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

Qdrant 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 / 3 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 / 4 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

Qdrant mentions (63)

• How to give Claude Code persistent memory with a self-hosted mem0 MCP server

  The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago

• The Database Zoo: Vector Databases and High-Dimensional Search

  Qdrant: Open-source vector database optimized for hybrid search and easy integration with ML workflows. - Source: dev.to / 8 months ago

• Java's Agentic Framework Boom is a Code Smell

  Yes, Java SDKs are critical. But you don't need to rebuild entire orchestration engines just to write agents in Java. The ecosystem already has platforms solving the hard problems: memory (Zep, Mem0, LangMem), tools (specialized platforms), vectors (Pinecone, Weaviate, Qdrant), observability (LangSmith, Helicone, Langfuse). Integrate, don't rebuild. - Source: dev.to / 9 months ago

• What is the Most Effective AI Tool for App Development Today?

  James Allsopp adds, "LangChain or LlamaIndex for managing LLM workflows, especially if you're adding vector search or documents." These tools handle multi-step processes, essential for complex apps. - Source: dev.to / 11 months ago

• 🔥 Build a RAG Chatbot That Talks to Your Documents Using Python (Gemma + Qdrant + Docling)

  📦 Qdrant for fast vector search and retrieval. - Source: dev.to / 12 months ago