爬虫相关-scrapy框架介绍
性能相关-进程、线程、协程
在编写爬虫时，性能的消耗主要在IO请求中，当单进程单线程模式下请求URL时必然会引起等待，从而使得请求整体变慢。
串行执行
import requests
def fetch_async(url):
response = requests.get(url)
return response
url_list = ['http://www.github.com', 'http://www.bing.com']
for url in url_list:
fetch_async(url)
多线程执行
from concurrent.futures import ThreadPoolExecutor
import requests
def fetch_async(url):
response = requests.get(url)
return response
url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ThreadPoolExecutor(5)
for url in url_list:
pool.submit(fetch_async, url)
pool.shutdown(wait=True)
多线程+回调函数
from concurrent.futures import ThreadPoolExecutor
import requests
def fetch_async(url):
response = requests.get(url)
return response
def callback(future):
print(future.result())
url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ThreadPoolExecutor(5)
for url in url_list:
v = pool.submit(fetch_async, url)
v.add_done_callback(callback)
pool.shutdown(wait=True)
多进程执行
from concurrent.futures import ProcessPoolExecutor
import requests
def fetch_async(url):
response = requests.get(url)
return response
url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ProcessPoolExecutor(5)
for url in url_list:
pool.submit(fetch_async, url)
pool.shutdown(wait=True)
多进程+回调函数
from concurrent.futures import ProcessPoolExecutor
import requests
def fetch_async(url):
response = requests.get(url)
return response
def callback(future):
print(future.result())
url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ProcessPoolExecutor(5)
for url in url_list:
v = pool.submit(fetch_async, url)
v.add_done_callback(callback)
pool.shutdown(wait=True)
通过上述代码均可以完成对请求性能的提高，对于多线程和多进行的缺点是在IO阻塞时会造成了线程和进程的浪费，所以异步IO会是首选：
asyncio 例子1:
import asyncio
@asyncio.coroutine
def func1():
print('before...func1......')
yield from asyncio.sleep(5)
print('end...func1......')
tasks = [func1(), func1()]
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
asyncIO例子2:
import asyncio
@asyncio.coroutine
def fetch_async(host, url='/'):
print(host, url)
reader, writer = yield from asyncio.open_connection(host, 80)
request_header_content = """GET %s HTTP/1.0\r\nHost: %s\r\n\r\n""" % (url, host,)
request_header_content = bytes(request_header_content, encoding='utf-8')
writer.write(request_header_content)
yield from writer.drain()
text = yield from reader.read()
print(host, url, text)
writer.close()
tasks = [
fetch_async('www.cnblogs.com', '/wupeiqi/'),
fetch_async('dig.chouti.com', '/pic/show?nid=4073644713430508&lid=10273091')
]
loop = asyncio.get_event_loop()
results = loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
asyncio + aiohttp
import aiohttp
import asyncio
@asyncio.coroutine
def fetch_async(url):
print(url)
response = yield from aiohttp.request('GET', url)
# data = yield from response.read()
# print(url, data)
print(url, response)
response.close()
tasks = [fetch_async('http://www.google.com/'), fetch_async('http://www.chouti.com/')]
event_loop = asyncio.get_event_loop()
results = event_loop.run_until_complete(asyncio.gather(*tasks))
event_loop.close()
asyncio + requests
import asyncio
import requests
@asyncio.coroutine
def fetch_async(func, *args):
loop = asyncio.get_event_loop()
future = loop.run_in_executor(None, func, *args)
response = yield from future
print(response.url, response.content)
tasks = [
fetch_async(requests.get, 'http://www.cnblogs.com/wupeiqi/'),
fetch_async(requests.get, 'http://dig.chouti.com/pic/show?nid=4073644713430508&lid=10273091')
]
loop = asyncio.get_event_loop()
results = loop.run_until_complete(asyncio.gather(*tasks))
loop.close()
gevent + requests
import gevent
import requests
from gevent import monkey
monkey.patch_all()
def fetch_async(method, url, req_kwargs):
print(method, url, req_kwargs)
response = requests.request(method=method, url=url, **req_kwargs)
