Synchronous ~180ms HTTP Scraper · Zero Proxies · Zero Headless Browsers
Scrape Reddit Posts & Comment Trees at $0.10 per 1K.
Stop maintaining brittle residential SOCKS5 proxy pools, Playwright stealth scripts, or 45-second Docker scraper queues. Scrape up to 100 subreddit posts or 200 nested comments per synchronous GET call at $0.10/1,000 items.
01 · PAY-AS-YOU-GO
$0.10 / 1K items · Never expires
0 Credits charged on empty keyword polls or 4xx/5xx upstream errors.
02 · ZERO OAUTH / ZERO COOKIES
No Reddit account or proxies needed
Skip 6-week commercial OAuth reviews, refresh tokens, and AWS/GCP 403 blocks.
03 · 10×–24× LOWER UNIT COST
Beats Official $0.24/1K calls & $1.50 actors
Up to 100 posts or 200 nested comments per call ($0.04–$0.06/1K with bonus).
04 · INSTANT FREE CREDITS
2,000 Free Credits on sign-up
Verified email anti-abuse (1× per developer), no credit card required.
Total Cost of Ownership (1M Items/Mo)
Why Engineering Teams Drop DIY Proxies & Container Scrapers
| Scraping Stack | Cost for 1,000,000 Items | Median Latency | Maintenance Burden |
|---|---|---|---|
| RedditDataAPI.io Gateway | $49.80 – $100.00 ($0 on empty/errors) | ~180ms synchronous JSON | Zero (single x-api-key header) |
| DIY Playwright + Residential Proxies ($8/GB) | $640 – $1,400+ bandwidth + EC2 | 3,500ms – 9,000ms | High (TLS fingerprinting, DOM breaks) |
| Batch Container Actors (Apify / Bright Data) | $1,500 – $2,500+ | 30,000ms – 60,000ms cold start | Async webhook/dataset polling |
| PRAW on AWS / Hetzner Datacenter IP | $240+ OAuth calls (100 QPM cap) | Blocked (403) or 5–25s per tree | OAuth token rotation & ToS risk |
Scrape Posts + Nested Comments in Python
200-comment trees with depth & parent_id.
import requests
API_KEY = "rd_live_your_api_key"
HEADERS = {"x-api-key": API_KEY}
# 1. Scrape newest mentions across all subreddits (0 Credits if empty)
posts = requests.get(
"https://api.redditdataapi.io/v1/posts/search",
params={"query": "postgres vector", "sort": "new", "limit": 50},
headers=HEADERS,
).json()["data"]["items"]
# 2. Scrape full nested comment tree (up to 200 comments in 1 call)
tree = requests.get(
"https://api.redditdataapi.io/v1/posts/comments",
params={"post_id": "1u0z4vz", "sort": "top", "limit": 200},
headers=HEADERS,
).json()["data"]["items"]Live Captured Comment Tree · post_id=1u0z4vz
{
"code": 0,
"provider": "https://redditdataapi.io",
"status": "ok",
"msg": "success",
"data": {
"post_id": "t3_1u0z4vz",
"items": [
{
"id": "oqlu8x4",
"comment_id": "t1_oqlu8x4",
"post_id": "t3_1u0z4vz",
"parent_id": "t3_1u0z4vz",
"author": "reallehnert",
"body": "Great News!",
"score": 86,
"depth": 0,
"is_submitter": false,
"created_utc": 1780995393,
"created_at": "2026-06-09T08:56:33.000Z",
"permalink": "https://www.reddit.com/r/SaaS/comments/1u0z4vz/new_rule_banning_a_saas_product_category_no/oqlu8x4/"
},
{
"id": "oqlvi4c",
"comment_id": "t1_oqlvi4c",
"post_id": "t3_1u0z4vz",
"parent_id": "t3_1u0z4vz",
"author": "JouniFlemming",
"body": "The world is finally healing. Thank you!",
"score": 48,
"depth": 0,
"is_submitter": false,
"created_utc": 1780996070,
"created_at": "2026-06-09T09:07:50.000Z"
}
],
"count": 2,
"has_more": true
},
"meta": {
"endpoint": "/v1/posts/comments",
"credits_used": 2,
"cache_hit": false,
"latency_ms": 212
}
}Run a live scrape right now.
curl "https://api.redditdataapi.io/v1/subreddit/posts?subreddit=MachineLearning&sort=hot&limit=25" \
-H "x-api-key: rd_live_your_api_key"{
"code": 0,
"provider": "https://redditdataapi.io",
"status": "ok",
"msg": "success",
"data": {
"items": [
{
"id": "1xmjld9",
"post_id": "t3_1xmjld9",
"subreddit": "saas",
"subreddit_name_prefixed": "r/saas",
"title": "How we scaled our B2B SaaS to $42k MRR using automated Reddit brand mention alerts",
"selftext": "We built an internal keyword monitor across r/saas, r/startups, and r/entrepreneur...",
"author": "indie_founder_io",
"score": 384,
"upvote_ratio": 0.96,
"num_comments": 78,
"created_utc": 1762286400,
"created_at": "2026-11-04T20:00:00.000Z",
"url": "https://www.reddit.com/r/saas/comments/1xmjld9/how_we_scaled_our_b2b_saas/",
"permalink": "https://www.reddit.com/r/saas/comments/1xmjld9/how_we_scaled_our_b2b_saas/",
"domain": "self.saas",
"flair": "Case Study",
"over_18": false,
"is_nsfw": false,
"is_video": false,
"is_self": true
}
],
"count": 1,
"next_cursor": "t3_1xmjld9",
"cursor": "t3_1xmjld9",
"has_more": true,
"hasMore": true
},
"meta": {
"request_id": "c42d9f10-81e3-4c22-9118-092f1a8b1122",
"endpoint": "/v1/subreddit/posts",
"credits_used": 2,
"credits_remaining": 249998,
"cache_hit": false,
"data_age_seconds": 0,
"latency_ms": 185
}
}Reddit Scraper API FAQ
Why use a synchronous Reddit Scraper API instead of Playwright, Crawlee, or residential proxies?
Reddit blocks datacenter ASNs (AWS, GCP, Hetzner, DigitalOcean) with HTTP 403/429 and serves heavy Shire/Lit web components that burn 3–8 MB of residential proxy bandwidth ($0.03–$0.08) per page. RedditDataAPI.io returns clean JSON in ~180ms for $0.0001 per post or comment ($0.10/1K).
How many posts and comments can I scrape in a single HTTP request?
Up to 100 posts per call on /v1/subreddit/posts, /v1/posts/search, and /v1/users/posts, and up to 200 flattened nested comments (with depth and parent_id) per call on /v1/posts/comments.
Can I convert a scraped Reddit thread directly into Markdown for LLMs?
Yes. Use our free online Reddit Thread to LLM Markdown tool at /tools/reddit-thread-to-markdown or fetch /v1/posts/detail + /v1/posts/comments via API.