Reddit Reviews

1. fzhsd

   · wall at tree · about 3 years ago
   reddit review

   i like reddit very much

   🏁 Competitors: Hyprland

   👍 Pros:    Bad|Stupid

   👎 Cons:    I love reddit

CodeOcean Reviews

Reddit mentions (3301)

• GitHub Trending to Product Ideas: Automated Market Signal Pipeline

  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

• How I Built an Autonomous PR Agent with SerpApi, LangGraph, and LangSmith

  @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

• How to Scrape Reddit in 2026: Subreddits, Posts, Comments via Python

  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

• I Built a Tool That Lets You Solve CAPTCHAs Once and Automate Forever

  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

• SEO tools I used to grow my sites to 20k+ visitors/month

  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

CodeOcean mentions (3)

• Ask HN: PG's 'Do Things That Don't Scale' Manual Examples

  I was an early hire at a computational reproducibility startup for scientists [0]; The platform was basically a web-based frontend wrapped around a Docker container hosted on AWS, and the idea was that you'd put your code and data on the platform and have it be online-executable indefinitely, and you wouldn't have to worry about package updates, functions breaking, etc., because it was containerized. The... - Source: Hacker News / almost 3 years ago

• Show HN: Open-source infra for data scientists

  It looks like Magniv is targeting Python in general. This is similar to ClearML. What are the differentiating points to Magniv compared to similar products? It seems like the product also integrates with SCM systems. Are you using gitea and then containers to push code and data to execution like CodeOcean? https://github.com/allegroai/clearml https://codeocean.com/. - Source: Hacker News / over 4 years ago

• publishing data analysis performed in R/code availability

  Code ocean also exists for this purpose, though the number of compute hours is limited on free academic licenses. Source: almost 5 years ago