print(response.url, response.content)
# ##### 发送请求 #####
gevent.joinall([
gevent.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
gevent.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),
gevent.spawn(fetch_async, method='get', url='https://github.com/', req_kwargs={}),
])
# ##### 发送请求（协程池控制最大协程数量） #####
# from gevent.pool import Pool
# pool = Pool(None)
# gevent.joinall([
# pool.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
# pool.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),
# pool.spawn(fetch_async, method='get', url='https://www.github.com/', req_kwargs={}),
# ])
grequests
import grequests
request_list = [
grequests.get('http://httpbin.org/delay/1', timeout=0.001),
grequests.get('http://fakedomain/'),
grequests.get('http://httpbin.org/status/500')
]
# ##### 执行并获取响应列表 #####
# response_list = grequests.map(request_list)
# print(response_list)
# ##### 执行并获取响应列表（处理异常） #####
# def exception_handler(request, exception):
# print(request,exception)
# print("Request failed")
# response_list = grequests.map(request_list, exception_handler=exception_handler)
# print(response_list)
Twisted示例
from twisted.web.client import getPage, defer
from twisted.internet import reactor
def all_done(arg):
reactor.stop()
def callback(contents):
print(contents)
deferred_list = []
url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
for url in url_list:
deferred = getPage(bytes(url, encoding='utf8'))
deferred.addCallback(callback)
deferred_list.append(deferred)
dlist = defer.DeferredList(deferred_list)
dlist.addBoth(all_done)
reactor.run()
Tornado
from tornado.httpclient import AsyncHTTPClient
from tornado.httpclient import HTTPRequest
from tornado import ioloop
def handle_response(response):
"""
处理返回值内容（需要维护计数器，来停止IO循环），调用 ioloop.IOLoop.current().stop()
:param response:
:return:
"""
if response.error:
print("Error:", response.error)
else:
print(response.body)
def func():
url_list = [
'http://www.baidu.com',
'http://www.bing.com',
]
for url in url_list:
print(url)
http_client = AsyncHTTPClient()
http_client.fetch(HTTPRequest(url), handle_response)
ioloop.IOLoop.current().add_callback(func)
ioloop.IOLoop.current().start()
以上均是Python内置以及第三方模块提供异步IO请求模块，使用简便大大提高效率，而对于异步IO请求的本质则是非阻塞Socket+IO多路复用。
copy自大牛,Mark下:史上最牛逼的异步IO模块
import select
import socket
import time
class AsyncTimeoutException(TimeoutError):
"""
请求超时异常类
"""
def __init__(self, msg):
self.msg = msg
super(AsyncTimeoutException, self).__init__(msg)
class HttpContext(object):
"""封装请求和相应的基本数据"""
def __init__(self, sock, host, port, method, url, data, callback, timeout=5):
"""
sock: 请求的客户端socket对象
host: 请求的主机名
port: 请求的端口
port: 请求的端口
method: 请求方式
url: 请求的URL
data: 请求时请求体中的数据
callback: 请求完成后的回调函数
timeout: 请求的超时时间
"""
self.sock = sock
self.callback = callback
self.host = host
self.port = port
self.method = method
self.url = url
self.data = data
self.timeout = timeout
self.__start_time = time.time()
self.__buffer = []
def is_timeout(self):
"""当前请求是否已经超时"""
current_time = time.time()
if (self.__start_time + self.timeout) < current_time:
return True
def fileno(self):
"""请求sockect对象的文件描述符，用于select监听"""
return self.sock.fileno()
def write(self, data):
"""在buffer中写入响应内容"""
self.__buffer.append(data)
def finish(self, exc=None):
"""在buffer中写入响应内容完成，执行请求的回调函数"""
if not exc:
response = b''.join(self.__buffer)
self.callback(self, response, exc)
else:
self.callback(self, None, exc)
def send_request_data(self):
content = """%s %s HTTP/1.0\r\nHost: %s\r\n\r\n%s""" % (
self.method.upper(), self.url, self.host, self.data,)
return content.encode(encoding='utf8')
class AsyncRequest(object):
def __init__(self):
self.fds = []
self.connections = []
def add_request(self, host, port, method, url, data, callback, timeout):
"""创建一个要请求"""
