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FastComments
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i like reddit very much
Based on our record, Reddit seems to be a lot more popular than FastComments. While we know about 3301 links to Reddit, we've tracked only 7 mentions of FastComments. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I'm working on Watch.ly - a remote human-in-the-loop networking and FS sandbox for AI agents like openclaw: https://watch.ly/ Also this week launching https://dirtforever.net/ which is an open alternative to RaceNet Clubs for Dirt Rally 2, since EA is shutting that down. I'm also expanding the SDK and plugin space for https://fastcomments.com and am planning on adding AI agents because everyone expects that now :)... - Source: Hacker News / 4 months ago
Hello! This year I've been working on building an integrated registration and live timing platform [0] for my local organizers in CA, but it is spreading. Very fun/rewarding project. I hope to launch my own cellular-based timing hardware this year which will integrate into the timing platform (right now I've reverse engineered and now support 5 different chronometers, I never knew cross platform serial port comms... - Source: Hacker News / almost 2 years ago
Another one I can recommend enthusiastically but forgot to mention before, is a paid service called FastComments (https://fastcomments.com/). Great, non-heavy code with a super-helpful developer. Source: about 4 years ago
With a quick search, I found https://fastcomments.com/, which does provide comments storage. What does your library provide that this service doesn't? Source: about 4 years ago
I just started using https://fastcomments.com/. I am still in the free trial but it seems pretty good so far. Source: over 5 years ago
From urllib.parse import urlparse Def normalize_gh(r): return { "title": r["name"], "url": r["url"], "source": "github", "score": r["stars_this_period"], "desc": r.get("description", ""), "date": r["trending_date"], "lang": r.get("language"), } Def normalize_hn(p): return { "title": p["title"].replace("Show HN: ", ""), "url":... - Source: dev.to / 4 months ago
@tool Def search_reddit(keywords: str, max_results: int = 20) -> list[dict]: """Fallback: search Reddit directly via PRAW.""" reddit = praw.Reddit( client_id=os.environ["REDDIT_CLIENT_ID"], client_secret=os.environ["REDDIT_CLIENT_SECRET"], user_agent="doug-agent/1.0", ) candidates = [] for submission in reddit.subreddit("all").search(keywords, sort="new",... - Source: dev.to / 3 months ago
Import requests Import time Def fetch_subreddit_posts(subreddit, sort="hot", limit=25): url = f"https://www.reddit.com/r/{subreddit}/{sort}.json" params = { "limit": limit, "raw_json": 1, # Prevents HTML encoding in responses } headers = { "User-Agent": "PythonScraper/1.0 (research project)" } response = requests.get(url, params=params, headers=headers) if... - Source: dev.to / 4 months ago
From sessionkeeper import SessionKeeper Async with SessionKeeper("reddit") as sk: page = await sk.get_authenticated_page("https://reddit.com") # You're logged in. Do your automation. await page.goto("https://reddit.com/r/blender/submit"). - Source: dev.to / 5 months ago
It's completely free, and takes just moments to set up - you just need to create an account, and set up keywords for the service to track. When your keywords are mentioned on Reddit, Hackernews, or Lobste.rs, you'll get a tidy little email in your inbox. - Source: dev.to / over 1 year ago
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