Reddit Comments

Search Reddit comments by keyword. Returns comment content, parent post URL, subreddit, author, and publication date. Supports fetching multiple pages in a single API call.

Endpoint

GET /v1/reddit/comments

Price: $0.003 per page Free tier: 50 requests/month

Parameters

Parameter	Required	Description
`query`	Yes	Search keyword (max 500 characters)
`pages`	No	Number of pages to fetch, 1-5 (default: 1)
`sort_by`	No	Sort order: `most_recent`, `relevance`, or `top` (default: `most_recent`)
`get_sentiment`	No	Set to `true` to add AI emotion analysis (Plutchik’s Wheel) to each result. Adds +$0.001 per page to the cost. Returns emotion scores, dominant emotion, intensity, and polarity.

Response Fields

Field	Type	Description
`posts`	array	Array of matching comments
`posts[].title`	string	Comment title (format: `username on subreddit`)
`posts[].url`	string	Link to the parent post
`posts[].date`	string	Publication date and time
`posts[].author`	string	Reddit username
`posts[].source`	string	`"Reddit (Comment)"`
`posts[].domain`	string	`"reddit.com"`
`posts[].subreddit`	string	Subreddit name
`posts[].snippet`	string	Comment content text
`posts[].type`	string	`"comment"`
`posts[].upvotes`	integer/null	Net upvotes on the comment. `null` if the score is hidden by the subreddit or unavailable from the fallback source.
`posts[].post_upvotes`	integer/null	Net upvotes on the parent post. `null` if unavailable from the fallback source.
`posts[].post_comments`	integer/null	Total comments on the parent post. `null` if unavailable from the fallback source.
`posts[].sentiment`	object/null	Emotion analysis results. Only present when `get_sentiment=true`. Returns `null` if analysis fails.
`posts[].sentiment.emotions`	object	Plutchik emotion scores (0-100) for: `joy`, `trust`, `fear`, `surprise`, `sadness`, `disgust`, `anger`, `anticipation`.
`posts[].sentiment.dominant_emotion`	string	The emotion with the highest score.
`posts[].sentiment.emotional_intensity`	integer	Overall emotional intensity on a scale of 0-10.
`posts[].sentiment.polarity`	string	Overall sentiment polarity: `positive`, `negative`, or `neutral`.
`pages`	integer	Number of pages fetched
`count`	integer	Total results returned

Example Request

cURL

curl "https://apidirect.io/v1/reddit/comments?query=python&pages=2&sort_by=relevance" \
  -H "X-API-Key: YOUR_API_KEY"

Python

import requests

response = requests.get(
    "https://apidirect.io/v1/reddit/comments",
    headers={"X-API-Key": "YOUR_API_KEY"},
    params={
        "query": "python",
        "pages": 2,
        "sort_by": "relevance"
    }
)
print(response.json())

Example Response

{
  "posts": [
    {
      "title": "commenter on python",
      "url": "https://reddit.com/r/python/comments/...",
      "date": "2024-01-15 14:30:00",
      "author": "commenter",
      "source": "Reddit (Comment)",
      "domain": "reddit.com",
      "subreddit": "python",
      "snippet": "Comment content...",
      "type": "comment",
      "upvotes": 42,
      "post_upvotes": 1850,
      "post_comments": 274,
      "sentiment": {
        "emotions": {
          "joy": 40,
          "trust": 55,
          "fear": 0,
          "surprise": 10,
          "sadness": 0,
          "disgust": 0,
          "anger": 0,
          "anticipation": 30
        },
        "dominant_emotion": "trust",
        "emotional_intensity": 5,
        "polarity": "positive"
      }
    }
  ],
  "pages": 2,
  "count": 50
}