Scrapy是一个功能强大的Python爬虫框架,可以通过多种方式来优化以提高性能和效率。以下是一些常见的优化策略:
settings.py
文件中的CONCURRENCY_LEVEL
和DOWNLOAD_DELAY
来控制并发请求数和下载延迟,避免对目标服务器造成过大压力。CONCURRENCY_LEVEL = 8
DOWNLOAD_DELAY = 1.0
DOWNLOAD_THROTTLE_RATE
来限制下载速度,避免被封禁IP。DOWNLOAD_THROTTLE_RATE = '5/m'
class CustomMiddleware:
def process_request(self, request, spider):
request.headers['User-Agent'] = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
COMPRESS_ENABLED
和COMPRESS_MIME_TYPES
来压缩响应内容,减少传输数据量。COMPRESS_ENABLED = True
COMPRESS_MIME_TYPES = ['text/html', 'text/xml', 'text/plain']
yield response.xpath('//div[@class="item"]//h2/text()').getall()
for item in response.css('div.item'):
title = item.css('h2::text').get()
class MyPipeline:
def process_item(self, item, spider):
item['title'] = item['title'].strip().upper()
return item
process_item
方法中缓存重复计算的结果。class MyPipeline:
def __init__(self):
self.titles = set()
def process_item(self, item, spider):
if item['title'] not in self.titles:
item['title'] = item['title'].strip().upper()
self.titles.add(item['title'])
return item
class MySpider(scrapy.Spider):
@classmethod
def from_crawler(cls, crawler, *args, **kwargs):
spider = super().from_crawler(crawler, *args, **kwargs)
spider.logger.info = lambda *args, **kwargs: crawler.stats.inc_value('my_custom_event')
return spider
def parse(self, response):
if response.status != 200:
self.logger.error(f"Failed to access {response.url}")
return
# 继续解析逻辑
DOWNLOADER_MIDDLEWARES = {
'scrapy.downloadermiddlewares.retry.RetryMiddleware': 550,
}
RETRY_ENABLED = True
RETRY_TIMES = 3
LOG_FILE = 'my_spider.log'
LOG_LEVEL = 'INFO'
通过以上这些优化策略,可以显著提高Scrapy爬虫的性能和效率。根据具体需求和目标,可以选择合适的优化方法进行实施。