在Python中,Scrapy爬虫可以通过多种方式进行分布式爬取,以提高爬取效率和速度。以下是一些常见的分布式爬取方法:
Scrapy-Redis是一个将Scrapy与Redis集成的扩展,可以方便地进行分布式爬取。
pip install scrapy-redis
在settings.py
文件中添加以下配置:
# 启用Scrapy-Redis调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
# 启用Scrapy-Redis去重
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
# 启用Scrapy-Redis优先级队列
SCHEDULER_PRIORITY_QUEUE = "scrapy_redis.priorityqueue.PriorityQueue"
# Redis连接信息
REDIS_HOST = 'localhost'
REDIS_PORT = 6379
REDIS_DB = 0
使用Redis作为调度器启动爬虫:
scrapy crawl myspider -s JOBDIR=redis://localhost:6379/myspider
Scrapy-Cluster是一个用于分布式爬取的框架,支持多节点协作。
pip install scrapy-cluster
在settings.py
文件中添加以下配置:
# 启用Scrapy-Cluster调度器
SCHEDULER = "scrapy_cluster.scheduler.Scheduler"
# 启用Scrapy-Cluster去重
DUPEFILTER_CLASS = "scrapy_cluster.dupefilter.RFPDupeFilter"
# 启用Scrapy-Cluster优先级队列
SCHEDULER_PRIORITY_QUEUE = "scrapy_cluster.priorityqueue.PriorityQueue"
# 配置Scrapy-Cluster节点信息
CLUSTER_NODES = {
'node1': {'host': '127.0.0.1', 'port': 5000},
'node2': {'host': '127.0.0.1', 'port': 5001},
}
使用Scrapy-Cluster启动爬虫:
scrapy crawl myspider -s JOBDIR=redis://localhost:6379/myspider
Scrapy-Splash是一个用于处理JavaScript渲染页面的扩展,可以与Scrapy结合使用进行分布式爬取。
pip install scrapy-splash
在settings.py
文件中添加以下配置:
# 启用Scrapy-Splash
DOWNLOADER_MIDDLEWARES = {
'scrapy_splash.SplashCookiesMiddleware': 723,
'scrapy_splash.SplashMiddleware': 725,
'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware': 810,
}
SPIDER_MIDDLEWARES = {
'scrapy_splash.SplashDeduplicateArgsMiddleware': 100,
}
DUPEFILTER_CLASS = 'scrapy_splash.SplashAwareDupeFilter'
HTTPCACHE_STORAGE = 'scrapy_splash.SplashAwareFSCacheStorage'
SPLASH_URL = 'http://localhost:8050'
DOWNLOADER_URL = f'{SPLASH_URL}/render.json'
docker pull scrapinghub/splash
docker run -p 8050:8050 -p 5023:5023 scrapinghub/splash
使用Scrapy-Splash启动爬虫:
scrapy crawl myspider -s SPLASH_URL=http://localhost:8050
Celery是一个分布式任务队列,可以与Scrapy结合使用进行分布式爬取。
pip install celery
在项目根目录下创建celery.py
文件:
from __future__ import absolute_import, unicode_literals
import os
from celery import Celery
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'myproject.settings')
app = Celery('myproject')
app.config_from_object('django.conf:settings', namespace='CELERY')
app.autodiscover_tasks()
在settings.py
文件中添加以下配置:
# 启用Celery
BROKER_URL = 'redis://localhost:6379/0'
CELERY_RESULT_BACKEND = 'redis://localhost:6379/0'
在myproject/tasks.py
文件中创建任务:
from celery import shared_task
from scrapy.crawler import CrawlerProcess
from scrapy.utils.project import get_project_settings
@shared_task
def crawl_spider(spider_name):
process = CrawlerProcess(get_project_settings())
process.crawl(spider_name)
process.start()
celery -A myproject worker --loglevel=info
celery -A myproject crawl_spider -s spider_name=myspider
以上是几种常见的分布式爬取方法,可以根据具体需求选择合适的方法进行实现。