Reddit Post & Comment Scraper — Scrape Reddit with 99% Accuracy

Scrape unlimited comments from any posts with the highest comment accuracy on the Apify Store. Input any Reddit post URL and get complete, rich JSON data, including deeply nested comment threads, scores, author details, and awards.

Unlike other Reddit scrapers, this Actor does not use a browser. That means lower compute costs for you and faster extraction times. You get the full data Reddit has on a post, not just what's visible on the web page, in tree formated way just like on reddit.

Why This Reddit Scraper?

Feature	This Actor	Most Actors
Comment scraping accuracy	99% (100% for posts under 500 comments)	40-80% (miss nested replies)
Data depth	Full Reddit JSON (80+ fields per post)	Surface-level web scrape
Browser required	No (lightweight HTTP)	Yes (Playwright/Puppeteer)
Compute cost	Low	3-5x higher
Comment Tree	Already Created	Missing, need to do it yourself

What Data Can You Extract from Reddit?

Each scraped post includes 80+ data fields, far more than what you see on the Reddit website.

Post Data

• Content: title, selftext, URL, domain, permalink
• Metrics: score, upvotes, downvotes, upvote_ratio, num_comments, num_crossposts
• Author: username, author_fullname, author_premium, author_flair
• Subreddit: subreddit name, subscriber count, subreddit type
• Metadata: created_utc, edited, archived, locked, spoiler, over_18 (NSFW)
• Awards: all_awardings, total_awards_received, gilded
• Media: media, media_embed, is_video, thumbnail

Comment Data (nested with full reply threads)

• Content: body, body_html
• Metrics: score, ups, downs, controversiality
• Author: author, author_fullname, author_premium, author_flair
• Structure: parent_id, depth, link_id, is_submitter
• Metadata: created_utc, edited, stickied, distinguished, collapsed
• Nested replies: Full recursive reply threads preserved in tree structure

Use Cases of the Reddit Scraper

• Sentiment analysis — Extract thousands of comments with scores and metadata to analyze public opinion on any topic, product, or brand.
• AI/ML training data — Build training datasets from Reddit's rich comment threads for NLP models, chatbots, and language research.
• Brand monitoring — Track what people say about your brand or product by scraping comment threads from relevant subreddits.
• Market research — Analyze discussions in niche subreddits to understand customer pain points, feature requests, and competitor perception.
• Content research — Find high-engagement discussions and trending topics to fuel your content strategy.
• Academic research — Collect structured Reddit data for social science, linguistics, and behavioral research.

How to Scrape Reddit Posts and Comments

Step 1: Prepare Your Input

Add Reddit post URLs to the input. You can scrape one post or many at once.

{
  "urls": [
    {
      "url": "https://www.reddit.com/r/AskReddit/comments/1rcxhjq/people_40_what_actually_mattered_in_the_long_run/"
    },
    {
      "url": "https://www.reddit.com/r/technology/comments/example_post/"
    }
  ],
  "sort_type": "top",
  "max_comments": null,
  "lite_mode": false
}

Step 2: Configure Options

Parameter	Type	Default	Description
urls	Array	Required	List of Reddit post URLs to scrape.
sort_type	String	"top"	How to sort comments: top, best, new, controversial, old, qa.
max_comments	Number	null	Maximum number of comments to extract per post. Set to null for all comments.
lite_mode	Boolean	false	If true, returns lightweight comment objects with only core visible fields.

Step 3: Run and Export

Click Start to begin scraping. Once finished, go to the Dataset tab to view results. Export options:

• JSON — Full structured data, ideal for programmatic use
• CSV — Flattened data for spreadsheets (note: nested comments are best consumed as JSON)
• Excel — Direct download for quick analysis
• XML — For XML-based workflows
• API — Access results programmatically via the Apify REST API

Output Schema

Each dataset item represents one scraped Reddit post with its complete comment tree.

• Default mode (lite_mode: false): returns full Reddit JSON fields for post + comments.
• Lightweight mode (lite_mode: true): keeps full post fields but returns reduced comment objects.

Additional fields may appear depending on the post type.

