Reddit Scraper API endpoints

This guide shows you how to send a synchronous request to each Bright Data Reddit Scraper API endpoint. It covers collecting posts, discovering posts and collecting comments.

Prerequisites

A Bright Data account with an active API key
Completed the Quickstart

Request structure

Every synchronous request follows the same pattern:

POST https://api.brightdata.com/datasets/v3/scrape?dataset_id={DATASET_ID}&format=json
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

[{"url": "https://www.reddit.com/..."}]

The only things that change between endpoints are the dataset_id and the input shape.

The /scrape endpoint is built for real-time, single-URL requests. Bright Data recommends 20 URLs or fewer per request, a best practice rather than a hard limit, and the endpoint waits up to 1 minute. If collection takes longer, the response is HTTP 202 with a snapshot_id instead of data, and collection continues asynchronously. Fetch the result with async requests or have it pushed to you with webhook delivery.

Posts, Collect by URL

Scrape a specific Reddit post by its URL. Dataset ID: gd_lvz8ah06191smkebj4

curl -X POST \
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvz8ah06191smkebj4&format=json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[{"url": "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/"}]'

import requests

response = requests.post(
    "https://api.brightdata.com/datasets/v3/scrape",
    params={"dataset_id": "gd_lvz8ah06191smkebj4", "format": "json"},
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json=[{"url": "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/"}],
)

print(response.json())

const response = await fetch(
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvz8ah06191smkebj4&format=json",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer YOUR_API_KEY",
      "Content-Type": "application/json",
    },
    body: JSON.stringify([
      { url: "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/" }
    ]),
  }
);

const data = await response.json();
console.log(data);

You should see a 200 response. Processing time varies with target-site conditions and scraper workload.

Example response

[
  {
    "post_id": "t3_1w8chn8",
    "url": "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/",
    "user_posted": "xq_***x",
    "title": "found a for loop and can't find an explanation. Can someone explain, please?",
    "description": "Hey there, I just started the Project Euler Archive and started with the classic \"Find the sum of all the multiples of 3 or 5 below 1000.\" And when I wanted...",
    "num_upvotes": 8,
    "num_comments": 14,
    "date_posted": "2026-09-05T21:03:33.625Z",
    "tag": null,
    "community_name": "learnpython"
  }
]

Full Posts - Collect by URL schema

Which output fields does the Reddit posts scraper return?

The Reddit posts scraper (gd_lvz8ah06191smkebj4, collect_by_url) returns 27 output fields.

Output fields (27)

Field	Type	Description
`post_id`	text	Post ID
`url`	url	URL of the post
`user_posted`	text	Username of the post creator
`title`	text	Title of the post
`description`	text	Post text description
`num_comments`	number	Number of comments
`date_posted`	date	Post publication date
`community_name`	text	Name of the community
`num_upvotes`	number	Number of upvotes
`photos`	array	URLs of attached photos
`videos`	array	URLs of attached videos
`tag`	text	The name of the tag
`related_posts`	array	Related posts
`comments`	array	Comments of the post
`community_url`	url	URL of the community
`community_description`	text	Description of the community
`community_members_num`	number	Number of community members
`community_rank`	object	Community ranked
`post_karma`	number	post_karma
`bio_description`	text	bio_description
`embedded_links`	array	embedded_links
`description_markdown`	text	Post content with original line breaks and Markdown formatting
`subreddit_icon_image`	url	Subreddit icon image
`author_icon`	url	Author icon link
`user_id`	text	posting user unique id
`archived`	text	archived
`locked_post`	boolean	Indicator if the post is locked and new comments cannot be posted.

Machine-readable version with the input schema: /scrapers/gd_lvz8ah06191smkebj4.json

Posts, Discover by subreddit URL

Scrape recent posts from a specific subreddit, optionally sorted with sort_by. Values are case-sensitive and match the labels on Reddit, for example Hot. Lowercase hot is rejected with a validation error. Dataset ID: gd_lvz8ah06191smkebj4

Discovery endpoints are best used asynchronously via /trigger since they may return many results. The sync example below is for quick testing.