client = socket.socket()
client.setblocking(False)
try:
client.connect((host, port))
except BlockingIOError as e:
pass
# print('已经向远程发送连接的请求')
req = HttpContext(client, host, port, method, url, data, callback, timeout)
self.connections.append(req)
self.fds.append(req)
def check_conn_timeout(self):
"""检查所有的请求，是否有已经连接超时，如果有则终止"""
timeout_list = []
for context in self.connections:
if context.is_timeout():
timeout_list.append(context)
for context in timeout_list:
context.finish(AsyncTimeoutException('请求超时'))
self.fds.remove(context)
self.connections.remove(context)
def running(self):
"""事件循环，用于检测请求的socket是否已经就绪，从而执行相关操作"""
while True:
r, w, e = select.select(self.fds, self.connections, self.fds, 0.05)
if not self.fds:
return
for context in r:
sock = context.sock
while True:
try:
data = sock.recv(8096)
if not data:
self.fds.remove(context)
context.finish()
break
else:
context.write(data)
except BlockingIOError as e:
break
except TimeoutError as e:
self.fds.remove(context)
self.connections.remove(context)
context.finish(e)
break
for context in w:
# 已经连接成功远程服务器，开始向远程发送请求数据
if context in self.fds:
data = context.send_request_data()
context.sock.sendall(data)
self.connections.remove(context)
self.check_conn_timeout()
if __name__ == '__main__':
def callback_func(context, response, ex):
"""
:param context: HttpContext对象，内部封装了请求相关信息
:param response: 请求响应内容
:param ex: 是否出现异常（如果有异常则值为异常对象；否则值为None）
:return:
"""
print(context, response, ex)
obj = AsyncRequest()
url_list = [
{'host': 'www.google.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
'callback': callback_func},
{'host': 'www.baidu.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
'callback': callback_func},
{'host': 'www.bing.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
'callback': callback_func},
]
for item in url_list:
print(item)
obj.add_request(**item)
obj.running()
Scrapy
Scrapy是一个为了爬取网站数据，提取结构性数据而编写的应用框架。 其可以应用在数据挖掘，信息处理或存储历史数据等一系列的程序中。
其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的， 也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。Scrapy用途广泛，可以用于数据挖掘、监测和自动化测试。
Scrapy 使用了 Twisted异步网络库来处理网络通讯。整体架构大致如下:
Scrapy主要包括了以下组件:
-
引擎(Scrapy)
用来处理整个系统的数据流处理, 触发事务(框架核心) -
调度器(Scheduler)
用来接受引擎发过来的请求, 压入队列中, 并在引擎再次请求的时候返回. 可以想像成一个URL（抓取网页的网址或者说是链接）的优先队列, 由它来决定下一个要抓取的网址是什么, 同时去除重复的网址 -
下载器(Downloader)
用于下载网页内容, 并将网页内容返回给蜘蛛(Scrapy下载器是建立在twisted这个高效的异步模型上的) -
爬虫(Spiders)
爬虫是主要干活的, 用于从特定的网页中提取自己需要的信息, 即所谓的实体(Item)。用户也可以从中提取出链接,让Scrapy继续抓取下一个页面 -
项目管道(Pipeline)
负责处理爬虫从网页中抽取的实体，主要的功能是持久化实体、验证实体的有效性、清除不需要的信息。当页面被爬虫解析后，将被发送到项目管道，并经过几个特定的次序处理数据。 -
下载器中间件(Downloader Middlewares)
位于Scrapy引擎和下载器之间的框架，主要是处理Scrapy引擎与下载器之间的请求及响应。 -
爬虫中间件(Spider Middlewares)
介于Scrapy引擎和爬虫之间的框架，主要工作是处理蜘蛛的响应输入和请求输出。 -
调度中间件(Scheduler Middewares)
介于Scrapy引擎和调度之间的中间件，从Scrapy引擎发送到调度的请求和响应。
Scrapy运行流程大概如下：
- 引擎从调度器中取出一个链接(URL)用于接下来的抓取
- 引擎把URL封装成一个请求(Request)传给下载器
- 下载器把资源下载下来，并封装成应答包(Response)
- 爬虫解析Response
- 解析出实体（Item）,则交给实体管道进行进一步的处理
- 解析出的是链接（URL）,则把URL交给调度器等待抓取
安装
Linux
pip3 install scrapy
Windows
a. pip3 install wheel
b. 下载twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
c. 进入下载目录，执行 pip3 install Twisted‑17.1.0‑cp35‑cp35m‑win_amd64.whl
d. pip3 install scrapy
e. 下载并安装pywin32：https://sourceforge.net/projects/pywin32/files/
基本使用
基本命令
1. scrapy startproject 项目名称
- 在当前目录中创建中创建一个项目文件（类似于Django）
2. scrapy genspider [-t template] <name> <domain>
- 创建爬虫应用
如：
scrapy gensipider -t basic oldboy oldboy.com
scrapy gensipider -t xmlfeed autohome autohome.com.cn
PS:
查看所有命令：scrapy gensipider -l
查看模板命令：scrapy gensipider -d 模板名称
3. scrapy list
- 展示爬虫应用列表
4. scrapy crawl 爬虫应用名称
- 运行单独爬虫应用
项目结构以及爬虫应用简介
project_name/
scrapy.cfg
project_name/
__init__.py
items.py
pipelines.py
settings.py
spiders/
__init__.py
爬虫1.py
爬虫2.py
爬虫3.py
文件说明：
scrapy.cfg 项目的主配置信息。（真正爬虫相关的配置信息在settings.py文件中）
