pyscrappy 1.0.1

A robust, all-in-one Python web scraping toolkit

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PyScrappy: robust, all-in-one Python web scraping toolkit

PyScrappy is a Python toolkit for web scraping that works out of the box. Point it at any URL and get structured data back — or use built-in scrapers for Wikipedia, IMDB, Yahoo Finance, news feeds, and more.

Key features

• Generic scraper — give it any URL, get back structured text, links, images, tables, and metadata
• Auto-pagination — automatically follows "next page" links
• JS rendering — optional Playwright backend for JavaScript-heavy sites
• Custom selectors — pass CSS selectors to extract exactly what you need
• Built-in scrapers — Wikipedia, IMDB, Yahoo Finance, news (RSS), image search, Amazon, LinkedIn
• Clean API — every scraper returns a ScrapeResult with .to_dataframe() and .to_json()
• Retry & rate-limiting — built-in exponential backoff and per-domain rate limiting
• Type-safe — full type hints, py.typed marker

Installation

pip install pyscrappy

Optional extras:

# Browser support (for JS-rendered pages)
pip install 'pyscrappy[browser]'
playwright install chromium

# DataFrame support
pip install 'pyscrappy[dataframe]'

# Everything
pip install 'pyscrappy[all]'

Quick start

Scrape any URL (one-liner)

from pyscrappy import scrape

result = scrape("https://en.wikipedia.org/wiki/Web_scraping")
print(result.data[0]["metadata"]["title"])
print(result.data[0]["text"]["word_count"])

Custom CSS selectors

from pyscrappy import GenericScraper

with GenericScraper() as gs:
    result = gs.scrape(
        url="https://news.ycombinator.com",
        selectors={"title": ".titleline a", "score": ".score"},
    )
    for item in result.data:
        print(item["title"], item.get("score", ""))

Wikipedia

from pyscrappy import WikipediaScraper

with WikipediaScraper() as ws:
    result = ws.scrape(query="Python (programming language)", mode="summary")
    print(result.data[0]["text"])

Stock data

from pyscrappy import StockScraper

with StockScraper() as ss:
    result = ss.scrape(symbol="AAPL", mode="history", period="1mo")
    df = result.to_dataframe()
    print(df.head())

IMDB

from pyscrappy import IMDBScraper

with IMDBScraper() as scraper:
    result = scraper.scrape(genre="sci-fi", max_pages=2)
    df = result.to_dataframe()
    print(df[["title", "year", "rating"]])

News (RSS feeds)

from pyscrappy import NewsScraper

with NewsScraper() as ns:
    result = ns.scrape(feed_url="https://rss.nytimes.com/services/xml/rss/nyt/World.xml")
    for article in result.data[:5]:
        print(article["title"])

Image search

from pyscrappy import ImageSearchScraper

with ImageSearchScraper() as iss:
    result = iss.scrape(query="golden retriever", max_images=10, download_to="./dogs")

Configuration

from pyscrappy import ScraperConfig, GenericScraper

config = ScraperConfig(
    timeout=20.0,            # request timeout in seconds
    max_retries=3,           # retry failed requests
    rate_limit=2.0,          # seconds between requests per domain
    proxy="http://...",      # HTTP/SOCKS proxy
    headless=True,           # browser runs headless
    render_js="auto",        # auto-detect if JS rendering is needed
)

with GenericScraper(config) as gs:
    result = gs.scrape(url="https://example.com")

YouTube

from pyscrappy import YouTubeScraper

with YouTubeScraper() as scraper:
    result = scraper.scrape(query="python tutorial", max_results=10)
    for video in result.data:
        print(video["title"], video.get("views", ""))

SoundCloud

from pyscrappy import SoundCloudScraper

with SoundCloudScraper() as scraper:
    result = scraper.scrape(query="lo-fi beats", max_results=10)

E-Commerce (Alibaba, Flipkart, Snapdeal)

from pyscrappy import AlibabaScraper, FlipkartScraper, SnapdealScraper

with FlipkartScraper() as scraper:
    result = scraper.scrape(query="laptop", max_pages=2)
    df = result.to_dataframe()

Food Delivery (Swiggy, Zomato)

from pyscrappy import SwiggyScraper, ZomatoScraper

# These are JS-heavy — use render_js=True for best results
with SwiggyScraper() as scraper:
    result = scraper.scrape(city="bangalore", render_js=True)

Built-in scrapers

Scraper	What it does	Needs browser?
GenericScraper	Scrape any URL with auto-extraction	Optional
Data / Research
WikipediaScraper	Articles, sections, infoboxes	No
IMDBScraper	Movies by genre, search, charts	No
StockScraper	Quotes, history, profiles (Yahoo Finance)	No
NewsScraper	RSS/Atom feeds, article extraction	No
ImageSearchScraper	Image search + download	No
LinkedInJobsScraper	Public job listings	No
E-Commerce
AmazonScraper	Product search	No
AlibabaScraper	Product search	No
FlipkartScraper	Product search	No
SnapdealScraper	Product search	No
Social Media
YouTubeScraper	Video search, channel scraping	Optional
InstagramScraper	Profiles, hashtag posts	Recommended
TwitterScraper	Tweet search	Recommended
Music
SpotifyScraper	Track/playlist search	Recommended
SoundCloudScraper	Track search	Optional
Food Delivery
SwiggyScraper	Restaurant listings	Recommended
ZomatoScraper	Restaurant listings	Recommended

Dependencies

Required: httpx, beautifulsoup4, lxml

Optional: playwright (JS rendering), pandas (DataFrames)

License

MIT

Contributing

All contributions welcome. See Issues.

This package is for educational and research purposes.