philiprehberger-web-scraper 0.2.0

Lightweight web scraper with rate limiting and CSS selectors.

philiprehberger-web-scraper

Lightweight web scraper with rate limiting and CSS selectors.

Installation

pip install philiprehberger-web-scraper

Usage

from philiprehberger_web_scraper import Scraper

scraper = Scraper(rate_limit=2.0, retry_attempts=3)

# Fetch a single page
page = scraper.get("https://example.com")
titles = page.select_all("h2.title")
link = page.select_one("a.next")
all_links = page.links()

# Extract data
for el in page.select_all(".product"):
    print(el.select_one(".name").text)
    print(el.select_one("a").attr("href"))

# Crawl multiple pages
for page in scraper.crawl("https://example.com/blog", max_pages=20):
    for article in page.select_all("article"):
        print(article.select_one("h2").text)

# Export
Scraper.export_csv(data, "output.csv")
Scraper.export_json(data, "output.json")

Retry with Backoff

Transient HTTP errors (429 and 503) are retried automatically with exponential backoff. Configure the number of attempts and base delay:

from philiprehberger_web_scraper import Scraper

scraper = Scraper(retry_attempts=5, retry_delay=2.0)
page = scraper.get("https://example.com/api")

Response Caching

Cache fetched pages to disk so repeated requests for the same URL skip the network entirely:

from philiprehberger_web_scraper import Scraper, ResponseCache

cache = ResponseCache(cache_dir=".scraper_cache")
scraper = Scraper(cache=cache)

page = scraper.get("https://example.com")  # fetches from network
page = scraper.get("https://example.com")  # served from disk cache

cache.clear()  # remove all cached responses

Table Extraction

Pull an HTML table into a list of dicts using extract_table():

from philiprehberger_web_scraper import Scraper, extract_table

scraper = Scraper()
page = scraper.get("https://example.com/data")
rows = extract_table(page, "table#prices")
# [{"Product": "Widget", "Price": "$9.99"}, ...]

Following Paginated Links

Use follow_links() to crawl paginated content by following a CSS-selected link on each page:

from philiprehberger_web_scraper import Scraper

scraper = Scraper()
for page in scraper.follow_links("https://example.com/page/1", "a.next-page", max_pages=10):
    for item in page.select_all(".result"):
        print(item.text)

Proxy Rotation

Distribute requests across multiple proxies by passing a list of proxy URLs:

from philiprehberger_web_scraper import Scraper

scraper = Scraper(proxies=[
    "http://proxy1:8080",
    "http://proxy2:8080",
    "http://proxy3:8080",
])
page = scraper.get("https://example.com")  # uses proxy1
page = scraper.get("https://example.com/2")  # uses proxy2

API

Function / Class	Description
Scraper(rate_limit, retry_attempts, retry_delay, timeout, headers, cache, proxies)	Web scraper with rate limiting, retry, caching, and proxy rotation
Scraper.get(url)	Fetch a single page with retry and optional caching
Scraper.get_json(url)	Fetch JSON from a URL
Scraper.follow_links(start_url, selector, max_pages)	Follow paginated links matching a CSS selector
Scraper.crawl(start_url, max_pages, same_domain, next_selector)	Crawl pages starting from a URL
Scraper.export_csv(data, path)	Export list of dicts to CSV
Scraper.export_json(data, path, indent)	Export data to JSON
Page	A fetched web page with select_one(), select_all(), links(), images(), and title/text properties
Element	Wrapper around a parsed element with text, html, attr(), select_one(), select_all()
ResponseCache(cache_dir)	Disk-backed response cache with get(), put(), and clear() methods
extract_table(page, selector)	Extract an HTML table into a list of dicts

Development

pip install -e .
python -m pytest tests/ -v

Support

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License

MIT