items.py 设置数据存储模板，用于结构化数据，如：Django的Model
pipelines 数据处理行为，如：一般结构化的数据持久化
settings.py 配置文件，如：递归的层数、并发数，延迟下载等
spiders 爬虫目录，如：创建文件，编写爬虫规则
注意：一般创建爬虫文件时，以网站域名命名
示例:
import scrapy
class XiaoHuarSpider(scrapy.spiders.Spider):
name = "xiaohuar" # 爬虫名称 *****
allowed_domains = ["xiaohuar.com"] # 允许的域名
start_urls = [
"http://www.xiaohuar.com/hua/", # 其实URL
]
def parse(self, response):
# 访问起始URL并获取结果后的回调函数
小试牛刀
import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
class DigSpider(scrapy.Spider):
# 爬虫应用的名称，通过此名称启动爬虫命令
name = "dig"
# 允许的域名
allowed_domains = ["chouti.com"]
# 起始URL
start_urls = [
'http://dig.chouti.com/',
]
has_request_set = {}
def parse(self, response):
print(response.url)
hxs = HtmlXPathSelector(response)
page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()
for page in page_list:
page_url = 'http://dig.chouti.com%s' % page
key = self.md5(page_url)
if key in self.has_request_set:
pass
else:
self.has_request_set[key] = page_url
obj = Request(url=page_url, method='GET', callback=self.parse)
yield obj
@staticmethod
def md5(val):
import hashlib
ha = hashlib.md5()
ha.update(bytes(val, encoding='utf-8'))
key = ha.hexdigest()
return key
执行此爬虫文件，则在终端进入项目目录执行如下命令：
scrapy crawl dig --nolog
对于上述代码重要之处在于：
- Request是一个封装用户请求的类，在回调函数中yield该对象表示继续访问
- HtmlXpathSelector用于结构化HTML代码并提供选择器功能
选择器
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from scrapy.selector import Selector, HtmlXPathSelector
from scrapy.http import HtmlResponse
html = """<!DOCTYPE html>
<html>
<head lang="en">
<title></title>
</head>
<body>
<ul>
<li class="item-"><a id='i1' href="link.html">first item</a></li>
<li class="item-0"><a id='i2' href="llink.html">first item</a></li>
<li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li>
</ul>
<div><a href="llink2.html">second item</a></div>
</body>
</html>
"""
response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8')
# hxs = HtmlXPathSelector(response)
# print(hxs)
# hxs = Selector(response=response).xpath('//a')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[2]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id="i1"]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[contains(@href, "link")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first()
# print(hxs)
# ul_list = Selector(response=response).xpath('//body/ul/li')
# for item in ul_list:
# v = item.xpath('./a/span')
# # 或
# # v = item.xpath('a/span')
# # 或
# # v = item.xpath('*/a/span')
# print(v)
示例：自动登陆抽屉并点赞
# -*- coding: utf-8 -*-
import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequest
class ChouTiSpider(scrapy.Spider):
# 爬虫应用的名称，通过此名称启动爬虫命令
name = "chouti"
# 允许的域名
allowed_domains = ["chouti.com"]
cookie_dict = {}
has_request_set = {}
def start_requests(self):
url = 'http://dig.chouti.com/'
# return [Request(url=url, callback=self.login)]
yield Request(url=url, callback=self.login)
def login(self, response):
cookie_jar = CookieJar()
cookie_jar.extract_cookies(response, response.request)
for k, v in cookie_jar._cookies.items():
for i, j in v.items():
for m, n in j.items():
self.cookie_dict[m] = n.value
req = Request(
url='http://dig.chouti.com/login',
method='POST',
headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},
body='phone=86your_phone&password=your_pwd&oneMonth=1',
cookies=self.cookie_dict,
callback=self.check_login
)
yield req
def check_login(self, response):
req = Request(
url='http://dig.chouti.com/',
method='GET',
callback=self.show,
cookies=self.cookie_dict,
dont_filter=True
)
yield req
def show(self, response):
# print(response)
hxs = HtmlXPathSelector(response)
news_list = hxs.select('//div[@id="content-list"]/div[@class="item"]')
for new in news_list:
# temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract()
link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first()
