Reddit Post Comments Scraper — Full Thread with Depth & Karma 🚀

foXLabs Reddit series: Search · Subreddit Posts · Post Details · User

🎉 The comments of any public Reddit post, as Reddit shows them to a signed-out visitor: every comment with its text, author, exact time, permalink, score, depth, the parent it answers and the OP/moderator marks — the Actor walks Reddit's own "more comments" loaders, so a reply from the bottom of the tree is as complete as the top comment (measured: 1,500 comments of a 3,503-comment thread, those fields 100 % filled). Each author's karma and account age on request. The post's own row comes first on request. Authors can be stable codes for name-free analyses. No login, no cookies of yours, no CAPTCHA solving.

🔍 What is the Reddit Post Comments Scraper — and when should you use it?

Give this Actor Reddit post URLs and it returns their comments as clean rows — the whole tree in the order you choose, each row with its thread depth, the parent it answers, its score and its text.

Use it when you need: the comments of a post as data — the top of the thread with its structure and scores, and the breadth of the thread for sentiment or text mining; author karma per comment on request.

Use something else when: you want the post records only → Post Details; to discover posts → Search / Subreddit Posts.

🤖 Use with AI agents

Already on the Apify MCP server? Ask for this Actor by name: foxlabs/reddit-post-comments-scraper. An agent can discover it, run it and read the dataset over MCP.

Real-time Standby API. The Reddit family ships Standby endpoints so an agent can fetch on demand; this Actor delivers full threads in batch and the family's Standby mode is prepared for live use (same events).

Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

I want a Reddit post's full comment thread using the Apify Actor
`foxlabs/reddit-post-comments-scraper`.

Input: `postUrls` is a list of post URLs/ids; `commentSort` is confidence/top/new/controversial/old/qa;
`includePost` adds the post row; `hideAuthors` returns codes; `minCommentScore`/`maxDepth` filter.
Each comment row has text, author, time, permalink, score, depth and the parent it answers.

Start with:
{ "postUrls": ["https://www.reddit.com/r/Python/comments/1x2j7z3/"], "maxCommentsPerPost": 500 }

Ask me which thread to read, run the Actor, then summarise the discussion.

The machine-readable API, MCP config and OpenAPI definition live at apify.com/foxlabs/reddit-post-comments-scraper.md.

📋 Overview

Everything you need to turn a Reddit thread into clean, structured data — the whole tree with its scores, depths and parents — in one Actor, with no login, cookies or CAPTCHA solving.

Why teams pick this Actor:

• ✅ The whole thread, every row complete — the Actor walks Reddit's own "more comments" loaders, so a comment from the bottom of the tree carries exactly what one from the top does. Measured 2026-10-17 on a 3,503-comment thread in r/AskReddit: 1,500 comments in one run, score, text, author, createdAt, depth, parentId and url 100 % filled, every id unique (depths 0–3: 736 / 446 / 218 / 100).
• 🌳 Structure preserved — depth, parentId, isSubmitter, distinguished, collapsed, removedBy.
• 👤 Author karma — link/comment karma and the cake day per comment with includeAuthorInfo (one profile-page read per author, off unless asked).
• 🕵️ Name-free mode — hideAuthors returns a stable 16-char code.
• 💰 Pay only for results — comment/post events per row; filtered-out and status rows free.
• 🤖 Agent-ready — MCP + prepared Standby.

✨ Features

• 🔍 Full thread by URL — URL, t3_ name or id.
• 💬 Every comment — text, score, controversiality, awards, exact/edit time, flags.
• 🧵 Thread order — confidence (best), top, new, controversial, old, qa.
• 📌 Post row — the post itself first with includePost.
• 🧹 Filters — minCommentScore, maxDepth; onlyNewComments for thread watching.

🎬 Quick Start

curl -X POST "https://api.apify.com/v2/acts/foxlabs~reddit-post-comments-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"postUrls": ["https://www.reddit.com/r/Python/comments/1x2j7z3/"], "maxCommentsPerPost": 500}'

🚀 Getting Started (3 steps)

1. Paste your posts — one per line: URL, t3_ name or id.
2. Pick order & cap — commentSort, maxCommentsPerPost; hideAuthors for privacy.
3. Run and export — get a clean dataset as JSON, CSV or Excel.

📥 Input

Field	Meaning
postUrls	one per line: a post URL, t3_ name or id; share links (…/s/…) not accepted.
maxCommentsPerPost	comments per post in thread order (default 500).
maxComments	comment rows in the whole run (default 100,000).
commentSort	confidence (best, default), top, new, controversial, old, qa.
includePost	the post's own row first (default on; charged as a post).
minCommentScore, maxDepth	keep only comments at/above a score or up to a depth; the rest are skipped and not charged.
includeAuthorInfo	the author's karma and cake day — one profile-page read per author (default off).
hideAuthors	replace user names with stable codes (default off).
onlyNewComments, listName	remember delivered comments and skip them next time.
proxyConfiguration	nothing to change for normal use.

{ "postUrls": ["https://www.reddit.com/r/Python/comments/1x2j7z3/"], "maxCommentsPerPost": 2000, "commentSort": "top", "includePost": true }

📤 Output

One row per comment (type: "comment"); the post as a type: "post" row first with includePost.

