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Reddit Scraper

Reddit data actor for posts, comments, users, and subreddits.

Use this actor to collect Reddit data in clean JSON format through Apify datasets.

Pricing

• Pricing: $1.25 / 1,000 results

What It Can Do

• Search Reddit posts by query
• Search subreddits by query
• Fetch posts from a subreddit
• Fetch subreddit metadata
• Fetch comments for a post
• Fetch user profile data
• Fetch posts by a user
• Fetch comments by a user
• Fetch popular posts

Why Use This Actor

• Faster than browser-based Reddit actors
• Clean dataset output for apps, agents, and workflows
• No Reddit login required
• Good fit for Python scripts, Make, n8n, and Apify workflows
• Cheaper launch pricing than many comparable Reddit actors

Input

The actor requires an action plus action-specific fields.

Supported Actions

Example Input

{
"action":"search_posts",
"query":"python web framework",
"subreddit":"python",
"sort":"top",
"time":"month"
}

Input Examples and Usage

The examples below use a small Python wrapper so each actor action can be called with explicit parameters and sensible defaults.

from apify_client import ApifyClient
APIFY_TOKEN ="YOUR_APIFY_TOKEN"
ACTOR_ID ="good-apis/reddit-scraper"
classRedditScraperActor:
def__init__(self, token:str, actor_id:str= ACTOR_ID)->None:
 self.client = ApifyClient(token)
 self.actor_id = actor_id
def_run(self,**run_input):
 run = self.client.actor(self.actor_id).call(run_input=run_input)
returnlist(self.client.dataset(run["defaultDatasetId"]).iterate_items())
defsearch_posts(
 self,
 query:str,
 subreddit:str|None=None,
 sort:str|None=None,
 time:str|None=None,
 cursor:str|None=None,
):
return self._run(
 action="search_posts",
 query=query,
 subreddit=subreddit,
 sort=sort,
 time=time,
 cursor=cursor,
)
defsearch_subreddits(self, query:str, cursor:str|None=None):
return self._run(action="search_subreddits", query=query, cursor=cursor)
defsubreddit_posts(
 self,
 subreddit:str,
 sort:str|None=None,
 time:str|None=None,
 cursor:str|None=None,
):
return self._run(
 action="subreddit_posts",
 subreddit=subreddit,
 sort=sort,
 time=time,
 cursor=cursor,
)
defsubreddit_about(self, subreddit:str):
return self._run(action="subreddit_about", subreddit=subreddit)
defpost_comments(
 self,
 post_id:str,
 subreddit:str,
 sort:str|None=None,
):
return self._run(
 action="post_comments",
 post_id=post_id,
 subreddit=subreddit,
 sort=sort,
)
defuser_about(self, username:str):
return self._run(action="user_about", username=username)
defuser_posts(
 self,
 username:str,
 sort:str|None=None,
 cursor:str|None=None,
):
return self._run(action="user_posts", username=username, sort=sort, cursor=cursor)
defuser_comments(
 self,
 username:str,
 sort:str|None=None,
 cursor:str|None=None,
):
return self._run(action="user_comments", username=username, sort=sort, cursor=cursor)
defpopular_posts(self, sort:str|None=None, cursor:str|None=None):
return self._run(action="popular_posts", sort=sort, cursor=cursor)
reddit = RedditScraperActor(APIFY_TOKEN)

search_posts

items = reddit.search_posts(
 query="python web framework",
 subreddit="python",
 sort="top",
 time="month",
 cursor=None,
)
print(items)

search_subreddits

items = reddit.search_subreddits(
 query="machine learning",
 cursor=None,
)
print(items)

subreddit_posts

items = reddit.subreddit_posts(
 subreddit="python",
 sort="hot",
 time="day",
 cursor=None,
)
print(items)

subreddit_about

items = reddit.subreddit_about(subreddit="python")
print(items)

post_comments

items = reddit.post_comments(
 post_id="1r82a0a",
 subreddit="python",
 sort="top",
)
print(items)

user_about

items = reddit.user_about(username="spez")
print(items)

user_posts

items = reddit.user_posts(
 username="spez",
 sort="new",
 cursor=None,
)
print(items)

user_comments

items = reddit.user_comments(
 username="spez",
 sort="top",
 cursor=None,
)
print(items)

popular_posts

items = reddit.popular_posts(
 sort="hot",
 cursor=None,
)
print(items)

Output

Results are written to the default Apify dataset.

• list responses are pushed as one dataset item per result
• object responses are pushed as a single dataset item
• failed runs push an error object before failing

List results include:

• _action: the executed action
• _cursor: the next-page cursor when available

Client Examples

Python

See ./examples/python_client.py for the same helper wrapper in a runnable file.

Node.js

import{ ApifyClient }from'apify-client';
const client =newApifyClient({token: process.env.APIFY_TOKEN});
const run =await client.actor('good-apis/reddit-scraper').call({
action:'search_posts',
query:'python web framework',
subreddit:'python',
sort:'top',
time:'month',
});
const{ items }=await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Agent-Friendly Notes

This actor is designed to be easy for agents to call reliably.

• Inputs are flat and structured
• actions are explicit and predictable
• pagination state is returned as _cursor
• errors fail the run explicitly instead of silently returning partial success
• dataset output is machine-readable JSON without browser rendering artifacts

For agent use, prefer:

• subreddit_about for metadata lookup
• search_posts for query-driven discovery
• post_comments for thread extraction
• _cursor chaining for pagination