Python爬虫框架Scrapy

性能相关

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。

那么如何编写出高效的程序。

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)
1.同步执行
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)
2.多线程执行
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)
2.多线程+回调函数执行
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)
3.多进程执行
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)
3.多进程+回调函数执行

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：

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()
1.asyncio示例1
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()
1.asyncio示例2
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()
2.asyncio + aiohttp
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()
3.asyncio + 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={}),
# ])
4.gevent + requests
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)
5.grequests
from twisted.web.client import getPage
from twisted.internet import reactor

REV_COUNTER = 0
REQ_COUNTER = 0

def callback(contents):
    print(contents,)

    global REV_COUNTER
    REV_COUNTER += 1
    if REV_COUNTER == REQ_COUNTER:
        reactor.stop()


url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
REQ_COUNTER = len(url_list)
for url in url_list:
    deferred = getPage(bytes(url, encoding='utf8'))
    deferred.addCallback(callback)
reactor.run()
6.twisted示例1
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from twisted.internet import defer
from twisted.web.client import getPage
from twisted.internet import reactor


@defer.inlineCallbacks
def task(url):
    url = url
    while url:
        ret = getPage(bytes(url, encoding='utf8'))
        ret.addCallback(one_done)
        url = yield ret


i = 0


def one_done(arg):
    global i
    i += 1
    if i == 10:
        return
    print('one', arg)
    return 'http://www.cnblogs.com'


@defer.inlineCallbacks
def task_list():
    start_url_list = [
        'http://www.cnblogs.com',
    ]
    defer_list = []
    for url in start_url_list:
        deferObj = task(url)
        defer_list.append(deferObj)
    yield defer.DeferredList(defer_list)


def all_done(arg):
    print('done', arg)
    reactor.stop()


if __name__ == '__main__':
    d = task_list()
    print(type(d))
    d.addBoth(all_done)
    reactor.run()
6.twisted示例2
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from tornado.httpclient import AsyncHTTPClient
from tornado.httpclient import HTTPRequest
from tornado import ioloop


def handle_response(response):
    if response.error:
        print("Error:", response.error)
    else:
        print(response.body)
        # 方法同twisted
        # ioloop.IOLoop.current().stop()


def func():
    url_list = [
        'http://www.google.com',
        'http://127.0.0.1:8000/test2/',
    ]
    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()
7.tornado示例

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】：

import select
import socket


class HttpRequest(object):
    def __init__(self, sk, host, callback):
        self.sk = sk
        self.host = host
        self.callback = callback

    def fileno(self):
        return self.sk.fileno()


class AsyncRequest(object):
    def __init__(self):
        self.conn = []
        self.connection = []

    def add_request(self, host, callback):
        try:
            sk = socket.socket()
            sk.setblocking(False)
            sk.connect((host, 80, ))

        except BlockingIOError as e:
            pass

        request = HttpRequest(sk, host, callback)
        self.conn.append(request)
        self.connection.append(request)

    def running(self):
        while True:
            # select并不仅仅只能监听socket套接字对象
            #   再自定义对象中实现fileno()方法, 并返回socket文件描述符对象即可 return socket_obj.fileno()
            r_list, w_list, e_list = select.select(self.conn, self.connection, self.conn, 0.05)
            for w in w_list:
                # w_list 表示连接上的请求
                http_msg = "GET / HTTP/1.0\r\nHost:%s\r\n\r\n" % (w.host,)
                w.sk.send(bytes(http_msg, encoding='utf-8'))
                self.connection.remove(w)
            for r in r_list:
                # r_list 表示有数据返回
                data = bytes()
                while True:
                    try:
                        recv = r.sk.recv(8096)
                        data += recv
                    except Exception as e:
                        break
                r.callback(data)
                r.sk.close()
                self.conn.remove(r)
            if len(self.conn) == 0:
                break


def func1(data):
    print(data)


def func2(data):
    print(data)

url_list = [
    {'host': 'www.baidu.com', 'callback': func1},
    {'host': 'www.cnblogs.com', 'callback': func2},
    {'host': 'www.huaban.com', 'callback': func2},
]

async_obj = AsyncRequest()
for item in url_list:
    async_obj.add_request(item['host'], item['callback'])

async_obj.running()
NB异步框架版本1.1

Scrapy介绍及安装

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：

  1. 引擎从调度器中取出一个链接(URL)用于接下来的抓取
  2. 引擎把URL封装成一个请求(Request)传给下载器
  3. 下载器把资源下载下来，并封装成应答包(Response)
  4. 爬虫解析Response
  5. 解析出实体（Item）,则交给实体管道进行进一步的处理
  6. 解析出的是链接（URL）,则把URL交给调度器等待抓取

Scrapy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/

Scrapy命令及项目结构

1，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

2，项目结构以及应用简介

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

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
爬虫1.py

Scrapy初体验

编写 Spider/spider_name.py 文件

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
DEMO

执行此文件需

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">
        <meta charset="UTF-8">
        <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)
HTML选择器解析

示例

# -*- 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=8615131255089&password=pppppppp&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)
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注意：settings.py中设置DEPTH_LIMIT = 1来指定"递归"的层数。