Post Fields

Field	Type	Description
title	String	The title of the Reddit post
author	String	Username of the post author
author_fullname	String	Reddit's internal fullname (e.g., t2_abc123)
author_premium	Boolean	Whether the author has Reddit Premium
subreddit	String	Subreddit name (without r/ prefix)
subreddit_id	String	Reddit's internal ID for the subreddit
subreddit_subscribers	Integer	Number of subscribers in the subreddit
id	String	The post's unique ID
name	String	The post's fullname (e.g., t3_abc123)
selftext	String	Post text content (empty string for link posts)
selftext_html	String/Null	HTML-rendered version of the post text
score	Integer	Net score (upvotes minus downvotes)
ups	Integer	Number of upvotes
upvote_ratio	Number	Ratio of upvotes to total votes (0.0–1.0)
num_comments	Integer	Total comment count (as reported by Reddit)
created_utc	Number	Unix timestamp of creation
edited	Boolean/Number	false if not edited, or Unix timestamp of last edit
permalink	String	Relative URL path to the post
url	String	The original post URL or the submitted link URL
domain	String	Domain of the URL (e.g., self.AskReddit, i.imgur.com)
over_18	Boolean	Whether the post is NSFW
spoiler	Boolean	Whether the post is a spoiler
locked	Boolean	Whether the post is locked
archived	Boolean	Whether the post is archived
stickied	Boolean	Whether the post is pinned
is_video	Boolean	Whether the post contains a Reddit-hosted video
thumbnail	String	Thumbnail URL or keyword (self, default, nsfw)
total_awards_received	Integer	Total number of awards received
all_awardings	Array	Detailed list of all awards
gilded	Integer	Number of times gilded
link_flair_text	String/Null	Post flair tag text
num_crossposts	Integer	Number of crossposts
comments	Array	Full nested comment tree (see below)
success	Boolean	Whether the post was successfully scraped
error	String/Null	Error message if scraping failed, null otherwise

Conditional Post Fields

These fields appear depending on the post type:

Field	Type	When present
media	Object/Null	Video/embed posts — structure varies by media type (Reddit video, YouTube embed, etc.)
media_embed	Object	Posts with embedded media
preview	Object	Image/link posts — contains images array with source and resolutions
post_hint	String	Certain post types: image, link, hosted:video, rich:video, self
url_overridden_by_dest	String	Link posts — the destination URL
crosspost_parent_list	Array	Crossposted content — includes the original post data

Comment Fields (Default Mode)

Each comment in the comments array contains these fields, plus a replies array with the same structure (recursively for the full thread):

Field	Type	Description
id	String	The comment's unique ID
author	String	Username of the comment author
author_fullname	String	Reddit's internal fullname for the author
body	String	Comment text in Markdown
body_html	String	HTML-rendered comment body
score	Integer	Net score
ups	Integer	Number of upvotes
downs	Integer	Number of downvotes (usually 0 due to vote fuzzing)
created_utc	Number	Unix timestamp of creation
edited	Boolean/Number	false if not edited, or Unix timestamp of last edit
parent_id	String	Parent fullname (t3_postid for top-level, t1_commentid for replies)
link_id	String	Parent post fullname (t3_postid)
depth	Integer	Nesting depth (0 = top-level)
is_submitter	Boolean	Whether the commenter is the OP
permalink	String	Relative URL path to the comment
controversiality	Integer	Whether the comment is controversial (0 or 1)
distinguished	String/Null	moderator or admin if distinguished, null otherwise
stickied	Boolean	Whether the comment is pinned
collapsed	Boolean	Whether the comment is collapsed by default
author_premium	Boolean	Whether the author has Reddit Premium
subreddit	String	Subreddit name
total_awards_received	Integer	Total awards on this comment
all_awardings	Array	Detailed list of all awards
replies	Array	Nested reply comments (same structure, recursively)

Comment Fields (Lightweight Mode)

When lite_mode is enabled, each comment (including nested replies) contains only:

Field	Type	Description
id	String	The comment's unique ID
parent_id	String	Parent fullname (t3_postid for top-level, t1_commentid for replies)
author	String	Username of the comment author
body	String	Comment text in Markdown
created_utc	Number	Unix timestamp of creation
ups	Integer	Number of upvotes
replies	Array	Nested reply comments in the same lightweight structure

