Reddit
X (Twitter)
Facebook
YouTube
Google
Quora
Instagram
Hacker News
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Reddit Matplotlibi like reddit very much
Based on our record, Reddit seems to be a lot more popular than Matplotlib. While we know about 3301 links to Reddit, we've tracked only 114 mentions of Matplotlib. 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 / 2 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 / 3 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
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months 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.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Facebook - Connect with friends, family and other people you know. Share photos and videos, send messages and get updates.
NumPy - NumPy is the fundamental package for scientific computing with Python
YouTube - Our mission is to give everyone a voice and show them the world.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