Scrapy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。接下来演示一个下载校花网图片的DEMO。

# -*- coding: utf-8 -*-
import scrapy
import sys
import io
from xiaohua.items import XiaohuaItem
from scrapy.selector import Selector, HtmlXPathSelector
from scrapy.http.request import Request

sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='gb18030')


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/hua/']
    visited_urls = 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
        hxs1 = Selector(response=response).xpath('//div[@id="list_img"]')  # 标签对象列表
        for obj in hxs1:
            img_list = obj.xpath('.//div[@class="img"]')
            for img in img_list:
                img_url = img.xpath('.//a/img/@src').extract_first().strip()
                img_title = img.xpath('.//span[@class="price"]/text()').extract_first().strip()
                img_obj = XiaohuaItem(title=img_title, href=img_url)
                yield img_obj

        hxs = Selector(response=response).xpath(
            '//a[re:test(@href, "http://www.xiaohuar.com/list-1-\d+.html")]/@href'
        ).extract()
        for url in hxs:
            md5_url = self.encrypt(url)
            if md5_url not in self.visited_urls:
                self.visited_urls.add(md5_url)
                yield Request(url=url, callback=self.parse)

    def encrypt(self, url):
        import hashlib
        hash_obj = hashlib.md5()
        hash_obj.update(bytes(url, encoding='utf-8'))
        return hash_obj.hexdigest()
spiders/xiaohuar.py
import scrapy


class XiaohuaItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    title = scrapy.Field()
    href = scrapy.Field()
items
from scrapy.contrib.pipeline.images import ImagesPipeline
from scrapy.exceptions import DropItem
from scrapy.http.request import Request


class XiaohuaPipeline(ImagesPipeline):
    """
    Scrapy 封装了 ImagesPipeline 的管道, 辣么只需要继承一下它, 并重写了俩个方法(名字不可随意修改)
    
    如果你不想使用它, 打开注释掉的内容即可
    """

    # def process_item(self, item, spider):
    #     img_url = 'http://www.xiaohuar.com{}'.format(item['href'])
    #     print(img_url)
    #     img_name = '{}.jpg'.format(item['title'])
    #     response = requests.get(url=img_url)
    #     with open(os.path.join('image', img_name), 'wb') as f:
    #         f.write(response.content)
    #     # return item


    def get_media_requests(self, item, info):
        img_url = 'http://www.xiaohuar.com{}'.format(item['href'])
        yield Request(img_url)

    def item_completed(self, results, item, info):
        # print(results)
        image_paths = [x['path'] for ok, x in results if ok]
        if not image_paths:
            raise DropItem("Item contains no images")
        item['image_paths'] = image_paths
        return item
pipelines
ITEM_PIPELINES = {
   'xiaohua.pipelines.XiaohuaPipeline': 300,
   'scrapy.contrib.pipeline.images.ImagesPipeline': 1
}


# 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。

# 递归深度
DEPTH_LIMIT = 1
# 项目图片下载路径  
IMAGES_STORE = 'F:\\python\\spiderTest\\xiaohua\\image'
settings

对于pipeline可以做更多，如下：

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')
自定义pipeline

Scrapy中间件

爬虫中间件

爬虫中间件是介入到Scrapy的spider处理机制的钩子框架，您可以添加代码来处理发送给 Spiders 的response及spider产生的item和 request。

激活爬虫中间件

要启用 spider中间件，您可以将其加入到 SPIDER_MIDDLEWARES 设置中。 该设置是一个字典，键为中间件的路径，值为中间件的顺序(order)。

# 在 settings 文件中配置如下，如果值为None即为不启用

SPIDER_MIDDLEWARES = {
    'myproject.middlewares.CustomSpiderMiddleware': 543,
    'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': None,
}

编写自己的爬虫中间件

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

爬虫中间件
爬虫中间件

 

下载中间件

下载器中间件是介于Scrapy的request/response处理的钩子框架。 是用于全局修改Scrapy request和response的一个轻量、底层的系统。

激活下载中间件

要激活下载器中间件组件，将其加入到 DOWNLOADER_MIDDLEWARES 设置中。 该设置是一个字典(dict)，键为中间件类的路径，值为其中间件的顺序(order)。

# 在 settings 文件中配置， 值为None即为不启用

DOWNLOADER_MIDDLEWARES = {
    'myproject.middlewares.CustomDownloaderMiddleware': 543,
    'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': None,
}

编写自己的下载中间件

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
下载中间件

Scrapy自定制命令

  • 在spiders同级创建任意目录，如：commands
  • 在其中创建 crawlall.py 文件 （此处文件名就是自定义的命令）
    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()
crawlall.py
  • 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

Scrapy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
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)
自定义Url去重操作

Scrapy中Settings

# -*- 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,
# }
settings

Scrapy自定义扩展

Scrapy使用信号来通知事情发生。您可以在您的Scrapy项目中捕捉一些信号(使用 extension)来完成额外的工作或添加额外的功能，扩展Scrapy。

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')
View Code

更多信号API   http://scrapy-chs.readthedocs.io/zh_CN/latest/topics/api.html#module-scrapy.signalmanager

Scrapy源码剖析及自定义Scrapy框架

详细参见>>> http://www.cnblogs.com/leguan1314/articles/6892040.html

posted @ 2017-05-19 15:01  病毒尖er  阅读(222)  评论(0)  编辑  收藏  举报