yield Request(
url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,),
method='POST',
cookies=self.cookie_dict,
callback=self.do_favor
)
page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()
for page in page_list:
page_url = 'http://dig.chouti.com%s' % page
import hashlib
hash = hashlib.md5()
hash.update(bytes(page_url,encoding='utf-8'))
key = hash.hexdigest()
if key in self.has_request_set:
pass
else:
self.has_request_set[key] = page_url
yield Request(
url=page_url,
method='GET',
callback=self.show
)
def do_favor(self, response):
print(response.text)
注意：settings.py中设置DEPTH_LIMIT = 1来指定“递归”的层数。
格式化处理
上述实例只是简单的处理，所以在parse方法中直接处理。如果对于想要获取更多的数据处理，则可以利用Scrapy的items将数据格式化，然后统一交由pipelines来处理。
spiders/xiahuar.py代码:
import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequest
class XiaoHuarSpider(scrapy.Spider):
# 爬虫应用的名称，通过此名称启动爬虫命令
name = "xiaohuar"
# 允许的域名
allowed_domains = ["xiaohuar.com"]
start_urls = [
"http://www.xiaohuar.com/list-1-1.html",
]
# custom_settings = {
# 'ITEM_PIPELINES':{
# 'spider1.pipelines.JsonPipeline': 100
# }
# }
has_request_set = {}
def parse(self, response):
# 分析页面
# 找到页面中符合规则的内容（校花图片），保存
# 找到所有的a标签，再访问其他a标签，一层一层的搞下去
hxs = HtmlXPathSelector(response)
items = hxs.select('//div[@class="item_list infinite_scroll"]/div')
for item in items:
src = item.select('.//div[@class="img"]/a/img/@src').extract_first()
name = item.select('.//div[@class="img"]/span/text()').extract_first()
school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()
url = "http://www.xiaohuar.com%s" % src
from ..items import XiaoHuarItem
obj = XiaoHuarItem(name=name, school=school, url=url)
yield obj
urls = hxs.select('//a[re:test(@href, "http://www.xiaohuar.com/list-1-\d+.html")]/@href')
for url in urls:
key = self.md5(url)
if key in self.has_request_set:
pass
else:
self.has_request_set[key] = url
req = Request(url=url,method='GET',callback=self.parse)
yield req
@staticmethod
def md5(val):
import hashlib
ha = hashlib.md5()
ha.update(bytes(val, encoding='utf-8'))
key = ha.hexdigest()
return key
items代码:
import scrapy
class XiaoHuarItem(scrapy.Item):
name = scrapy.Field()
school = scrapy.Field()
url = scrapy.Field()
pipelines代码
import json
import os
import requests
class JsonPipeline(object):
def __init__(self):
self.file = open('xiaohua.txt', 'w')
def process_item(self, item, spider):
v = json.dumps(dict(item), ensure_ascii=False)
self.file.write(v)
self.file.write('\n')
self.file.flush()
return item
class FilePipeline(object):
def __init__(self):
if not os.path.exists('imgs'):
os.makedirs('imgs')
def process_item(self, item, spider):
response = requests.get(item['url'], stream=True)
file_name = '%s_%s.jpg' % (item['name'], item['school'])
with open(os.path.join('imgs', file_name), mode='wb') as f:
f.write(response.content)
return item
settings代码:
ITEM_PIPELINES = {
'spider1.pipelines.JsonPipeline': 100,
'spider1.pipelines.FilePipeline': 300,
}
# 每行后面的整型值，确定了他们运行的顺序，item按数字从低到高的顺序，通过pipeline，通常将这些数字定义在0-1000范围内。
piplines可以做更多,自定义pipline扩展:
from scrapy.exceptions import DropItem
class CustomPipeline(object):
def __init__(self,v):
self.value = v
def process_item(self, item, spider):
# 操作并进行持久化
# return表示会被后续的pipeline继续处理
return item
# 表示将item丢弃，不会被后续pipeline处理
# raise DropItem()
@classmethod
def from_crawler(cls, crawler):
"""
初始化时候，用于创建pipeline对象
:param crawler:
:return:
"""
val = crawler.settings.getint('MMMM')
return cls(val)
def open_spider(self,spider):
"""
爬虫开始执行时，调用
:param spider:
:return:
"""
print('000000')
def close_spider(self,spider):
"""
爬虫关闭时，被调用
:param spider:
:return:
"""
print('111111')
中间件
爬虫中间件:
class SpiderMiddleware(object):
def process_spider_input(self,response, spider):
"""
下载完成，执行，然后交给parse处理
:param response:
:param spider:
:return:
"""
