How to Scrape Reddit in 2026: 3 Methods That Still Work After the API Changes

Reddit changed everything in 2023 when they started charging for API access. Pushshift.io shut down. Third-party apps like Apollo went dark. And most scraping tutorials from before that era are completely broken now.

If you need Reddit data in 2026 — for market research, sentiment analysis, lead generation, or content monitoring — you have three realistic options. I'll walk through each one with working code, then compare them so you can pick the right approach for your use case.

Just need data fast? If you don't want to deal with OAuth apps, rate limits, or browser automation, Reddit Scraper on Apify handles everything out of the box. Enter a subreddit or search query, get structured JSON back. No setup required.

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Method 1: PRAW (Python Reddit API Wrapper)

PRAW is the official Python wrapper for Reddit's API. It handles OAuth for you and provides a clean interface for reading posts, comments, and user data.

Setup

First, you need a Reddit app. Go to reddit.com/prefs/apps, create a "script" type app, and grab your client_id and client_secret.

pip install praw

Working Example

import praw

reddit = praw.Reddit(
    client_id="YOUR_CLIENT_ID",
    client_secret="YOUR_CLIENT_SECRET",
    user_agent="data-collector/1.0"
)

for post in reddit.subreddit("python").hot(limit=10):
    print(f"{post.title} | Score: {post.score} | Comments: {post.num_comments}")

The Catch

PRAW works, but it comes with real limitations:

• Rate limits: 100 requests per minute for OAuth apps, 10 per minute without
• 1000-item cap: Reddit's API won't return more than ~1000 posts per listing, no matter what
• No historical data: You can't search posts older than what Reddit's search index holds (roughly 6-12 months depending on the subreddit)
• OAuth required: You need to register an app and manage credentials
• Fragile search: Reddit's native search is notoriously inconsistent — it misses results and doesn't support complex queries well

For quick, small-scale data pulls, PRAW is fine. For anything production-grade, you'll hit walls fast.

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Method 2: Playwright Browser Automation

If you need data that the API doesn't expose — or you want to bypass API rate limits — you can automate a real browser. Playwright is the go-to tool for this in 2026.

Working Example

from playwright.sync_api import sync_playwright

with sync_playwright() as p:
    browser = p.chromium.launch(headless=True)
    page = browser.new_page()
    page.goto("https://www.reddit.com/r/webdev/top/?t=week")
    page.wait_for_selector('shreddit-post')

    posts = page.query_selector_all('shreddit-post')
    for post in posts[:10]:
        title = post.get_attribute('post-title')
        score = post.get_attribute('score')
        print(f"{title} | Score: {score}")

    browser.close()

The Catch

Browser automation gives you flexibility, but the trade-offs are significant:

• Fragile selectors: Reddit redesigns their frontend regularly. The shreddit-post component could change tomorrow
• Slow: Each page load takes 2-5 seconds. Scraping 10,000 posts takes hours
• Resource heavy: Headless browsers eat RAM. Running multiple instances requires proper infrastructure
• Anti-bot detection: Reddit actively detects and blocks automated browsers. You'll need proxy rotation and fingerprint randomization
• Pagination complexity: Infinite scroll means you need to handle scroll-triggered lazy loading, which adds fragile timing logic
• No structured output: You're parsing HTML. Every field you need requires a separate selector that can break

Browser automation makes sense for one-off extractions or when you need something very specific the API doesn't provide. For regular data collection, it's a maintenance headache.

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Method 3: Ready-Made Scraper (No Code)

If you don't want to maintain code, deal with rate limits, or manage infrastructure, pre-built scrapers handle all of this for you.

Reddit Scraper on Apify is a ready-made actor that extracts posts, comments, and community data from Reddit. You configure what you want (subreddit, search term, sort order, date range), run it, and get clean JSON or CSV output.

What it handles that you'd otherwise build yourself:

• Proxy rotation and anti-bot bypass
• Pagination across thousands of results
• Structured output (title, score, author, comments, URLs, timestamps)
• Scheduling for recurring data pulls
• No rate limit concerns — it manages request pacing internally

It runs on Apify's cloud infrastructure, so there's nothing to install or deploy.

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Comparison Table

Factor	PRAW	Playwright	Ready-Made Scraper
Setup time	15-30 min	30-60 min	2 min
Cost	Free (API)	Free (self-hosted)	Pay-per-result
Max results	~1000 per query	Unlimited (slow)	Unlimited
Reliability	High (official API)	Low (selectors break)	High (maintained)
Maintenance	Low	High	None
Historical data	Limited	Limited	Yes
Infrastructure	Your server	Your server + browser	Cloud (managed)
Anti-bot handling	N/A	DIY	Built-in

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Which Method Should You Use?

Choose PRAW if you need small amounts of recent data, you're comfortable with Python, and you're okay with the 1000-item limit. It's free and officially supported.

Choose Playwright if you need very specific data the API doesn't expose, or you're building a one-off extraction for a unique page layout. Expect to maintain it.

Choose a ready-made scraper if you need production-grade data collection, historical data, or you want to skip the setup entirely. The trade-off is cost — but the time you save on maintenance usually makes up for it.

Whatever you pick, Reddit data is still accessible in 2026. The API changes killed the easy path, but they didn't kill the data. You just need the right tool for your specific use case.