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Reddit
SQLAlchemyi like reddit very much
Based on our record, Reddit seems to be a lot more popular than SQLAlchemy. While we know about 3301 links to Reddit, we've tracked only 2 mentions of SQLAlchemy. 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.
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
@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 / 4 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
Under the hood, LangChain works with SQLAlchemy to connect to various types of databases. This means it can work with many popular databases, like MS SQL, MySQL, MariaDB, PostgreSQL, Oracle SQL, and SQLite. To learn more about connecting LangChain to your specific database, you can check the SQLAlchemy documentation for helpful information and requirements. - Source: dev.to / about 3 years ago
SQLModel is a library for interacting with SQL databases from Python code, using Python objects. It is designed to be intuitive, easy-to-use, highly compatible, and robust. It is powered by Pydantic and SQLAlchemy and relies on Python type annotations for maximum simplicity. The key features are: it's intuitive to write and use, highly compatible, extensible, and minimizes code duplication. The library does a lot... - Source: dev.to / over 3 years ago
X (Twitter) - Connect with your friends and other fascinating people. Get in-the-moment updates on the things that interest you. And watch events unfold, in real time, from every angle.
Hibernate - Hibernate an open source Java persistence framework project.
Facebook - Connect with friends, family and other people you know. Share photos and videos, send messages and get updates.
Sequel Pro - MySQL database management for Mac OS X
YouTube - Our mission is to give everyone a voice and show them the world.
phpMyAdmin - phpMyAdmin is a tool written in PHP intended to handle the administration of MySQL over the Web.