Monitor Reddit for mentions of your product in Python

A developer built Qovia, a paid API that wraps Reddit search, and published a Python tutorial showing how to poll it hourly from cron to find brand mentions, de-duplicate results via a state file, log them to CSV and alert on Slack. The script uses Reddit's search syntax with time_range and sort parameters, pages results about seven at a time via cursor, and retries once on HTTP 429 using the Retry-After header; empty results and errors are not billed.

I build Qovia, the API used in this post. The monitoring logic search, de-duplicate, filter, alert works with any Reddit data source; the state file, CSV and Slack parts are plain Python. If you ship a developer tool or a SaaS product, Reddit is where people ask "is there an alternative to X?", complain about your onboarding, or recommend you to someone else, often without tagging you. Finding those threads early is worth a lot: a helpful answer in the first hour of a thread does more than a week of ads. Doing it by hand means refreshing Reddit search every morning, so let's automate it. In this tutorial we'll write a script that: Run it from cron every hour and you have a basic social-listening tool for a few dollars a month. You need Python 3.9+ and requests : pip install requests export QOVIA KEY=sk-qovia-... key from the Qovia console export SLACK WEBHOOK URL=https://hooks.slack.com/services/... optional Get a key from Qovia https://qovia.ai/?utm source=devto&utm medium=article&utm campaign=reddit-keyword-monitor-python . Requests authenticate with Authorization: Bearer <key an x-api-key header also works . The Reddit search reference https://qovia.ai/docs/api-reference/raw.reddit.search/?utm source=devto&utm medium=article&utm campaign=reddit-keyword-monitor-python shows every parameter with a real response; the other Reddit endpoints are listed next to it. You don't need a Reddit account, OAuth app or client secret for this. The trade-off is that it's read-only and public content only more under Limits . Every response has the same envelope: the result is in data , and meta reports the charge meta.billed , meta.charged usd , meta.empty . Empty results come back as HTTP 200 with meta.empty: true and are not charged. Errors are {"error": {"code", "message", ...}} and are never charged. A post or subreddit that doesn't exist answers 404 , so the helper turns that into None . A 429 carries a Retry-After header, so the helper waits and retries once: python import os import time import requests BASE = "https://api.qovia.ai" HEADERS = {"Authorization": f"Bearer {os.environ 'QOVIA KEY' }"} spent = 0.0 def get path, params : global spent params = {k: v for k, v in params.items if v is not None} for attempt in range 2 : r = requests.get f"{BASE}{path}", headers=HEADERS, params=params, timeout=60 if r.status code == 429 and attempt == 0: time.sleep int r.headers.get "Retry-After", "10" continue if r.status code == 404: return None missing post or subreddit, not charged r.raise for status body = r.json spent += float body.get "meta" or {} .get "charged usd" or 0 return body.get "data" or {} Unknown parameters are rejected with 400 invalid params , which is why the helper drops None values instead of sending them. GET /v1/raw/reddit/search takes a keyword 1 to 200 characters and Reddit's search syntax works inside it: AND , OR , NOT , quoted phrases, subreddit: , author: , title: and so on. Two more parameters matter for monitoring: sort : relevance the default , hot , top , new or comments . For monitoring you want time range : all the default , year , month , week , day or hour . If you run hourly, Results come about 7 a page. Pass cursor back for the next page and stop when has more is false. If Reddit spell-corrected your query, corrected query tells you what it actually searched, which is worth logging: brand names get "corrected" more often than you'd think. Each post record has text title and body , author username , metrics likes , which is the post's score, and comments and extra with source id the post's fullname, t3 ... , title , subreddit , published at UTC , flair , content type , link url and url . QUERIES = { "brand": '"acme analytics" OR acmeanalytics', "competitor": '"plausible analytics" alternative', } def search query, time range="day", max pages=2 : posts, cursor = , None for in range max pages : page = get "/v1/raw/reddit/search", keyword=query, sort="new", time range=time range, cursor=cursor if not page: break if page.get "corrected query" : print f" note: Reddit searched {page 'corrected query' r} instead of {query r}" posts.extend page.get "items", if not