How to search Reddit posts by keyword and collect their comments

The job: Reddit is where people ask "which one should I buy" and get long, honest answers. You want those answers for a product or topic as data. Search for the posts, keep the threads with the most discussion, and read their comments with the reply structure intact. You end with one CSV: each row a comment with its post, community, text, score, author and, for replies, the comment it answers.

No Reddit account, app registration or OAuth token is involved. Each call is an HTTPS request with your key.

Step by step

Step 1: search posts

Call Reddit post search with query. Two parameters decide what comes back:

• sort: relevance (the default), latest (newest first) or popular (highest score first).
• published_within: day, week, month or year. Leave it out to search all time.

One call returns about 25 posts for $0.004. Each post has id (in Reddit's t3_ form, such as t3_1p4kx9q), url, type (text, image or video), title, the body in text (empty for link and image posts), published_at, author.username, the score in metrics.likes and the comment count in metrics.comments. Add view=full for ext.subreddit (the community, as r/name), ext.upvote_ratio, ext.link (the outside link of a link post), ext.flair and ext.nsfw.

curl -G "https://api.okdata.online/v1/reddit/posts/search" \
  -H "Authorization: Bearer $OKDATA_API_KEY" \
  --data-urlencode 'query=air fryer' \
  -d sort=popular -d published_within=month -d view=full

For the next page, send page.next_cursor back as cursor, unchanged; stop when page.has_more is false.

Step 2: read the comments

Pass a post's id (with or without t3_) or its link as url to Reddit post comments. sort takes best (the default, Reddit's own order), latest or popular (highest score first).

One call returns about 10 comments for $0.002, together with the first levels of replies under them. Each comment has id (t1_ form), post_id, parent_id, text, author.username, the score in likes, the reply count in replies and published_at. parent_id is null for a top-level comment and holds the t1_ ID of the comment being answered for a reply, so you can rebuild the thread as a tree.

curl -G "https://api.okdata.online/v1/reddit/posts/comments/list" \
  -H "Authorization: Bearer $OKDATA_API_KEY" \
  -d id=t3_1p4kx9q -d sort=popular

Page with page.next_cursor as in step 1. Each further page brings more top-level comments with their first replies.

Step 3: put it together in Python

import csv
import os
import requests

API = "https://api.okdata.online"
HEADERS = {"Authorization": f"Bearer {os.environ['OKDATA_API_KEY']}"}
SEARCH_PAGES = 2
THREADS = 6  # first comment page of each; one call per thread


def get(path, **params):
    body = requests.get(API + path, headers=HEADERS, params=params, timeout=60).json()
    if body["code"] != "ok":
        raise RuntimeError(f"{body['code']}: {body['message']} (charged: {body['charged']})")
    return body


posts, cursor = [], None
for _ in range(SEARCH_PAGES):
    body = get("/v1/reddit/posts/search", query="air fryer", sort="popular", published_within="month", view="full", **({"cursor": cursor} if cursor else {}))
    posts += body["data"]["items"]
    if not body["page"]["has_more"]:
        break
    cursor = body["page"]["next_cursor"]

busiest = sorted(posts, key=lambda p: p["metrics"]["comments"] or 0, reverse=True)[:THREADS]
with open("reddit_comments.csv", "w", newline="", encoding="utf-8") as f:
    out = csv.writer(f)
    out.writerow(["community", "post_id", "post_title", "comment_id", "parent_id", "author", "score", "replies", "published_at", "text"])
    for p in busiest:
        for c in get("/v1/reddit/posts/comments/list", id=p["id"], sort="popular")["data"]["items"]:
            out.writerow([p["ext"]["subreddit"], p["id"], p["title"], c["id"], c["parent_id"], c["author"]["username"], c["likes"], c["replies"], c["published_at"], c["text"]])

Rows with an empty parent_id are top-level comments; the rest are replies. To read deeper threads, page the comments of the posts that matter most.

Good to know

• Score, not likes. Reddit shows a score (upvotes minus downvotes), and that is what metrics.likes and a comment's likes hold. Scores near zero can mean a disputed comment, not an ignored one.
• What is null. Reddit shows no view counts, so metrics.views is null. Commenters' avatars, follower counts and locations are not returned; replies can be null when the count is not known.
• Deleted content. A removed post returns not_found, which costs nothing. Deleted comments can still appear in a thread with their text replaced by Reddit's placeholder; filter them out before analysis.
• Search reach. The results are what Reddit's own search returns for the query and period, not every post that mentions the words. Try a few phrasings for a full picture.
• The official route. Reddit has its own Data API. Its Data API Terms say that commercial use, or research beyond its rate limits, needs a separate agreement with Reddit. For a personal or approved research project within those limits, it is a good option.
• Retries without paying twice. Send an Idempotency-Key header with each call; the same request with the same key within 24 hours returns the stored answer and no new charge.

For what comments cost across platforms, see social media comments cost per 1,000. Turning threads like these into findings is covered in word of mouth.

{
  "endpoint": "reddit.posts.search",
  "params": {
    "query": "saturn rings"
  },
  "idempotency_key": "<a new UUID>"
}