Field	What it is
commentId, fullname, url, postId, postTitle, subreddit	ids and address, the post it belongs to
parentId, parentIsPost, depth	tree position (0 = top-level)
author, authorFlair, authorPremium, authorDeleted	who wrote it — a stable code with hideAuthors
text, score, controversiality, awardCount	the comment and its numbers
createdAt, editedAt	exact times (UTC)
isSubmitter, distinguished, stickied, locked, collapsed, removedBy	flags
authorInfo	link/comment karma, account creation date, avatar (null for deleted)
position, input, scrapedAt, type, error	place; input line; row type / free status row

A line that brings no thread gets a free status row: not a post, no such post (deleted/never existed), a private/quarantined/Premium-only subreddit, no comments, or a post named twice.

💼 Use cases

1. Community sentiment — read an entire discussion, not just the top comments. Input: the post, commentSort: top. Output: every comment + author karma. Use: gauge reaction in depth.

2. Thread watching — collect only-new comments as a discussion grows. Input: the post, onlyNewComments + commentSort: new, scheduled. Output: new comments each run. Use: a live thread feed.

3. Research datasets — structured comment trees for analysis, name-free. Input: posts, hideAuthors on. Output: comments with depth + codes. Use: NLP/analysis within policy.

🔗 Integration

JavaScript / Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('foxlabs/reddit-post-comments-scraper').call({
  postUrls: ['https://www.reddit.com/r/Python/comments/1x2j7z3/'], maxCommentsPerPost: 500,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('foxlabs/reddit-post-comments-scraper').call(
    run_input={'postUrls': ['https://www.reddit.com/r/Python/comments/1x2j7z3/'], 'maxCommentsPerPost': 500}
)
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

Written for apify-client 3 for Python, where call() returns a run object; with version 1 or 2 it returns a dict — write run['defaultDatasetId'] there.

Automation (n8n / Zapier / Make): schedule → HTTP request to the Actor API with your postUrls → handle the JSON dataset → push to a sheet, CRM or dashboard.

📊 Pricing

Pay per event: comment per delivered comment row (the author's record rides along free), post for the post's own row with includePost. Status rows are free; filtered-out comments aren't written or charged; a run Reddit doesn't answer ends FAILED and charges nothing; no start fee. View current pricing.

❓ FAQ

Do I need a Reddit account, login or API key? No — a signed-out guest token, no account, no cookies, no CAPTCHA solving.

Does it get the whole thread? Yes — it resolves "more comments" stubs (100 ids a request) up to maxCommentsPerPost or the end. Deleted/removed/collapsed comments in Reddit's count aren't delivered; the run's last word says how many weren't reached.

Can I hide commenter names? Yes — hideAuthors returns a stable 16-char code.

Can I export to CSV / Excel / JSON? Yes — directly from the Apify dataset.

Are share links accepted? No (…/s/…) — use the full post URL, t3_ name or id.

🐛 Troubleshooting

• Fewer comments than the post's count — the count includes deleted/removed/collapsed comments; the run says how many weren't reached.
• A line returns a status row — not a post, no such post, private/Premium-only subreddit, no comments, or named twice (free).
• Big threads are slow — read stub by stub (100 a request); set maxCommentsPerPost to what you need.

How it reads Reddit: opens a listing as a signed-out visitor, takes the guest token, and calls Reddit's JSON API — the thread in one answer (up to 500, 10 levels), then "more comments" stubs packed 100 ids a request. Residential-only token (measured 7/7 residential, 0/8 datacenter) → Apify Proxy residential by default; four addresses rotate.

⚠️ Trademark

Independent, third-party tool. Reddit is a trademark of Reddit, Inc.; this Actor is not affiliated with, endorsed by or connected to Reddit. The mark is used here for identification only.

⚖️ Is it legal to scrape this data?

It reads only what Reddit shows anyone who is not signed in. Comment rows carry user names (public pseudonyms) and publicly posted text; hideAuthors replaces names with codes. You are responsible for using the data lawfully (GDPR, CCPA, Reddit's User Agreement). Nothing is stored outside your own Apify datasets. See Apify's blog post on the legality of web scraping.

🤝 Support & contact

• 🌐 Website: data.foxlabs.com.tr
• 📧 Email: info@foxlabs.com.tr
• 🐛 Issues: open a ticket in the Actor's Issues tab — the run's SOURCE_REPORT record holds what was seen, read, delivered and why the run stopped.
• 🧰 More clean data actors: Fox Labs on Apify

Changelog

0.3.0 — 2026-10-17

The full comment tree is back. Reddit's own web client loads the rest of a thread through hidden "more comments" loaders, and each one is a POST carrying its own cursor: asked that way they answer with 4–100 further comments, every one of them complete (score, depth, parent, body), plus the loaders of the level below. Build 0.2 asked them as GETs — which answer "page not found" — and fell back to the thread's feed, whose rows have no score, depth or parent. Measured 2026-10-17: 1,500 comments of a 3,503-comment thread, all of those fields 100 % filled, 267 requests, 2 MB on the wire. commentSort now really sets the thread's order (the page honours it and the loaders carry it on), and maxDepth stops the walk instead of filtering afterwards, so the budget buys comments you keep. A thread with more to give says so in the run's last word instead of calling the rest "deleted". editedAt, controversiality, collapsed, locked, stickied, authorFlair and authorPremium remain null (Reddit's HTML does not carry them). Field names, the dataset shape and the prices are unchanged.

0.2.0 — 2026-10-17

Reddit closed its JSON API to signed-out visitors on 16 October 2026, so a thread came from its page (the post and its first 25 comments, complete with score, depth and parent) plus the thread's own feed, whose rows said null for score, depth and parentId. Superseded by 0.3.0.

0.1.0 — 2026-10-10

• First release: full comment trees with depth, parent, flags, removed/deleted state and author karma; "more comments" stubs packed 100 ids a request; the post's own row; score and depth filters; author codes; only-new lists; free status rows; Standby API prepared.