Reddit Scraper - Real Vote Scores, Posts, Comments & Search

What does Reddit Scraper do?

Reddit Scraper is a Reddit API alternative that extracts public Reddit posts, comments, search results, and user submissions — without a Reddit account, OAuth, or official API key.

The difference that matters: many Store scrapers rely on RSS / recovery paths and return score: 0 even when the thread is huge. This Actor renders live pages and returns real vote data — score, upvoteRatio, and comment scores when Reddit exposes them.

Flat, spreadsheet-ready rows. Export JSON, CSV, or Excel. Schedule brand watches, feed RAG pipelines, or call it from Make / Zapier / n8n / Apify MCP.

Try it free with the default r/technology sample (5 posts) — no input required.

Who is this Reddit scraper for?

Brand & PR teams

• Monitor product and brand mentions across subreddits and search
• Rank threads by real engagement, not placeholder zeros
• Catch rising posts early with sort: "new" + date filters

Marketing & social listening

• Track competitor keywords and community sentiment
• Find high-upvote discussions for content and GEO research
• Export comment threads for qualitative analysis

Researchers, agencies & journalists

• Build clean datasets of public discussions
• Filter by subreddit, keywords, NSFW, and date window
• Reproducible runs you can schedule and audit

AI / ML / RAG builders

• Optional jsonl-finetune and rag-markdown outputs
• Training and retrieval corpora with honest ranking signals
• Wire via Apify API, webhooks, or MCP — no Reddit developer app

Why use this Reddit scraper?

• Real votes — score + upvoteRatio from rendered pages (never invent 0)
• Four modes — subreddit listings, search, user submissions, post + comments
• No Reddit login — public data only; no cookies or CAPTCHA solving
• Search that works — RSS discovery + browser enrichment for scores
• AI-ready formats — one charged post record; comments bundled free in AI modes
• Honest failures — blocked targets become uncharged target-status rows
• Apify native — schedules, datasets, proxy, API, Make/Zapier/MCP

How it compares

	This Actor	Typical RSS / “recovery” scrapers
Vote fields	Real score + upvoteRatio when visible	Often 0 / fake / missing
Modes	Listing + search + user + comments	Often listing or search only
AI exports	JSONL fine-tune + RAG markdown	Rare
Failures	Explicit target-status (uncharged)	Silent empty datasets
Auth	No Reddit API key	Same, but weaker vote fidelity

If you rank, filter, or train on engagement — zeros destroy your model. Use real votes.

Which mode should I use?

Mode	Best for	First-run tip
Subreddit URL / r/name	Hot / new / top community feeds	maxPostsPerSource: 25
searchQuery	Brand / topic discovery	Start with one keyword + timeFilter: "week"
searchSubreddit + query	In-community search	e.g. programming + typescript
User URL / u/name	Author timelines	/user/{name}/submitted/
Post URL + includeComments	Thread deep-dives	maxCommentsPerPost: 50, depth 2–3

What data can you extract?

Category	Fields
Post	id, title, author, subreddit, createdAt, permalink, selfText, link, domain
Votes	score, upvoteRatio, numComments
Flags	isSelf, isVideo, isNSFW, isSpoiler, isStickied, linkFlairText
Comment	id, postId, parentId, author, body, score, depth, permalink
Provenance	source, scrapedAt
Status	type: "target-status" when blocked / empty / private

Missing values stay null. This Actor never fakes a hidden score as 0.

Output example

{
  "type": "post",
  "id": "1wv1j68",
  "title": "NYC is now the first city in America that bans sketchy subscriptions",
  "author": "MarvelsGrantMan136",
  "subreddit": "technology",
  "score": 13599,
  "upvoteRatio": 0.982,
  "numComments": 420,
  "createdAt": "2026-10-01T14:53:16.572Z",
  "permalink": "https://www.reddit.com/r/technology/comments/1wv1j68/…/",
  "link": "https://www.theverge.com/…",
  "domain": "theverge.com",
  "isSelf": false,
  "isNSFW": false,
  "scrapedAt": "2026-10-01T22:30:00.000Z",
  "source": "https://www.reddit.com/r/technology/"
}

You can download the dataset as JSON, CSV, Excel, or HTML.

