crawlee-python/docs/deployment/code_examples/aws/beautifulsoup_crawler_lambd...

62 lines
2.0 KiB
Python

import asyncio
import json
from datetime import timedelta
from typing import Any
from aws_lambda_powertools.utilities.typing import LambdaContext
from crawlee.crawlers import BeautifulSoupCrawler, BeautifulSoupCrawlingContext
from crawlee.storage_clients import MemoryStorageClient
from crawlee.storages import Dataset, RequestQueue
async def main() -> str:
# highlight-start
# Disable writing storage data to the file system
storage_client = MemoryStorageClient()
# highlight-end
# Initialize storages
dataset = await Dataset.open(storage_client=storage_client)
request_queue = await RequestQueue.open(storage_client=storage_client)
crawler = BeautifulSoupCrawler(
storage_client=storage_client,
max_request_retries=1,
request_handler_timeout=timedelta(seconds=30),
max_requests_per_crawl=10,
)
@crawler.router.default_handler
async def request_handler(context: BeautifulSoupCrawlingContext) -> None:
context.log.info(f'Processing {context.request.url} ...')
data = {
'url': context.request.url,
'title': context.soup.title.string if context.soup.title else None,
'h1s': [h1.text for h1 in context.soup.find_all('h1')],
'h2s': [h2.text for h2 in context.soup.find_all('h2')],
'h3s': [h3.text for h3 in context.soup.find_all('h3')],
}
await context.push_data(data)
await context.enqueue_links()
await crawler.run(['https://crawlee.dev'])
# Extract data saved in `Dataset`
data = await crawler.get_data()
# Clean up storages after the crawl
await dataset.drop()
await request_queue.drop()
# Serialize the list of scraped items to JSON string
return json.dumps(data.items)
def lambda_handler(_event: dict[str, Any], _context: LambdaContext) -> dict[str, Any]:
result = asyncio.run(main())
# Return the response with results
return {'statusCode': 200, 'body': result}