pass
def process_spider_output(self,response, result, spider):
"""
spider处理完成，返回时调用
:param response:
:param result:
:param spider:
:return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
"""
return result
def process_spider_exception(self,response, exception, spider):
"""
异常调用
:param response:
:param exception:
:param spider:
:return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
"""
return None
def process_start_requests(self,start_requests, spider):
"""
爬虫启动时调用
:param start_requests:
:param spider:
:return: 包含 Request 对象的可迭代对象
"""
return start_requests
下载器中间件:
class DownMiddleware1(object):
def process_request(self, request, spider):
"""
请求需要被下载时，经过所有下载器中间件的process_request调用
:param request:
:param spider:
:return:
None,继续后续中间件去下载；
Response对象，停止process_request的执行，开始执行process_response
Request对象，停止中间件的执行，将Request重新调度器
raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
"""
pass
def process_response(self, request, response, spider):
"""
spider处理完成，返回时调用
:param response:
:param result:
:param spider:
:return:
Response 对象：转交给其他中间件process_response
Request 对象：停止中间件，request会被重新调度下载
raise IgnoreRequest 异常：调用Request.errback
"""
print('response1')
return response
def process_exception(self, request, exception, spider):
"""
当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
:param response:
:param exception:
:param spider:
:return:
None：继续交给后续中间件处理异常；
Response对象：停止后续process_exception方法
Request对象：停止中间件，request将会被重新调用下载
"""
return None
自定制命令
- 在spiders同级创建目录:
commands - 在其中创建 crawlall.py 文件 （此处文件名就是自定义的命令）
- 在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
- 在项目目录执行命令：
scrapy crawlall --nolog
crawlall.py:
from scrapy.commands import ScrapyCommand
from scrapy.utils.project import get_project_settings
class Command(ScrapyCommand):
requires_project = True
def syntax(self):
return '[options]'
def short_desc(self):
return 'Runs all of the spiders'
def run(self, args, opts):
spider_list = self.crawler_process.spiders.list()
for name in spider_list:
self.crawler_process.crawl(name, **opts.__dict__)
self.crawler_process.start()
利用信号自定义扩展
自定义扩展时，利用信号在指定位置注册制定操作
from scrapy import signals
class MyExtension(object):
def __init__(self, value):
self.value = value
@classmethod
def from_crawler(cls, crawler):
val = crawler.settings.getint('MMMM')
ext = cls(val)
crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)
crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)
return ext
def spider_opened(self, spider):
print('open')
def spider_closed(self, spider):
print('close')
避免重复访问
scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重，相关配置有：
DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'
DUPEFILTER_DEBUG = False
JOBDIR = "保存范文记录的日志路径，如：/root/" # 最终路径为 /root/requests.seen
也可以通过自定义URL去重操作:
class RepeatUrl:
def __init__(self):
self.visited_url = set()
@classmethod
def from_settings(cls, settings):
"""
初始化时，调用
:param settings:
:return:
"""
return cls()
def request_seen(self, request):
"""
检测当前请求是否已经被访问过
:param request:
:return: True表示已经访问过；False表示未访问过
"""
if request.url in self.visited_url:
return True
self.visited_url.add(request.url)
return False
def open(self):
"""
开始爬去请求时，调用
:return:
"""
print('open replication')
def close(self, reason):
"""
结束爬虫爬取时，调用
:param reason:
:return:
"""
print('close replication')
def log(self, request, spider):
"""
记录日志
:param request:
:param spider:
:return:
"""
print('repeat', request.url)
settings设置解释
# -*- coding: utf-8 -*-
# Scrapy settings for step8_king project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
# http://doc.scrapy.org/en/latest/topics/settings.html
# http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
# 1. 爬虫名称
BOT_NAME = 'step8_king'
# 2. 爬虫应用路径
SPIDER_MODULES = ['step8_king.spiders']
NEWSPIDER_MODULE = 'step8_king.spiders'