Output Example

{
  "title": "People 40+, what actually mattered in the long run and what didn't?",
  "author": "Psychological_Sky_58",
  "subreddit": "AskReddit",
  "score": 9965,
  "upvote_ratio": 0.95,
  "num_comments": 4987,
  "created_utc": 1771888793,
  "url": "https://www.reddit.com/r/AskReddit/comments/1rcxhjq/...",
  "selftext": "",
  "permalink": "/r/AskReddit/comments/1rcxhjq/people_40_what_actually_mattered_in_the_long_run/",
  "over_18": false,
  "is_video": false,
  "comments": [
    {
      "author": "Right-Breakfast444",
      "body": "Jesus Christ...that looks a little bit like Jason Bourne!",
      "score": 63,
      "depth": 6,
      "created_utc": 1771938473,
      "parent_id": "t1_o74gb87",
      "permalink": "/r/AskReddit/comments/1rcxhjq/.../o74ohw9/",
      "replies": [
        {
          "author": "Alarming-Research-42",
          "body": "lol.\nWe went from the Bourne Supremacy to Bourne Approximation.",
          "score": 7,
          "depth": 7,
          "replies": []
        }
      ]
    }
  ],
  "success": true,
  "error": null
}

Note: The example above shows key fields for readability. The actual output contains 80+ fields per post and per comment, as documented in the tables above.

Roadmap

Planned updates for this Actor:

• 100% comment accuracy — Not miss a single comment.
• Subreddit scraping — Input a subreddit URL to get all posts
• User profile scraping — Extract post and comment history from Reddit user profiles
• Speed improvements — Batch processing for faster runs

Integrations

JavaScript / TypeScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor("YOUR_ACTOR_ID").call({
  urls: [
    { url: "https://www.reddit.com/r/AskReddit/comments/1rcxhjq/people_40_what_actually_mattered_in_the_long_run/" }
  ],
  sort_type: "top",
  max_comments: null
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(post => {
  console.log(`${post.title} — ${post.num_comments} comments, score: ${post.score}`);
  console.log(`Comments extracted: ${post.comments.length}`);
});

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("YOUR_ACTOR_ID").call(run_input={
    "urls": [
        {"url": "https://www.reddit.com/r/AskReddit/comments/1rcxhjq/people_40_what_actually_mattered_in_the_long_run/"}
    ],
    "sort_type": "top",
    "max_comments": None
})

for post in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{post['title']} — {post['num_comments']} comments")
    for comment in post.get("comments", []):
        print(f"  [{comment['score']}] {comment['author']}: {comment['body'][:80]}...")

FAQs for Reddit Scraper

How is this different from other Reddit scrapers?

Three key differences:

1. Comment accuracy — Most scrapers miss deeply nested replies. This Actor follows the full comment tree.
2. Rich data — You get 80+ fields per post/comment (the full data Reddit stores), not just what's visible on the webpage.
3. No browser — Runs without Playwright or Puppeteer, which means lower costs and faster runs.

Does it scrape entire subreddits?

Currently, this Actor scrapes individual Reddit posts with their full comment threads. Subreddit-level scraping (listing all posts from a subreddit) is on the roadmap and coming soon.

Can it scrape user profiles?

User profile scraping is planned for a future update. Currently, the Actor extracts author information (username, flair, premium status) from within the posts and comments it scrapes.

Do I need Reddit API keys?

No. This Actor does not require any Reddit API keys, OAuth tokens, or authentication. It works out of the box.

Can I export Reddit data to CSV or Excel?

Yes. Export directly from the Apify console as JSON, CSV, Excel, or XML.

What does the sort_type parameter do?

It controls how comments are sorted before extraction, matching Reddit's own sort options:

• top — Highest scored comments first
• best — Reddit's "best" algorithm (balances score and recency)
• new — Most recent comments first
• controversial — Most debated comments first
• old — Oldest comments first
• qa — Q&A format (OP replies prioritized)

Is Reddit scraping legal?

This Actor accesses only publicly available Reddit data. Users are responsible for complying with applicable laws, Reddit's Terms of Service, and their own jurisdiction's data regulations.

Legal and Compliance

This Actor extracts only publicly available data from Reddit. Users are responsible for:

• Complying with Reddit's Terms of Service and API Terms
• Following applicable data protection laws (GDPR, CCPA, etc.)
• Using extracted data ethically and in accordance with their jurisdiction's regulations
• Not using the data to harass, dox, or target individual Reddit users

This Actor does not bypass authentication, access private subreddits, or extract data that requires a logged-in session.