Reddit Posts Search Scraper — Fast Parallel Reddit Search with Full Comment Trees

Search Reddit by keyword, subreddit or URL and pull back up to 10,000 posts per run with their full comment threads. Built for speed: posts are processed in parallel, so a large keyword sweep finishes in a fraction of the time a sequential scraper would take.

No Reddit API key, no browser, no login. Just sources, a total cap, and a sort mode.

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What you get

📝 Post data	💬 Comments	🔎 Diagnostics
Post ID and permalink	Comment author	Per-post success flag
Title and full body text	Comment body	Precise error message on failure
Author	Comment score	Per-post processing time
Score (net upvotes)	Creation timestamp	Proxy tier escalation in the log
Comment count	Nested replies, recursively
Subreddit	Configurable limit per post
Image URL and thumbnail
Creation timestamp (UTC)

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Key features

• Parallel processing. Posts are fetched concurrently rather than one after another — the single biggest difference in wall-clock time on large runs.
• One total cap, not per source. maxPosts is a hard ceiling across all sources combined (up to 10,000). The run stops the moment it hits that number, so your budget is predictable no matter how many keywords you throw in.
• Keywords, subreddits and URLs together. artificial intelligence, r/technology and https://www.reddit.com/r/news/ can all sit in the same input list; each source is scraped independently.
• Full comment trees. Every comment carries its own replies array, recursively — the discussion structure survives into your dataset.
• Comments are optional. maxComments: 0 gives a much faster metadata-only pass; up to 1,000 per post when you need depth.
• Four sort modes with a time window. Hot, New, Top and Rising; the time filter applies to Top and Rising and is ignored for Hot and New — stated plainly so you are never misled.
• Smart proxy fallback. No proxy → datacenter → residential, escalating automatically when Reddit blocks a request.
• Failures are visible, not silent. Posts that cannot be fetched are recorded with success: false, the exact error_message, and how long the attempt took.

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Use cases

• Large-scale keyword monitoring — sweep every mention of a brand, product or topic across Reddit in one run.
• Social listening at volume — thousands of posts with their comment threads, ready for sentiment analysis.
• Market & customer research — capture how a whole community talks about a problem you solve.
• Content and SEO research — the top posts for a keyword are a ranked list of what an audience actually wants.
• Trend detection — rising plus a short time window catches topics while they are still climbing.
• Competitive intelligence — track competitor mentions and read the replies for unfiltered opinions.
• Lead generation — find people asking for recommendations in your category.
• Research datasets — build large, timestamped corpora of public discussion with engagement metrics attached.

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How it works

1. You list sources — keywords, subreddits, or full Reddit URLs, one per line.
2. Each source is resolved: subreddits and URLs are read as listings; keywords run as Reddit searches.
3. Posts are queued and processed in parallel, with the global maxPosts cap enforced across the whole run.
4. Comments are fetched per post up to maxComments, with replies nested inside each comment.
5. On a block, the proxy tier escalates and the request is retried.
6. Each post is pushed to the dataset as it completes, successful or not.

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Quick start

1. Open the Actor and add your sources — e.g. artificial intelligence, r/technology.
2. Set Maximum Posts (total) — start with 25–50.
3. Set Maximum Comments per Post — use 0 for a fast first look.
4. Pick a Sort Order and, for Top/Rising, a Time Filter.
5. Click Start and export the Output tab as JSON (recommended) or CSV.

Minimal input

{
  "startUrls": ["https://www.reddit.com/r/news/"],
  "sortOrder": "top",
  "timeFilter": "week",
  "maxPosts": 50,
  "maxComments": 10
}

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Input configuration

Field	Type	Default	Description
startUrls	array	— (required)	Any mix of full Reddit URLs, subreddit names (news, r/news) and search keywords. One entry per line; each source is scraped independently.
sortOrder	string	top	hot (trending now), new (most recent), top (highest scoring), rising (gaining traction).
maxPosts	integer	10	Hard cap on total posts across all sources combined (1–10,000). The run stops as soon as this many posts are collected.
maxComments	integer	10	Comments per post (0–1000). 0 skips comments entirely — much faster.
timeFilter	string	week	hour, day, week, month, year, all. Applies to top and rising; ignored for hot and new.
proxyConfiguration	object	off	Optional. Smart fallback: no proxy → datacenter → residential when Reddit blocks.

Note on maxPosts: it is a run total, not a per-source limit. With five keywords and maxPosts: 100, you get 100 posts overall — not 500. This makes cost predictable; add sources freely without multiplying your bill.

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Output data

One row per post.

Field	Type	Description
post_id	string	Reddit post ID.
title	string	Post title.
body	string	Self-text body.
author	string	Poster's Reddit username.
subreddit	string	Subreddit the post belongs to.
score	number	Net upvotes.
num_comments	number	Total comments Reddit reports.
permalink	string	Reddit permalink path.
image_url	string	External / media URL the post points to.
thumbnail_url	string	Thumbnail image URL.
created_utc	number	Creation timestamp (Unix, UTC).
comments	array	{ author, body, score, created_utc, replies[] }, nested recursively.
success	boolean	Whether the post was scraped successfully.
error_message	string	Failure reason when success is false.
processing_time	number	Seconds spent on this post.