# limit_per_input caps the records returned for each input
curl -X POST \
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvz8ah06191smkebj4&format=json&type=discover_new&discover_by=subreddit_url" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"input": [{"url": "https://www.reddit.com/r/learnpython/", "sort_by": "Hot"}], "limit_per_input": 10}'

import requests

response = requests.post(
    "https://api.brightdata.com/datasets/v3/scrape",
    params={
        "dataset_id": "gd_lvz8ah06191smkebj4",
        "format": "json",
        "type": "discover_new",
        "discover_by": "subreddit_url",
    },
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    # limit_per_input caps the records returned for each input
    json={
        "input": [{"url": "https://www.reddit.com/r/learnpython/", "sort_by": "Hot"}],
        "limit_per_input": 10,
    },
)

print(response.json())

const response = await fetch(
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvz8ah06191smkebj4&format=json&type=discover_new&discover_by=subreddit_url",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer YOUR_API_KEY",
      "Content-Type": "application/json",
    },
    // limit_per_input caps the records returned for each input
    body: JSON.stringify({
      input: [{ url: "https://www.reddit.com/r/learnpython/", sort_by: "Hot" }],
      limit_per_input: 10,
    }),
  }
);

const data = await response.json();
console.log(data);

Full Discover by subreddit URL schema

Posts, Discover by keyword

Find Reddit posts matching a search term, filtered by date. Dataset ID: gd_lvz8ah06191smkebj4

# limit_per_input caps the records returned for each input
curl -X POST \
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvz8ah06191smkebj4&format=json&type=discover_new&discover_by=keyword" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"input": [{"keyword": "machine learning", "date": "Past week", "num_of_posts": 20}], "limit_per_input": 10}'

import requests

response = requests.post(
    "https://api.brightdata.com/datasets/v3/scrape",
    params={
        "dataset_id": "gd_lvz8ah06191smkebj4",
        "format": "json",
        "type": "discover_new",
        "discover_by": "keyword",
    },
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    # limit_per_input caps the records returned for each input
    json={
        "input": [{"keyword": "machine learning", "date": "Past week", "num_of_posts": 20}],
        "limit_per_input": 10,
    },
)

print(response.json())

const response = await fetch(
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvz8ah06191smkebj4&format=json&type=discover_new&discover_by=keyword",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer YOUR_API_KEY",
      "Content-Type": "application/json",
    },
    // limit_per_input caps the records returned for each input
    body: JSON.stringify({
      input: [{ keyword: "machine learning", date: "Past week", num_of_posts: 20 }],
      limit_per_input: 10,
    }),
  }
);

const data = await response.json();
console.log(data);

Full Discover by keyword schema

Comments, Collect by URL

Scrape all comments from a Reddit post or a specific comment thread, with optional filtering by age. Dataset ID: gd_lvzdpsdlw09j6t702

curl -X POST \
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvzdpsdlw09j6t702&format=json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[{"url": "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/", "days_back": 7}]'

import requests

response = requests.post(
    "https://api.brightdata.com/datasets/v3/scrape",
    params={"dataset_id": "gd_lvzdpsdlw09j6t702", "format": "json"},
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json=[{"url": "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/", "days_back": 7}],
)

print(response.json())

const response = await fetch(
  "https://api.brightdata.com/datasets/v3/scrape?dataset_id=gd_lvzdpsdlw09j6t702&format=json",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer YOUR_API_KEY",
      "Content-Type": "application/json",
    },
    body: JSON.stringify([
      { url: "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/", days_back: 7 }
    ]),
  }
);

const data = await response.json();
console.log(data);

Example response

[
  {
    "comment_id": "p841ojc",
    "user_posted": "rec***e",
    "comment": "[List\\_comprehension](https://en.wikipedia.org/wiki/List_comprehension) have an interesting history. It use in functional programming language which python a...",
    "date_posted": "2026-09-06T05:58:16.000Z",
    "num_upvotes": 1,
    "num_replies": 0,
    "replies": null,
    "post_url": "https://www.reddit.com/r/learnpython/comments/1w8chn8/found_a_for_loop_and_cant_find_an_explanation_can/",
    "post_id": "1w8chn8",
    "post_type": null
  }
]

Full Comments - Collect by URL schema

Which output fields does the Reddit comments scraper return?

