pyscrappy

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.

Metadata

Release files for pyscrappy 1.0.4

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Source distribution for pyscrappy 1.0.4
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Uploaded via	`twine/6.1.0 CPython/3.13.12`