Example output

{
  "post_id": "1abcdef",
  "title": "Which AI tools have actually stuck in your workflow?",
  "body": "Curious what people still use six months later, not just what they tried once.",
  "author": "example_user",
  "subreddit": "artificial",
  "score": 3120,
  "num_comments": 487,
  "permalink": "/r/artificial/comments/1abcdef/which_ai_tools_have_actually_stuck/",
  "image_url": "",
  "thumbnail_url": "https://b.thumbs.redditmedia.com/…",
  "created_utc": 1786451234,
  "comments": [
    {
      "author": "another_user",
      "body": "Transcription and summarisation. Everything else fell away.",
      "score": 402,
      "created_utc": 1786454321,
      "replies": [
        {
          "author": "third_user",
          "body": "Same here — which one are you using?",
          "score": 61,
          "created_utc": 1786455000,
          "replies": []
        }
      ]
    }
  ],
  "success": true,
  "error_message": null,
  "processing_time": 0.87
}

Illustrative values — a live run returns current Reddit data.

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Usage examples

Wide keyword sweep with a predictable budget

{
  "startUrls": [
    "project management software",
    "time tracking app",
    "team collaboration tool"
  ],
  "maxPosts": 500,
  "maxComments": 15,
  "sortOrder": "top",
  "timeFilter": "month"
}

Brand monitoring, newest first

{
  "startUrls": ["your brand name"],
  "sortOrder": "new",
  "maxPosts": 200,
  "maxComments": 25
}

Save as a Task, attach a daily Schedule, and deduplicate on post_id.

Catch rising topics early

{
  "startUrls": ["r/startups", "r/SaaS", "r/entrepreneur"],
  "sortOrder": "rising",
  "timeFilter": "day",
  "maxPosts": 100,
  "maxComments": 0
}

Maximum-speed metadata harvest

{
  "startUrls": ["r/all"],
  "sortOrder": "hot",
  "maxPosts": 5000,
  "maxComments": 0
}

Deep discussion analysis

{
  "startUrls": ["https://www.reddit.com/r/AskReddit/"],
  "sortOrder": "top",
  "timeFilter": "year",
  "maxPosts": 50,
  "maxComments": 500
}

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Run it from your own code

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_API_TOKEN>")

run = client.actor("scraperx/reddit-posts-search-scraper").call(run_input={
    "startUrls": ["artificial intelligence", "r/technology"],
    "sortOrder": "top",
    "timeFilter": "week",
    "maxPosts": 200,
    "maxComments": 10,
})

for post in client.dataset(run["defaultDatasetId"]).iterate_items():
    if post["success"]:
        print(post["score"], "|", post["subreddit"], "|", post["title"])

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_API_TOKEN>' });

const run = await client.actor('scraperx/reddit-posts-search-scraper').call({
    startUrls: ['artificial intelligence'],
    maxPosts: 200,
    maxComments: 10,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

cURL

curl -X POST "https://api.apify.com/v2/acts/scraperx~reddit-posts-search-scraper/runs?token=<YOUR_APIFY_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"startUrls":["artificial intelligence"],"maxPosts":200,"maxComments":10}'

Integrations

Push results into Google Sheets, Airtable, Slack, Make, Zapier, Google Drive or your own endpoint via webhooks, and use Schedules for continuous keyword monitoring.

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Pricing

Pay-per-event: a small Actor-start charge plus a charge per post row delivered. Comments are nested inside the post row, so raising maxComments does not increase the number of billed rows — maxPosts is the cost lever, and because it is a run-wide total you can add as many sources as you like without multiplying the bill.

Current rates are on the Pricing tab of this Actor's page, and Apify shows an estimate before and during every run.

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Limits & good to know

• maxPosts is a run-wide total (max 10,000), unlike per-source limits in other scrapers. Plan your source list accordingly.
• timeFilter only applies to top and rising — Reddit ignores it for hot and new.
• Comments cost time, not rows. Very high maxComments values lengthen runs considerably.
• Reddit rate-limits aggressively. For big runs, enable Apify Proxy up front instead of waiting for the fallback.
• Only public subreddits and posts are accessible; private, quarantined and banned communities are not.
• Deleted or removed content is returned exactly as Reddit serves it ([deleted], [removed]).
• Rows with success: false include a precise error_message — useful for retrying just the failures.
• Default run options are 4 GB memory and a 1-hour timeout — raise the timeout for deep comment runs.

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FAQ

How is this different from a plain subreddit scraper? Two things: posts are processed in parallel for speed, and maxPosts is a single run-wide cap rather than a per-source limit — so many keywords cost the same as one.

Do I need a Reddit account or API key? No. It reads public Reddit data without authentication.

Can I search all of Reddit by keyword? Yes — put the keyword in startUrls as plain text.

Do I get nested replies? Yes. Each comment has a replies array containing its child comments, recursively.

How do I make it as fast as possible? Set maxComments: 0. Comment fetching is the main cost in run time.

Why is my time filter ignored? Because sortOrder is hot or new. Reddit only applies a window to top and rising.

Do I need proxies? Not to start — the Actor escalates automatically. Enable Apify Proxy in advance for large runs.

Which export format should I use? JSON to keep the comment trees; CSV works well with maxComments: 0.

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Legal & responsible use

This Actor collects only publicly available Reddit content — the same posts and comments any visitor can read without logging in. It does not log in, vote, post, or access private communities. Usernames and content belong to their authors and may constitute personal data: comply with Reddit's User Agreement, copyright, and GDPR or comparable regulations when processing it.

Support

Need extra fields, higher concurrency, or a custom Reddit monitoring pipeline? Open an issue on the Issues tab of this Actor.