# Crawl responsibly by identifying yourself (and your website) on the user-agent
# 3. 客户端 user-agent请求头
# USER_AGENT = 'step8_king (+http://www.yourdomain.com)'
# Obey robots.txt rules
# 4. 禁止爬虫配置
# ROBOTSTXT_OBEY = False
# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 5. 并发请求数
# CONCURRENT_REQUESTS = 4
# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# 6. 延迟下载秒数
# DOWNLOAD_DELAY = 2
# The download delay setting will honor only one of:
# 7. 单域名访问并发数，并且延迟下次秒数也应用在每个域名
# CONCURRENT_REQUESTS_PER_DOMAIN = 2
# 单IP访问并发数，如果有值则忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延迟下次秒数也应用在每个IP
# CONCURRENT_REQUESTS_PER_IP = 3
# Disable cookies (enabled by default)
# 8. 是否支持cookie，cookiejar进行操作cookie
# COOKIES_ENABLED = True
# COOKIES_DEBUG = True
# Disable Telnet Console (enabled by default)
# 9. Telnet用于查看当前爬虫的信息，操作爬虫等...
# 使用telnet ip port ，然后通过命令操作
# TELNETCONSOLE_ENABLED = True
# TELNETCONSOLE_HOST = '127.0.0.1'
# TELNETCONSOLE_PORT = [6023,]
# 10. 默认请求头
# Override the default request headers:
# DEFAULT_REQUEST_HEADERS = {
# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
# 'Accept-Language': 'en',
# }
# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
# 11. 定义pipeline处理请求
# ITEM_PIPELINES = {
# 'step8_king.pipelines.JsonPipeline': 700,
# 'step8_king.pipelines.FilePipeline': 500,
# }
# 12. 自定义扩展，基于信号进行调用
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
# EXTENSIONS = {
# # 'step8_king.extensions.MyExtension': 500,
# }
# 13. 爬虫允许的最大深度，可以通过meta查看当前深度；0表示无深度
# DEPTH_LIMIT = 3
# 14. 爬取时，0表示深度优先Lifo(默认)；1表示广度优先FiFo
# 后进先出，深度优先
# DEPTH_PRIORITY = 0
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
# 先进先出，广度优先
# DEPTH_PRIORITY = 1
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'
# 15. 调度器队列
# SCHEDULER = 'scrapy.core.scheduler.Scheduler'
# from scrapy.core.scheduler import Scheduler
# 16. 访问URL去重
# DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'
# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html
"""
17. 自动限速算法
from scrapy.contrib.throttle import AutoThrottle
自动限速设置
1. 获取最小延迟 DOWNLOAD_DELAY
2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY
3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY
4. 当请求下载完成后，获取其"连接"时间 latency，即：请求连接到接受到响应头之间的时间
5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCY
target_delay = latency / self.target_concurrency
new_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间
new_delay = max(target_delay, new_delay)
new_delay = min(max(self.mindelay, new_delay), self.maxdelay)
slot.delay = new_delay
"""
# 开始自动限速
# AUTOTHROTTLE_ENABLED = True
# The initial download delay
# 初始下载延迟
# AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
# 最大下载延迟
# AUTOTHROTTLE_MAX_DELAY = 10
# The average number of requests Scrapy should be sending in parallel to each remote server
# 平均每秒并发数
# AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
# 是否显示
# AUTOTHROTTLE_DEBUG = True
# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
"""
18. 启用缓存
目的用于将已经发送的请求或相应缓存下来，以便以后使用
from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddleware
from scrapy.extensions.httpcache import DummyPolicy
from scrapy.extensions.httpcache import FilesystemCacheStorage
"""
# 是否启用缓存策略
# HTTPCACHE_ENABLED = True
# 缓存策略：所有请求均缓存，下次在请求直接访问原来的缓存即可
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
# 缓存策略：根据Http响应头：Cache-Control、Last-Modified 等进行缓存的策略
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"
# 缓存超时时间
# HTTPCACHE_EXPIRATION_SECS = 0
# 缓存保存路径
# HTTPCACHE_DIR = 'httpcache'
# 缓存忽略的Http状态码
# HTTPCACHE_IGNORE_HTTP_CODES = []
# 缓存存储的插件
# HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
"""
19. 代理，需要在环境变量中设置
from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware
方式一：使用默认
os.environ
{
http_proxy:http://root:woshiniba@192.168.11.11:9999/
https_proxy:http://192.168.11.11:9999/
}
方式二：使用自定义下载中间件
def to_bytes(text, encoding=None, errors='strict'):
if isinstance(text, bytes):
return text
if not isinstance(text, six.string_types):
raise TypeError('to_bytes must receive a unicode, str or bytes '
'object, got %s' % type(text).__name__)
if encoding is None:
encoding = 'utf-8'
return text.encode(encoding, errors)
class ProxyMiddleware(object):
def process_request(self, request, spider):
PROXIES = [
{'ip_port': '111.11.228.75:80', 'user_pass': ''},
{'ip_port': '120.198.243.22:80', 'user_pass': ''},
{'ip_port': '111.8.60.9:8123', 'user_pass': ''},
{'ip_port': '101.71.27.120:80', 'user_pass': ''},
{'ip_port': '122.96.59.104:80', 'user_pass': ''},
{'ip_port': '122.224.249.122:8088', 'user_pass': ''},
]
proxy = random.choice(PROXIES)
if proxy['user_pass'] is not None:
request.meta['proxy'] = to_bytes（"http://%s" % proxy['ip_port']）
encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))
request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)
print "**************ProxyMiddleware have pass************" + proxy['ip_port']
else:
print "**************ProxyMiddleware no pass************" + proxy['ip_port']
request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
DOWNLOADER_MIDDLEWARES = {
'step8_king.middlewares.ProxyMiddleware': 500,
}
"""
"""
20. Https访问
Https访问时有两种情况：
1. 要爬取网站使用的可信任证书(默认支持)
DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"
2. 要爬取网站使用的自定义证书
DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"
# https.py
from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory
from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)
class MySSLFactory(ScrapyClientContextFactory):
def getCertificateOptions(self):
from OpenSSL import crypto
v1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read())
v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read())
return CertificateOptions(
privateKey=v1, # pKey对象
certificate=v2, # X509对象
verify=False,
method=getattr(self, 'method', getattr(self, '_ssl_method', None))
)
其他：
相关类