The Reddit comments scraper (gd_lvzdpsdlw09j6t702, collect_by_url) returns 34 output fields.

Output fields (34)

Field	Type	Description
`url`	url	URL of comment
`comment_id`	text	ID of comment
`user_posted`	text	Username of the user who posted the comment
`comment`	text	Description of the comment
`date_posted`	date	Date posted
`post_url`	url	URL of the post this comment appears at
`post_id`	text	ID of the post this comment appears at
`community_name`	text	The name of the community the comment was posted at
`community_url`	text	URL of the community where the comment was posted at
`community_description`	text	Description of the community this comment was posted at
`community_members_num`	text	Number of community members where the comment was posted at
`community_rank`	object
`replies`	array
`num_upvotes`	number	Number of comment’s upvotes
`num_replies`	number	Number of replies to the comment
`days_back`	number	Reproduce from Input
`is_moderator`	boolean	A post has a “MOD” icon - this means it was posted by a moderator or bot in some cases
`is_pinned`	boolean	pinned or stickied comment, placed on top of all
`has_bot_in_username`	boolean	The username has a substring “bot” - This parameter can be an indirect sign of a bot In most cases, but can also occur in common usernames
`is_locked`	boolean	The post has a “lock” icon - this means that comments are blocked by moderators and no one but them can comment on them. This parameter can be an indirect sign of a bot
`is_admin_post`	boolean	hidden is labeled as “distinguished admin”
`is_archived_post`	boolean	Indicates whether the post is archived or not
`is_moderator_post`	boolean	Specifies if the post is made by a moderator
`is_quarantined_post`	boolean	Indicates if the post is quarantined
`is_not_safe_for_work_post`	boolean	Flags whether the post contains content not safe for work
`is_eligible_for_content_blocking_post`	boolean	Specifies if the post is eligible for content blocking
`is_promoted_post`	boolean	Indicates if the post is promoted content
`post_language`	text	Language in which the post is written
`post_state`	text	Current state/status of the post
`post_type`	text	Type or category of the post
`images`	array	Images from the comment
`parent_comment_id`	text
`root_comment_id`	text	Links all replies to the original root comment
`videos`	array	Video and GIF URLs

Machine-readable version with the input schema: /scrapers/gd_lvzdpsdlw09j6t702.json

Async batch requests

Scrape thousands of posts or run keyword discovery jobs in a single async request.

API reference

Full endpoint specs, parameters and response schemas.

Get started

Data extraction

Web search

AI training data

Proxy networks

Prerequisites

Request structure

Posts, Collect by URL

Which output fields does the Reddit posts scraper return?

Posts, Discover by subreddit URL

Posts, Discover by keyword

Comments, Collect by URL

Which output fields does the Reddit comments scraper return?

Async batch requests

API reference

​Prerequisites

​Request structure

​Posts, Collect by URL

​Which output fields does the Reddit posts scraper return?

​Posts, Discover by subreddit URL

​Posts, Discover by keyword

​Comments, Collect by URL

​Which output fields does the Reddit comments scraper return?

​Related

Async batch requests

API reference

Prerequisites

Request structure

Posts, Collect by URL

Which output fields does the Reddit posts scraper return?

Posts, Discover by subreddit URL

Posts, Discover by keyword

Comments, Collect by URL

Which output fields does the Reddit comments scraper return?

Related