Reddit Scraper 🤖

Scrape Reddit posts, comments, subreddits, search results, and user profiles — fast, at scale, and without a Reddit API key or login. Extract engagement metrics, media URLs, nested comment threads, and 35+ structured fields from any public Reddit content.

Perfect for market research, brand monitoring, sentiment analysis, trend tracking, lead generation, and feeding LLMs/RAG pipelines with real Reddit discussions.

Why this scraper

• 🔑 No API key, no Reddit account — just run it.
• ⚡ Fast & concurrent — processes posts in parallel; a lightweight metadata-only mode for cheap, high-speed monitoring.
• 🔎 Deep search coverage — returns several times more results per query than a basic search.
• 💬 Full comment threads — nested replies, optionally flattened into one row per comment.
• 🧱 35+ structured fields per post, ready for analysis or the API/MCP.
• 💸 Transparent, low cost — pay only for what you scrape.

What you can scrape

Source	How
Subreddit posts	subreddits: ["technology"]
Search across Reddit	searchTerms: ["machine learning"]
User posts & comments	usernames: ["spez"]
Any Reddit URL	startUrls — posts, subreddits, users, or search URLs

Two modes: tune speed vs. depth

	Full mode (default)	Fast mode
Set	fetchPostDetails: true	fetchPostDetails: false
Gets	title, body text, upvote ratio, media, all fields	post metadata only (title, score, author, dates, flags, media) — no body/ratio
Speed / cost	one extra request per post	metadata only → much faster & cheaper
Best for	full analysis	high-volume monitoring, dashboards

Comments are a separate switch — turn on scrapeComments to extract them (each comment is a billed result and its own row). See the Comments section below.

Input

Scraping sources (use one or combine)

Field	Type	Description
subreddits	string[]	Subreddit names (without r/ prefix)
searchTerms	string[]	Keywords to search across Reddit
usernames	string[]	Reddit usernames (without u/ prefix)
startUrls	URL[]	Direct Reddit URLs (posts, subreddits, users, search)

Scope, sorting & coverage

Field	Type	Default	Description
maxItems	integer	100	Max posts per source (1–10,000)
sort	string	hot	hot, new, top, rising, relevance, comments
timeFilter	string	all	Time range for top/search: hour, day, week, month, year, all
maximizeCoverage	boolean	true	For searches, gather results more thoroughly and de-duplicate → many more posts per query

Comments

Field	Type	Default	Description
scrapeComments	boolean	false	Turn ON to extract comments. Each comment is a billed result and its own row (linked to its post). OFF = comments are never fetched (no cost)
maxComments	integer	100	Max comments per post (only when scrapeComments is ON)
commentDepth	integer	3	Max depth of nested replies, 1–20 (only when scrapeComments is ON)

Filters

Field	Type	Default	Description
startDate	string	—	Only posts after this date (YYYY-MM-DD)
endDate	string	—	Only posts before this date (YYYY-MM-DD)
minScore	integer	—	Minimum post score
includeNSFW	boolean	false	Include NSFW posts
mediaOnly	boolean	false	Only posts with images, videos, or galleries

Performance & advanced

Field	Type	Default	Description
fetchPostDetails	boolean	true	Fetch full post detail (body, upvote ratio, comments). Turn off for fast, cheap metadata-only runs
maxConcurrency	integer	5	How many posts to process in parallel (1–20)
customMapFunction	string	—	JavaScript to transform each result. Receives post, must return an object

Output

Each post is one dataset item with 35+ fields:

{
  "id": "1abc123",
  "title": "Post title",
  "text": "Post body text",
  "url": "https://www.reddit.com/r/technology/comments/1abc123/...",
  "author": "username",
  "authorFullname": "t2_abc",
  "subreddit": "technology",
  "score": 15432,
  "upvoteRatio": 0.95,
  "numComments": 892,
  "postType": "image",
  "createdAt": "2026-04-15T10:30:00.000Z",
  "domain": "i.redd.it",
  "isNSFW": false,
  "hasMedia": true,
  "media": [{ "type": "image", "url": "https://i.redd.it/...jpeg" }],
  "linkFlair": "Discussion",
  "comments": [
    { "author": "commenter", "body": "Comment text", "score": 523, "depth": 0, "isOP": false, "replies": [] }
  ]
}

Field groups: core (id, title, text, author, subreddit, permalink, createdAt, postType, domain, linkUrl) · engagement (score, upvoteRatio, numComments, numCrossposts, totalAwards) · media (thumbnail, media[], hasMedia, hasVideo, hasImage, isGallery) · flags (isNSFW, isSpoiler, isStickied, isLocked, isArchived, isSelf) · flair (linkFlair, authorFlair) · metadata (subredditSubscribers, sourceType, sourceQuery, scrapedAt).

With scrapeComments: true, each comment becomes its own billed row (itemType: "comment") carrying body, author, score, depth, isOP, plus postId/postTitle/subreddit to link it back to its post — ideal for exporting a flat comment list.

Examples

Top posts from a subreddit (last week):

{ "subreddits": ["technology"], "maxItems": 50, "sort": "top", "timeFilter": "week" }

Search Reddit, maximum coverage:

{ "searchTerms": ["benq monitor"], "maxItems": 300, "sort": "relevance", "maximizeCoverage": true }

A post with its comments (each comment a billed row):

{ "startUrls": ["https://www.reddit.com/r/AskReddit/comments/1abc123/title/"], "scrapeComments": true, "maxComments": 100 }

Posts + comments as a flat list:

{ "subreddits": ["buildapc"], "maxItems": 50, "scrapeComments": true, "maxComments": 100 }

Fast, cheap monitoring (metadata only):

{ "subreddits": ["worldnews"], "maxItems": 500, "fetchPostDetails": false, "sort": "new" }

Tips on speed & cost

• Don't need body text? Set fetchPostDetails: false — dramatically faster and cheaper (no per-post fetch).
• Need comments? Turn on scrapeComments — each comment is a billed row. Set maxComments sensibly (e.g. 50–200); cost scales with how many comments you pull.
• Want more results from a search? Keep maximizeCoverage: true and raise maxItems.
• Raise maxConcurrency (e.g. 8–10) for more speed, or lower it to be gentler.

Limitations

• Scrapes public content only. Private or quarantined subreddits return an error.
• upvoteRatio and post body text require fetchPostDetails: true; comments require scrapeComments: true.
• Very large comment threads may not return every single nested reply.
• subredditSubscribers and award counts are best-effort and may be 0 when not exposed.

Disclaimer

This actor accesses publicly available data from Reddit and is provided for research and educational purposes. By using it you agree to comply with Reddit's User Agreement and all applicable laws. You are solely responsible for how the collected data is used. Always respect rate limits and the privacy of Reddit users.