scrapy.core.downloader.handlers.http.HttpDownloadHandler
scrapy.core.downloader.webclient.ScrapyHTTPClientFactory
scrapy.core.downloader.contextfactory.ScrapyClientContextFactory
相关配置
DOWNLOADER_HTTPCLIENTFACTORY
DOWNLOADER_CLIENTCONTEXTFACTORY
"""
"""
21. 爬虫中间件
class SpiderMiddleware(object):
def process_spider_input(self,response, spider):
'''
下载完成，执行，然后交给parse处理
:param response:
:param spider:
:return:
'''
pass
def process_spider_output(self,response, result, spider):
'''
spider处理完成，返回时调用
:param response:
:param result:
:param spider:
:return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
'''
return result
def process_spider_exception(self,response, exception, spider):
'''
异常调用
:param response:
:param exception:
:param spider:
:return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
'''
return None
def process_start_requests(self,start_requests, spider):
'''
爬虫启动时调用
:param start_requests:
:param spider:
:return: 包含 Request 对象的可迭代对象
'''
return start_requests
内置爬虫中间件：
'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,
'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,
'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,
'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,
'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,
"""
# from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {
# 'step8_king.middlewares.SpiderMiddleware': 543,
}
"""
22. 下载中间件
class DownMiddleware1(object):
def process_request(self, request, spider):
'''
请求需要被下载时，经过所有下载器中间件的process_request调用
:param request:
:param spider:
:return:
None,继续后续中间件去下载；
Response对象，停止process_request的执行，开始执行process_response
Request对象，停止中间件的执行，将Request重新调度器
raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
'''
pass
def process_response(self, request, response, spider):
'''
spider处理完成，返回时调用
:param response:
:param result:
:param spider:
:return:
Response 对象：转交给其他中间件process_response
Request 对象：停止中间件，request会被重新调度下载
raise IgnoreRequest 异常：调用Request.errback
'''
print('response1')
return response
def process_exception(self, request, exception, spider):
'''
当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
:param response:
:param exception:
:param spider:
:return:
None：继续交给后续中间件处理异常；
Response对象：停止后续process_exception方法
Request对象：停止中间件，request将会被重新调用下载
'''
return None
默认下载中间件
{
'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,
'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,
'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,
'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,
'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,
'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,
'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,
'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,
'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,
'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,
'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,
'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,
'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,
'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,
}
"""
# from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# DOWNLOADER_MIDDLEWARES = {
# 'step8_king.middlewares.DownMiddleware1': 100,
# 'step8_king.middlewares.DownMiddleware2': 500,
# }
出自银角wusir的精简scrapy
tinyscrapy.py参考版:
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import types
from twisted.internet import defer
from twisted.web.client import getPage
from twisted.internet import reactor
class Request(object):
def __init__(self, url, callback):
self.url = url
self.callback = callback
self.priority = 0
class HttpResponse(object):
def __init__(self, content, request):
self.content = content
self.request = request
class ChouTiSpider(object):
def start_requests(self):
url_list = ['http://www.cnblogs.com/', 'http://www.bing.com']
for url in url_list:
yield Request(url=url, callback=self.parse)
def parse(self, response):
print(response.request.url)
# yield Request(url="http://www.baidu.com", callback=self.parse)
from queue import Queue
Q = Queue()
class CallLaterOnce(object):
def __init__(self, func, *a, **kw):
self._func = func
self._a = a
self._kw = kw
self._call = None
def schedule(self, delay=0):
if self._call is None:
self._call = reactor.callLater(delay, self)
def cancel(self):
if self._call:
self._call.cancel()
def __call__(self):
self._call = None
return self._func(*self._a, **self._kw)
class Engine(object):
def __init__(self):
self.nextcall = None
self.crawlling = []
self.max = 5
self._closewait = None
def get_response(self,content, request):
response = HttpResponse(content, request)
gen = request.callback(response)
if isinstance(gen, types.GeneratorType):
for req in gen:
req.priority = request.priority + 1
Q.put(req)
def rm_crawlling(self,response,d):
self.crawlling.remove(d)
def _next_request(self,spider):
if Q.qsize() == 0 and len(self.crawlling) == 0:
self._closewait.callback(None)
if len(self.crawlling) >= 5:
return
while len(self.crawlling) < 5:
try:
req = Q.get(block=False)
except Exception as e:
req = None
if not req:
return
d = getPage(req.url.encode('utf-8'))
self.crawlling.append(d)
d.addCallback(self.get_response, req)
d.addCallback(self.rm_crawlling,d)
d.addCallback(lambda _: self.nextcall.schedule())
@defer.inlineCallbacks
def crawl(self):
spider = ChouTiSpider()
start_requests = iter(spider.start_requests())
flag = True
while flag:
try:
req = next(start_requests)
Q.put(req)
except StopIteration as e:
flag = False
self.nextcall = CallLaterOnce(self._next_request,spider)
self.nextcall.schedule()
self._closewait = defer.Deferred()
yield self._closewait
@defer.inlineCallbacks
def pp(self):
yield self.crawl()
_active = set()
obj = Engine()
d = obj.crawl()
_active.add(d)
li = defer.DeferredList(_active)
li.addBoth(lambda _,*a,**kw: reactor.stop())
reactor.run()
