gracyvsscrapling
Gracy is an API client library based on httpx that provides an extra stability layer with:
- Retry logic
- Logging
- Connection throttling
- Tracking/Middleware
In web scraping, Gracy can be a convenient tool for creating scraper based API clients.
Scrapling is an adaptive web scraping framework for Python that introduces "self-healing" selectors — selectors that can track and find elements even when the website's DOM structure changes. This solves one of the biggest maintenance headaches in web scraping: broken selectors after website updates.
Key features include:
- Self-healing selectors Scrapling uses smart element matching that can identify target elements even after the page structure changes. It builds a fingerprint of the element based on multiple attributes (text, position, siblings, attributes) and uses fuzzy matching to relocate it.
- Multiple parsing backends Supports different parsing engines including lxml (fast) and a custom engine, allowing you to choose the right balance of speed and features.
- Scrapy-like Spider API Provides a familiar Spider class pattern for organizing crawling logic, similar to Scrapy but with the added benefit of adaptive selectors.
- CSS and XPath selectors Full support for CSS selectors and XPath, plus the adaptive matching system on top.
- Type hints and modern Python Built with full type annotations and 92% test coverage for reliability.
- Async support Supports asynchronous crawling for efficient concurrent scraping.
Scrapling gained massive traction in 2025 as one of the most starred new Python scraping libraries. It is particularly useful for scraping targets that frequently update their HTML structure, where traditional selector-based scrapers would break.
Highlights
css-selectorsxpathfastpopular
Example Use
```python
# 0. Import
import asyncio
from typing import Awaitable
from gracy import BaseEndpoint, Gracy, GracyConfig, LogEvent, LogLevel
# 1. Define your endpoints
class PokeApiEndpoint(BaseEndpoint):
GET_POKEMON = "/pokemon/{NAME}" # 👈 Put placeholders as needed
# 2. Define your Graceful API
class GracefulPokeAPI(Gracy[str]):
class Config: # type: ignore
BASE_URL = "https://pokeapi.co/api/v2/" # 👈 Optional BASE_URL
# 👇 Define settings to apply for every request
SETTINGS = GracyConfig(
log_request=LogEvent(LogLevel.DEBUG),
log_response=LogEvent(LogLevel.INFO, "{URL} took {ELAPSED}"),
parser={
"default": lambda r: r.json()
}
)
async def get_pokemon(self, name: str) -> Awaitable[dict]:
return await self.get(PokeApiEndpoint.GET_POKEMON, {"NAME": name})
# Note: since Gracy is based on httpx we can customized the used client with custom headers etc"
def _create_client(self) -> httpx.AsyncClient:
client = super()._create_client()
client.headers = {"User-Agent": f"My Scraper"}
return client
pokeapi = GracefulPokeAPI()
async def main():
try:
pokemon = await pokeapi.get_pokemon("pikachu")
print(pokemon)
finally:
pokeapi.report_status("rich")
asyncio.run(main())
```
```python
from scrapling import Fetcher, StealthFetcher, PlayWrightFetcher
# Simple fetching with adaptive parsing
fetcher = Fetcher()
page = fetcher.get("https://example.com/products")
# CSS selectors work as expected
products = page.css(".product-card")
for product in products:
name = product.css_first(".name").text()
price = product.css_first(".price").text()
print(f"{name}: {price}")
# Adaptive selector - finds the element even if DOM changes
# Uses element fingerprinting for resilient matching
element = page.find("Product Title", auto_match=True)
# Stealth fetching with anti-bot bypass
stealth = StealthFetcher()
page = stealth.get("https://protected-site.com")
# Playwright-based fetching for JS-rendered pages
pw = PlayWrightFetcher()
page = pw.get("https://spa-example.com", headless=True)
```
Alternatives / Similar
katana
new
crawl4ai
new
scrapling
new
crawlee
new
mechanize
new
scrapegraphai
new
botasaurus
new
goutte
new
kimurai
new
firecrawl
new
jsdom
new
katana
new
crawl4ai
new
crawlee
new
mechanize
new
scrapegraphai
new
botasaurus
new
goutte
new
kimurai
new
simple-html-dom
new
firecrawl
new