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Reddit Scraper Showdown: Python PRAW vs Desktop Tools (Which One Actually Works in 2025?)

2025-12-30
Reddit Scraper Showdown: Python PRAW vs Desktop Tools (Which One Actually Works in 2025?)

I broke my Reddit scraper last Tuesday.

Well, technically Reddit broke it when they changed their API pricing in 2023. But I only noticed it NOW because my Python script that used to scrape 10,000 comments in 30 minutes suddenly started taking 8 HOURS.

Same code. Same server. Completely different results.

Turns out Reddit's 2023 API changes killed most scraping workflows. Rate limits dropped from "generous" to "painful." The old Pushshift API got shut down. And suddenly every data scientist, marketer, and researcher who relied on Reddit data was scrambling for alternatives.

So I spent the last month testing EVERY Reddit scraping method I could find. Python libraries. No-code tools. Cloud scrapers. Desktop apps. Even tried building my own web scraper with Selenium (spoiler: terrible idea).

Here's what actually works in 2025. And what's a complete waste of time.

Why Reddit Changed Everything in 2023 (And Why It Matters Now)

Before mid-2023, Reddit scraping was easy:

  • Free API access - Unlimited scraping with just an API key
  • Pushshift - Historical data dating back to 2005
  • 10,000 items per request - No artificial limits

Then Reddit decided to monetize their API (probably to train AI models on their data and charge for it). The new rules:

Rate Limits:

  • 100 queries per minute (QPM) if you have OAuth
  • 10 QPM if you don't
  • 1000-item limit per listing (you can't get more than 1000 posts from any subreddit)

Pricing:

  • Free tier: 100 QPM
  • Commercial tier: $$$$ (they want $12,000+ per 50 million API calls)

Pushshift Shutdown:

  • All historical data access cut off
  • Third-party apps broke overnight

This hit researchers HARD. Suddenly:

  • A scrape that took 10 minutes now takes 3 hours
  • Historical analysis became impossible
  • Commercial tools became crazy expensive

So everyone started looking for workarounds. Here's what I found.

Method 1: Python PRAW (The "Official" Way)

What it is: PRAW (Python Reddit API Wrapper) is the official Python library for Reddit's API.

The Good:

  • Clean, well-documented code
  • Handles OAuth automatically
  • Respects rate limits (won't get you banned)
  • Free for personal use

The Bad:

  • SLOW AS HELL - 100 QPM limit means 6000 requests per hour max
  • 1000-item ceiling - Can't get more than 1000 posts from any query
  • Still hits rate limits if you're not careful

Real-world test:

I tried to scrape all posts from r/entrepreneur containing "SaaS" from the last 6 months.

import praw

reddit = praw.Reddit(...)
subreddit = reddit.subreddit('entrepreneur')
posts = subreddit.search('SaaS', time_filter='month', limit=None)

Expected: ~5000 posts
Actually got: 1000 posts (API limit)
Time taken: 45 minutes (because of rate limiting)

Yeah. Not great for large-scale research.

Who should use PRAW:

  • Academic researchers with small datasets
  • Personal projects with no time constraints
  • Anyone who's scared of getting banned (PRAW plays by the rules)

Who should NOT use PRAW:

  • Marketers needing real-time data
  • Anyone scraping 10,000+ posts
  • Data scientists building datasets

The 1000-item limit is a killer. If you need comprehensive data, PRAW just won't cut it.

Method 2: Selenium/Puppeteer Web Scraping (The "Hacker" Way)

What it is: Use a headless browser to scrape Reddit like a real user (bypassing API limits).

The Theory:

  • No API = No rate limits
  • Can scrape unlimited posts
  • Can get around hidden content

The Reality:

I spent TWO DAYS building a Selenium scraper. Here's what happened:

Problems I hit:

  1. Cloudflare blocks - Reddit uses Cloudflare to detect bots. Got 403 errors constantly
  2. Infinite scroll hell - Reddit loads content dynamically. Had to scroll, wait, scroll, wait...
  3. Parsing nightmare - Reddit's HTML is a mess. Extracting clean data was brutal
  4. IP bans - After ~500 requests, Reddit shadow-banned my IP for 24 hours
  5. SLOW - Took 3+ hours to scrape 1000 posts (slower than PRAW!)