page.get "has more" : break cursor = page.get "cursor" return posts Quote multi-word names. Without quotes, acme analytics matches any post containing both words anywhere, which for a common word gets noisy fast. Search finds posts that name you. The more valuable posts often don't: "what do you use for privacy-friendly analytics?" in r/webdev never mentions any product. For those, watch the newest posts in the communities your users hang out in and filter locally. GET /v1/raw/reddit/subreddit posts takes a subreddit the name after r/ and a sort hot by default; also best , new , top , controversial , rising . It's cursor-paginated: about 6 posts on the first page, then about 24. The list records carry the title and the first 300 characters of the body extra.truncated tells you when it was cut , which is plenty for a phrase filter. Fields the list doesn't carry language, author ID, images, upvote ratio are null; GET /v1/raw/reddit/post has them if you need them. python import re SUBREDDITS = "webdev", "SaaS", "selfhosted" TOPIC = re.compile r"analytics|tracking|pageviews", re.I INTENT = re.compile r"alternative to|looking for|recommend|what do you use|switch ed|ing ? from", re.I def intent posts subreddit, max pages=2 : hits, cursor = , None for in range max pages : page = get "/v1/raw/reddit/subreddit posts", subreddit=subreddit, sort="new", cursor=cursor if not page: break 404: no such subreddit for p in page.get "items", : text = p.get "text" or "" if TOPIC.search text and INTENT.search text : hits.append p if not page.get "has more" : break cursor = page.get "cursor" return hits The two regexes are deliberately simple: a post must be about the topic and sound like someone is choosing a tool. Tune them on a week of output; this is the part of the script you'll edit most. Both sources return the same record shape with the same IDs, so one set of seen fullnames is enough. A JSON file next to the script is fine for an hourly job: python import json from pathlib import Path STATE = Path "reddit seen.json" def load seen : return set json.loads STATE.read text if STATE.exists else set def save seen seen : STATE.write text json.dumps sorted seen def only new posts, seen : fresh = for p in posts: pid = p "extra" "source id" if pid not in seen: seen.add pid fresh.append p return fresh This also de-duplicates a post that shows up in both a search and a subreddit feed during the same run. A title tells you a thread exists; the comments tell you whether it's worth answering. GET /v1/raw/reddit/comments takes the post's post id the same t3 ... fullname and an optional sort best by default, or top , new , old , controversial . A page holds 8 comments: a few top-level ones plus the replies Reddit expands under them, flattened in Reddit's order. Each has cid , text , likes the comment's score , reply count , created at UTC , pinned , author , depth 0 for top-level and parent cid . The page also has total , cursor and has more . A post without comments answers empty and isn't charged. python def top comments post id, keywords=None : page = get "/v1/raw/reddit/comments", post id=post id, sort="top" or {} out = for c in page.get "items", : text = c.get "text" or "" .replace "\n", " " out.append { "cid": c "cid" , "depth": c.get "depth" , "score": c.get "likes" , "replies": c.get "reply count" , "mentions": bool keywords and keywords.search text , "text": text :300 , } return out, page.get "total" One page per post keeps the cost predictable. If you need a full thread, keep paging with cursor ; replies Reddit collapses come with a replies cursor that GET /v1/raw/reddit/comment replies expands it takes post id and that cursor . For alerts, the top 8 is enough to see whether people are already recommending someone. python import csv from datetime import datetime, timezone FIELDS = "checked at", "source", "post id", "subreddit", "title", "author", "score", "comments", "published at", "url", "top comment" MENTION = re.compile r"acme", re.I flags comments that name you def now : return datetime.now timezone.utc .isoformat timespec="seconds" def row source, p, comments : ex, m = p.get "extra" or {}, p.get "metrics" or {} best = comments 0 "text" if comments else "" return { "checked at": now , "source": source, "post id": ex.get "source id" , "subreddit": ex.get "subreddit" , "title": ex.get "title" , "author": p.get "author" or {} .get "username" , "score": m.get "likes" , "comments": m.get "comments" , "published at": ex.get "published at" , "url": ex.get "url" , "top comment": best :200 , } def append csv path, rows : path = Path path new file = not path.exists with path.open "a", newline="", encoding="utf-8" as