botasaurusvsgracy
Botasaurus is an all-in-one Python web scraping framework that combines browser automation, anti-detection, and scaling features into a single package. It aims to simplify the entire web scraping workflow from development to deployment.
Key features include:
- Anti-detect browser Ships with a stealth-patched browser that passes common bot detection tests. Automatically handles fingerprinting, user agent rotation, and other anti-detection measures.
- Decorator-based API Uses Python decorators (@browser, @request) to define scraping tasks, making code clean and easy to organize.
- Built-in parallelism Easy parallel execution of scraping tasks across multiple browser instances with configurable concurrency.
- Caching Built-in caching layer to avoid re-scraping pages during development and debugging.
- Profile persistence Can save and reuse browser profiles (cookies, localStorage) across scraping sessions for maintaining login state.
- Output handling Automatic output to JSON, CSV, or custom formats with built-in data filtering.
- Web dashboard Includes a web UI for monitoring scraping progress, viewing results, and managing tasks.
Botasaurus is designed for developers who want a batteries-included framework that handles anti-detection automatically, without needing to manually configure stealth settings or manage browser fingerprints.
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.
Highlights
anti-detectstealthlarge-scale
Example Use
```python
from botasaurus.browser import browser, Driver
from botasaurus.request import request, Request
# Browser-based scraping with anti-detection
@browser(parallel=3, cache=True)
def scrape_products(driver: Driver, url: str):
driver.get(url)
# Wait for content to load
driver.wait_for_element(".product-list")
# Extract product data
products = []
for el in driver.select_all(".product-card"):
products.append({
"name": el.select(".product-name").text,
"price": el.select(".product-price").text,
"url": el.select("a").get_attribute("href"),
})
return products
# HTTP-based scraping (no browser needed)
@request(parallel=5, cache=True)
def scrape_api(req: Request, url: str):
response = req.get(url)
return response.json()
# Run the scraper
results = scrape_products(
["https://example.com/page/1", "https://example.com/page/2"]
)
```
```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())
```
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