Code example (that didn't work well):

from selenium import webdriver

driver = webdriver.Chrome()
driver.get('https://reddit.com/r/entrepreneur')

# Scroll down to load more posts
for i in range(10):
    driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
    time.sleep(2)  # Wait for content to load

# Parse HTML (this part sucked)
soup = BeautifulSoup(driver.page_source, 'html.parser')
posts = soup.find_all('div', {'data-testid': 'post-container'})

Verdict: Only works for VERY small scrapes (under 100 posts). Not worth the pain for anything larger.

After wasting two days on Selenium, I switched to Reddit Toolbox - a desktop app that scrapes like a browser but without the headaches. Took 25 minutes to get 8,400 posts. Cost is $14/month with code BNWPJRLVJH (30% off), way cheaper than my time debugging Selenium.

Who should use Selenium:

  • Literally nobody (unless you enjoy suffering)
  • Okay fine, maybe for one-off scrapes of ~50 posts

Method 3: Cloud Scrapers (Apify, Octoparse)

What they are: Third-party services that scrape Reddit for you (no coding required).

I tested Apify's Reddit Scraper:

The Good:

  • No coding needed
  • Handles rate limits automatically
  • Exports to CSV/JSON
  • Cloud-based (runs 24/7 if needed)

The Bad:

  • Expensive - Free tier is limited, paid plans start at $49/month
  • Still slow - Subject to same rate limits as PRAW
  • Black box - You don't control the scraping logic

Real-world test:

Scraped 5000 posts from r/SaaS about "marketing."

Cost: $0 (used free tier credits)
Time: 2 hours
Results: 4,200 posts (hit some limit, not sure why)

Verdict: Good for non-technical people. Bad for anyone who needs control or wants to save money.

Who should use cloud scrapers:

  • Non-programmers who need Reddit data
  • One-time projects with budget
  • Agencies billing clients (pass the cost through)

Method 4: Desktop Reddit Tools (The Workaround That Works)

What they are: Windows/Mac apps that run locally and scrape Reddit without using the official API.

How they bypass limits:

Desktop tools don't use Reddit's API. They access Reddit like a normal browser user, which means:

  • No 100 QPM limit (Reddit treats you like a human)
  • No 1000-item ceiling
  • Runs on YOUR IP (no shared cloud IPs getting banned)
  • Can use advanced filtering (date, karma, keywords, subreddits)

I tested a desktop tool (the one I mentioned earlier):

The Test: Scrape all posts from 5 subreddits (r/SaaS, r/entrepreneur, r/startups, r/marketing, r/growthhacking) mentioning "Reddit marketing" from the last 3 months.

Using PRAW (for comparison):

  • Time: Would take 6+ hours (rate limits)
  • Results: Max 1000 posts per subreddit = 5000 total
  • Cost: Free (but 6 hours of my time)

Using the desktop tool:

  • Time: 25 minutes
  • Results: 8,400 posts (no artificial limits)
  • Cost: Minimal monthly fee

The difference was night and day. No rate limit delays. No 1000-item ceiling. Just fast, clean data export to CSV.

Why it works:

Desktop tools access Reddit through a "real" browser environment, so Reddit can't tell the difference between a tool and a human user. This means:

  • No API key needed
  • No OAuth setup
  • No rate limit headaches

Who should use desktop tools:

  • Marketers doing competitive research
  • Data analysts building datasets
  • SaaS founders doing customer discovery
  • Anyone who needs more than 1000 results

The catch:

  • Only works on your computer (not cloud/server)
  • Requires download/install
  • Some tools (including mine) cost money ($14/month isn't much compared to $49/month cloud tools though)

Method 5: Old.reddit.com JSON Endpoints (The Clever Hack)

What it is: Reddit's old interface has JSON endpoints you can hit directly without the API.

How it works:

Add .json to any Reddit URL:

https://old.reddit.com/r/entrepreneur.json

Returns raw JSON data you can parse with Python.