f: w = csv.DictWriter f, fieldnames=FIELDS if new file: w.writeheader w.writerows rows def notify rows : url = os.environ.get "SLACK WEBHOOK URL" if not url or not rows: return lines = f" {len rows } new Reddit posts " for r in rows :15 : lines.append f"• {r 'source' } r/{r 'subreddit' }: <{r 'url' }|{r 'title' } " f" {r 'score' } pts, {r 'comments' } comments " requests.post url, json={"text": "\n".join lines }, timeout=30 def run : seen = load seen found = for name, q in QUERIES.items : found += name, p for p in only new search q , seen for sub in SUBREDDITS: found += f"r/{sub}", p for p in only new intent posts sub , seen rows = for source, p in found: comments, = top comments p "extra" "source id" , MENTION if any c "mentions" for c in comments : source += " +mentioned in comments" rows.append row source, p, comments append csv "reddit mentions.csv", rows notify rows save seen seen print f"{len rows } new posts, spent this run: ${spent:.4f}" if name == " main ": run The state is saved only after the CSV and the Slack message go out, so a crash mid-run means the next run reports those posts again instead of losing them. Run it once by hand, then schedule it: python3 reddit monitor.py crontab -e .env holds: export QOVIA KEY=... and export SLACK WEBHOOK URL=... 0 cd /path/to/monitor && . ./.env && python3 reddit monitor.py monitor.log 2 &1 Output looks something like this illustrative, not real data : note: Reddit searched 'acme analytic' instead of 'acmeanalytics' 4 new posts, spent this run: $0.0140 And in Slack also illustrative : 4 new Reddit posts • brand r/webdev: Anyone tried Acme Analytics for a static site? 12 pts, 9 comments • competitor r/selfhosted: Plausible alternative that runs on SQLite? 31 pts, 22 comments • r/SaaS r/SaaS: Looking for privacy-friendly analytics for a B2B app 5 pts, 3 comments • r/webdev +mentioned in comments r/webdev: What do you use for pageview tracking in 2026? 48 pts, 61 comments The last one is the interesting kind: a post that never names you, where someone in the comments already did. For one-off research "what did r/selfhosted say about analytics tools this month?" a script is overkill. The same endpoints are available through Qovia's MCP server at https://api.qovia.ai/mcp Streamable HTTP, same API key in an Authorization: Bearer header, same billing as the HTTP API . In Claude Code: claude mcp add --transport http qovia https://api.qovia.ai/mcp \ --header "Authorization: Bearer $QOVIA KEY" Then ask something like "search Reddit for posts from the last week asking for a Plausible alternative, and summarize what the top comments recommend." Configs for Cursor, VS Code and Claude Desktop are in the MCP docs https://qovia.ai/docs/mcp/?utm source=devto&utm medium=article&utm campaign=reddit-keyword-monitor-python . The assistant is good for digging into one question; the cron job is better for not missing anything. Every Reddit endpoint used here search , subreddit posts , comments , and post / comment replies if you add them is a fixed $0.001 per successful call $1 per 1,000 . Empty results, errors and 404s are not charged, so a quiet hour where search finds nothing costs nothing for that query. As a rough example arithmetic only : with 2 queries x up to 2 search pages, 3 subreddits x up to 2 pages, and one comment page per new post, a run is at most 10 calls plus one per new post. With 4 new posts that's $0.014. Run hourly, the worst case is 240 calls a day $0.24 plus one call per new post, so roughly $7 to $8 a month; it's less in practice because a search with no new results returns empty and isn't charged. The subreddit feeds are the fixed part: one page per subreddit, or running every three hours, cuts that by half or more. The spent counter prints the real number each run. New accounts get 50 trial calls, counted only when a call returns data; after that it's a prepaid balance with no monthly fee. Details are on the pricing page https://qovia.ai/pricing/?utm source=devto&utm medium=article&utm campaign=reddit-keyword-monitor-python , and every parameter is in the API docs https://qovia.ai/docs/?utm source=devto&utm medium=article&utm campaign=reddit-keyword-monitor-python . The default rate limit is 60 requests per minute per account, far more than an hourly job needs. subreddit posts carries only the first 300 characters of the body; fetch GET /v1/raw/reddit/post when you need the full text. corrected query and test your queries on reddit.com once before trusting them. If you build on this, tell me in the comments what you'd want it to flag besides mentions. Drafted with AI assistance and checked against the live API docs.