How to scrape Reddit (no API key)

1. Open Reddit Scraper in Apify Console.
2. Add URLs (r/technology, post links, u/name) or a searchQuery.
3. Keep Apify RESIDENTIAL proxy (US recommended) and ≥1024 MB memory.
4. Set maxPostsPerSource to 5–25 for a cheap trial.
5. Click Start → open Dataset → export.

Automate with Schedules, the API tab, webhooks, Make/Zapier, or Apify MCP.

How much does it cost to scrape Reddit?

Pay-per-event + usage — you pay for scraped posts/comments (+ Actor start), and for Apify compute / residential proxy separately. Set a max total charge on large jobs.

PPE headline: from about $0.65–$1.25 per 1,000 posts depending on your Apify plan tier (events only; CU + residential proxy are extra).

Event	FREE	BRONZE	SILVER	GOLD
Actor start (apify-actor-start)	$0.005	$0.005	$0.005	$0.005
Post scraped	$0.00125	$0.00108	$0.00085	$0.00065
Comment scraped	$0.00063	$0.00054	$0.00042	$0.00032

Per 1,000 posts (PPE only): $1.25 / $1.08 / $0.85 / $0.65 (FREE → GOLD).

Worked examples (FREE PPE only — proxy/CU not included):

Job	Approx. PPE
1,000 posts	~$1.25 + start
200 posts + 20 comments each	~$1.51 + start
AI format, 500 posts (comments bundled)	~$0.63 + start

target-status rows and empty invalid runs are not charged.

Default health-check (5 hot posts from r/technology) typically finishes in ~30 seconds on 1024 MB — far under Apify’s 300s ceiling.

Input examples

See the Input tab for every field. Patterns that convert well:

Subreddit listing

{
  "urls": ["https://www.reddit.com/r/technology/"],
  "sort": "hot",
  "maxPostsPerSource": 25
}

Aliases: "r/technology", "technology".

Brand / topic search

{
  "searchQuery": "your brand name",
  "sort": "new",
  "timeFilter": "week",
  "maxPostsPerSource": 50
}

Post + comments

{
  "urls": ["https://www.reddit.com/r/AskReddit/comments/abc123/title/"],
  "includeComments": true,
  "maxCommentsPerPost": 50,
  "commentDepth": 3
}

Time-sliced monitoring

Use sort: "new" with dateFrom / dateTo (ISO or YYYY-MM-DD). Pagination stops once posts fall before dateFrom — ideal for daily schedules.

AI / RAG export

{
  "urls": ["r/MachineLearning"],
  "maxPostsPerSource": 100,
  "includeComments": true,
  "outputFormat": "rag-markdown"
}

Tips for better results (and lower cost)

• Always RESIDENTIAL — datacenter / no-proxy paths hit login walls or empty shells.
• Start small (maxPostsPerSource: 5–25), then scale once the shape looks right.
• Prefer sort: "new" + date bounds for monitors instead of re-scraping “hot” forever.
• Fresh posts may show score: null until Reddit reveals votes — filter by age if needed.
• Schedule research/canary-input.json daily to catch breakage early.

Honest limitations

• Public listing depth is on the order of Reddit’s feed (~1,000).
• Comment trees are page-visible / capped (maxCommentsPerPost ≤ 500).
• Some comments omit score, permalink, or createdAt when Reddit’s public UI does not expose them; missing values stay null (never faked).
• Best-effort under blocks — logged + target-status, never silent “success” with empty truth.
• Not for private / authenticated Reddit data.

FAQ

Can I scrape Reddit without the official API?

Yes. This Actor scrapes public pages. No Reddit developer app, token, or login.

Why do other scrapers show score 0?

RSS and some recovery paths omit vote fields. Many Actors fill 0. We leave hidden scores as null and return live scores when present.

Do I need coding skills?

No. Paste URLs or a search query in Console. Developers can use the API / MCP when ready.

Can I export to Google Sheets, Slack, or Notion?

Yes — via Apify integrations, Make, Zapier, webhooks, or MCP connectors after the dataset is filled.

Is residential proxy required?

Strongly recommended (default). Without it, Reddit often serves login walls or JS shells with no posts.

Compliance

You are responsible for complying with applicable law and Reddit’s terms. Scrape public content for legitimate purposes. Do not collect personal data without a lawful basis. Prefer ethical brand monitoring, research, and public-community analysis.

Changelog

See ./CHANGELOG.md.