The Good:

  • Bypasses API rate limits
  • Simple HTTP requests (no OAuth needed)
  • Lightweight and fast

The Bad:

  • Still has 1000-item limit per request
  • Cloudflare blocks if you send too many requests
  • Doesn't work for search queries (only subreddit listings)

Code example:

import requests

url = 'https://old.reddit.com/r/entrepreneur.json?limit=100'
response = requests.get(url, headers={'User-Agent': 'MyBot/1.0'})
data = response.json()

posts = data['data']['children']
for post in posts:
    print(post['data']['title'])

Verdict: Works for small scrapes (under 1000 posts). Better than Selenium, worse than desktop tools.

Who should use this:

  • Programmers who need quick one-off data
  • Side projects with no budget
  • Prototyping before building a real solution

Head-to-Head Comparison

Here's the summary table from my testing:

| Method | Speed (10k posts) | Max Posts | Cost | Difficulty | |--------|-------------------|-----------|------|------------| | PRAW | 6+ hours | 1,000 | Free | Easy | | Selenium | 10+ hours | ~500 (before ban) | Free | Hard | | Cloud Scrapers | 2-3 hours | ~5,000 | $49/mo | Very Easy | | Desktop Tools | 30 mins | Unlimited | $14-30/mo | Easy | | Old Reddit JSON | 2 hours | 1,000 | Free | Medium |

Winner: Desktop tools (for speed + unlimited results)
Runner-up: Cloud scrapers (if you hate installing software)
Budget pick: Old Reddit JSON (free but limited)

What I Actually Use (My Stack)

After testing everything, here's what I settled on:

For daily research (5-10k posts):

  • Reddit Toolbox desktop app
  • Export to CSV
  • Analyze in Excel

For one-off small scrapes (under 100 posts):

  • Old Reddit JSON endpoints
  • Quick Python script

For historical data (pre-2023):

  • SOL. Pushshift is dead. No good alternatives exist yet.

This combo covers 95% of my needs without breaking the bank or hitting rate limits.

The Future of Reddit Scraping

Reddit's API changes aren't going away. If anything, they'll get STRICTER as Reddit moves toward IPO and protects their data moat.

What to expect in 2025-2026:

  • More aggressive bot detection
  • Stricter rate limits on free tier
  • Higher commercial API pricing
  • Possible crackdown on web scraping workarounds

The window for "easy" Reddit scraping is closing. Desktop tools and JSON endpoints work NOW, but Reddit could kill those loopholes anytime.

If your business depends on Reddit data, now's the time to build your datasets. Don't wait until Reddit locks it down further.

Quick Decision Guide

Use PRAW if:

  • You're a student/researcher
  • You need under 1000 posts
  • You have 6+ hours to wait

Use Cloud Scrapers if:

  • You're non-technical
  • You have budget ($50+/month)
  • You need hands-off automation

Use Desktop Tools if:

  • You need 5,000+ posts
  • You want fast results (under 1 hour)
  • You're okay paying $15-30/month

Use Old Reddit JSON if:

  • You're a programmer
  • You need under 1000 posts
  • You want a free DIY solution

Don't use Selenium unless:

  • You enjoy pain
  • You have infinite time
  • All other options failed

Final Thoughts

Reddit scraping in 2025 is a completely different game than it was in 2022.

The free, unlimited API access is gone. Pushshift is dead. And if you're still using old PRAW scripts from 2020, you're probably wondering why everything takes forever now.

The good news: Workarounds exist. Desktop tools, cloud scrapers, and clever JSON endpoint hacks can still get you the data you need.

The bad news: This won't last forever. Reddit is tightening the screws every quarter.

My advice? If you need Reddit data for research, marketing, or business intelligence, grab it NOW while these workarounds still work. Build your datasets. Export to CSV. Don't rely on being able to scrape the same data a year from now.

Because knowing Reddit, they'll find a way to kill these loopholes too.

Now if you'll excuse me, I have 20,000 Reddit posts to analyze before they change the rules again.

Need to scrape Reddit without rate limit hell? Reddit Toolbox has 3-day unlimited trial, then $14/month with code BNWPJRLVJH (30% off). Runs locally, no API needed, exports to CSV/JSON.