Reddit Scraper - Posts, Comments & Subreddit Data
Pricing
Pay per usage
Reddit Scraper - Posts, Comments & Subreddit Data
Scrape Reddit subreddits, search results, and comment threads. Extract post titles, authors, scores, comment counts, body text, and full comment trees with nested replies. Sort by hot, new, top, or rising. Perfect for market research and sentiment analysis.
Pricing
Pay per usage
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0.0
(0)
Developer

Renzo Madueno
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0
Bookmarked
7
Total users
1
Monthly active users
2 days ago
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Reddit Posts & Comments Scraper
Extract Posts, Comments, and Community Insights from Any Subreddit
Turn Reddit into a structured dataset. This scraper collects posts and comments from subreddits, search results, and individual threads -- delivering titles, authors, upvote scores, comment text, timestamps, and flair data in a clean, export-ready format.
Reddit is one of the richest sources of authentic consumer opinion on the internet. Whether you are running market research, building a sentiment analysis pipeline, scouting content ideas, or monitoring brand mentions, this actor gives you programmatic access to the conversations that matter -- without rate limits or API key management.
What data can you extract?
Post data
| Field | Type | Description |
|---|---|---|
dataType | string | Record type identifier (post) |
postTitle | string | Title of the Reddit post |
author | string | Username of the post author |
subreddit | string | Subreddit where the post was published |
score | integer | Net upvote score (upvotes minus downvotes) |
commentCount | integer | Total number of comments on the post |
body | string | Self-text content of the post |
url | string | Link URL (external link posts) or post permalink |
postUrl | string | Direct Reddit permalink to the post |
createdUtc | string | UTC timestamp of when the post was created |
flair | string | Post flair or tag assigned by the author or moderators |
isStickied | boolean | Whether the post is pinned by moderators |
scrapedAt | string | ISO 8601 timestamp of when the data was collected |
Comment data
| Field | Type | Description |
|---|---|---|
dataType | string | Record type identifier (comment) |
author | string | Username of the comment author |
body | string | Full text of the comment |
score | integer | Net upvote score for the comment |
depth | integer | Nesting level (0 = top-level reply, 1 = reply to a reply, etc.) |
createdUtc | string | UTC timestamp of when the comment was posted |
postTitle | string | Title of the parent post |
postUrl | string | Permalink to the parent post |
scrapedAt | string | ISO 8601 timestamp of when the data was collected |
Use cases
- Market research -- Understand what real users say about your product, your competitors, or your industry by mining relevant subreddits and search queries.
- Sentiment analysis -- Feed Reddit post and comment data into NLP pipelines to measure community sentiment around brands, product launches, or events.
- Content ideation -- Discover what questions people ask, what problems they face, and what topics generate the most engagement in your niche.
- Competitive intelligence -- Monitor competitor mentions across Reddit to track public perception and identify strengths or weaknesses in their offering.
- Academic research -- Collect structured datasets of online discussions for social science, linguistics, or communication studies.
Input parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
subreddits | array | No | [] | Subreddit names to scrape (without r/), e.g., "technology", "programming" |
searchQueries | array | No | [] | Keywords to search across all of Reddit |
postUrls | array | No | [] | Direct Reddit post URLs to scrape comments from |
maxPostsPerSubreddit | integer | No | 100 | Maximum posts to extract per subreddit or search query (1--500) |
includeComments | boolean | No | false | Whether to extract comments from each post |
maxCommentsPerPost | integer | No | 100 | Maximum comments to extract per post (1--500) |
sortBy | string | No | "hot" | How to sort posts: hot, new, top, or rising |
timeFilter | string | No | "week" | Time period when sorting by top: hour, day, week, month, year, all |
maxConcurrency | integer | No | 3 | Number of browser pages to run in parallel (1--10) |
At least one subreddit, search query, or post URL must be provided.
Example output
{"dataType": "post","postTitle": "What's the best programming language to learn in 2026?","author": "dev_user123","subreddit": "programming","score": 1547,"commentCount": 342,"body": "I've been thinking about switching careers into software development. I have some experience with Python from college, but I'm wondering what the job market actually wants right now. Any advice?","url": "https://old.reddit.com/r/programming/comments/abc123/whats_the_best_programming_language/","postUrl": "https://old.reddit.com/r/programming/comments/abc123/whats_the_best_programming_language/","createdUtc": "2026-02-28T15:30:00Z","flair": "Discussion","isStickied": false,"scrapedAt": "2026-03-01T12:00:00.000Z"}
{"dataType": "comment","author": "senior_eng_42","body": "Honestly, it depends on what you want to do. For web development, JavaScript/TypeScript is still king. For data science and ML, Python is non-negotiable. For enterprise backend work, Java and Go are in very high demand.","score": 892,"depth": 0,"createdUtc": "2026-02-28T16:15:00Z","postTitle": "What's the best programming language to learn in 2026?","postUrl": "https://old.reddit.com/r/programming/comments/abc123/whats_the_best_programming_language/","scrapedAt": "2026-03-01T12:00:00.000Z"}
How much does it cost?
This actor uses a pay-per-result pricing model. You are charged for each data record (post or comment) that is successfully extracted.
- $0.0005 per result -- that is $0.50 per 1,000 records.
- Scraping 100 posts from a subreddit (without comments) costs approximately $0.05.
- Scraping 100 posts with 50 comments each costs approximately $2.55 (100 posts + 5,000 comments).
There are no monthly subscriptions or minimum commitments. You only pay for the data you extract.
Tips and tricks
- Use search queries for broad research. Subreddit scraping is best for focused communities. If you want to find every mention of a brand or topic across all of Reddit, use the
searchQueriesinput instead. - Enable comments selectively. Comments multiply the number of results quickly. If you only need post-level data (titles, scores, dates), leave
includeCommentsset tofalseto keep costs low and runs fast. - Sort by "top" for high-signal data. When researching popular opinions or frequently recommended products, sort by
topwith a time filter ofmonthoryearto surface the most upvoted content. - NSFW subreddits are supported. The scraper handles Reddit's age verification prompts automatically, so you can scrape any publicly accessible subreddit.
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