Reddit Post
Fetch full details for a single Reddit post — title, body text, url, subreddit, author, score, upvote ratio, comment count, timestamp, NSFW/video flags, thumbnail, and media — as JSON. Pass a post id or a post URL. Costs 1 credit per request.
POST/api/v1/reddit/post
Authorizations
AuthorizationstringheaderrequiredBearer authentication header of the form Bearer <token>, where <token> is your Scavio API key (e.g. Bearer sk_live_your_key).
Body
application/jsonpost_idstringPost fullname (t3_...) or bare id. Provide this or url.
Example: t3_1v6ngaf
urlstringFull Reddit post URL. Provide this or post_id.
Example: https://www.reddit.com/r/MachineLearning/comments/1v6ngaf/example/
Request
from scavio import ScavioClient
client = ScavioClient(api_key="sk_live_your_key")
results = client.reddit.post(url="https://www.reddit.com/r/MachineLearning/comments/1v6ngaf/example/")
print(results)Response
"post_id": "t3_1v6ngaf",
"title": "What vector database are you using in production?",
"text": "We started on pgvector and are now evaluating Qdrant and Weaviate for a RAG pipeline. Curious what everyone is running at scale.",
"url": "https://redd.it/1v6ngaf",
"subreddit": "MachineLearning",
"author": "embeddings_guy",
"score": 428,
"upvote_ratio": 0.96,
"num_comments": 174,
"created_at": "2026-07-19T11:02:44.000Z",
"is_nsfw": false,
"is_video": false,
"thumbnail": "https://b.thumbs.redditmedia.com/abc123.jpg",
"media": []
},
"response_time": 934,
"credits_used": 1,
"credits_remaining": 4751
}