used to work, but the post‑2023 API changes have turned it into a nightmare.

I spent the last weekend trying to archive some threads from r/wallstreetbets for a sentiment‑analysis project and hit wall after wall:

• The 429 Errors. So many 429s.
• The Cost. The commercial tier pricing is aggressive.
• The Missing Data. Getting NSFW content or historical comments via the official API is now a hassle.

Below is an honest breakdown of the three ways you can still get data out of Reddit in 2025, ranked by “Headache Level.”

Method 1: The “Legacy” Way (Python + PRAW) 🐍

This is what every tutorial from 2020 tells you to do.

import praw

# Look at this clean code that will definitely get rate‑limited
reddit = praw.Reddit(
    client_id="...",
    client_secret="...",
    user_agent="my_user_agent"
)

Verdict: Great for building a bot that replies to comments, but terrible for data scraping. Pulling 10 000 comments will force your script to sleep for hours to respect the rate limits.

Method 2: The “Brute Force” Way (Selenium / Puppeteer) 🕷️

“Fine,” I thought. “I’ll just pretend to be a browser.” I fired up Selenium, wrote some selectors, and scraped about 50 pages before my IP got flagged. Parsing Reddit’s new HTML structure is a div‑soup nightmare.

Verdict: It works, but it’s slow—really slow. Maintaining headless Chrome instances just to get some text data feels like overkill.

Method 3: The “Local Desktop” Way (What Actually Worked) 🖥️

Reddit treats “real users” very differently from API calls. Browsing on a desktop lets you scroll infinitely with no blocks or limits. The solution isn’t a better script—it’s better emulation.

I started using Reddit Toolbox (disclosure: I built it out of frustration, but the tech is solid). Instead of fighting WAFs with Python requests, it uses a hybrid local browser engine that renders the page exactly like a user would, then scrapes the data into structured JSON/CSV in the background.

Why Local Extraction Wins in 2025

• Your IP, Your Rules: You aren’t sharing an API‑key quota with thousands of others.
• No Code: Sometimes you just want the CSV without debugging a BeautifulSoup script for hours.
• Media Handling: Downloading videos (v.redd.it) with sound is surprisingly hard with PRAW; desktop tools handle audio merging automatically.

Final Thoughts

If you are a student learning Python, stick with PRAW—it’s a great way to learn APIs. But if you actually need the data—like, yesterday—and you don’t want to maintain a scraping infrastructure, stop fighting the anti‑bot measures and move the scraping to the client side.

Happy scraping! 🚀

Originally published at Reddit Toolbox Blog.