Python學習筆記——爬蟲之Scrapy專案實戰
目錄
手機App抓包爬蟲
1. items.py
class DouyuspiderItem(scrapy.Item):
name = scrapy.Field()# 儲存照片的名字
imagesUrls = scrapy.Field()# 照片的url路徑
imagesPath = scrapy.Field()# 照片儲存在本地的路徑
2. spiders/douyu.py
import scrapy
import json
from douyuSpider.items import DouyuspiderItem
class DouyuSpider(scrapy.Spider):
name = "douyu"
allowd_domains = ["http://capi.douyucdn.cn"]
offset = 0
url = "http://capi.douyucdn.cn/api/v1/getVerticalRoom?limit=20&offset="
start_urls = [url + str(offset)]
def parse(self, response):
# 返回從json裡獲取 data段資料集合
data = json.loads(response.text)["data"]
for each in data:
item = DouyuspiderItem()
item["name"] = each["nickname"]
item["imagesUrls"] = each["vertical_src"]
yield item
self.offset += 20
yield scrapy.Request(self.url + str(self.offset), callback = self.parse)
3. 設定setting.py
ITEM_PIPELINES = {'douyuSpider.pipelines.ImagesPipeline': 1}
# Images 的存放位置，之後會在pipelines.py裡呼叫
IMAGES_STORE = "/Users/Power/lesson_python/douyuSpider/Images"
# user-agent
USER_AGENT = 'DYZB/2.290 (iPhone; iOS 9.3.4; Scale/2.00)'
4. pipelines.py
import scrapy
import os
from scrapy.pipelines.images import ImagesPipeline
from scrapy.utils.project import get_project_settings
class ImagesPipeline(ImagesPipeline):
IMAGES_STORE = get_project_settings().get("IMAGES_STORE")
def get_media_requests(self, item, info):
image_url = item["imagesUrls"]
yield scrapy.Request(image_url)
def item_completed(self, results, item, info):
# 固定寫法，獲取圖片路徑，同時判斷這個路徑是否正確，如果正確，就放到 image_path裡，ImagesPipeline原始碼剖析可見
image_path = [x["path"] for ok, x in results if ok]
os.rename(self.IMAGES_STORE + "/" + image_path[0], self.IMAGES_STORE + "/" + item["name"] + ".jpg")
item["imagesPath"] = self.IMAGES_STORE + "/" + item["name"]
return item
#get_media_requests的作用就是為每一個圖片連結生成一個Request物件，這個方法的輸出將作為item_completed的輸入中的results，results是一個元組，每個元組包括(success, imageinfoorfailure)。如果success=true，imageinfoor_failure是一個字典，包括url/path/checksum三個key。
在專案根目錄下新建main.py檔案,用於除錯
from scrapy import cmdline
cmdline.execute('scrapy crawl douyu'.split())
執行程式
py2 main.py
陽光熱線問政平臺
http://wz.sun0769.com/index.php/question/questionType?type=4
爬取投訴帖子的編號、帖子的url、帖子的標題，和帖子裡的內容。
items.py
import scrapy
class DongguanItem(scrapy.Item):
# 每個帖子的標題
title = scrapy.Field()
# 每個帖子的編號
number = scrapy.Field()
# 每個帖子的文字內容
content = scrapy.Field()
# 每個帖子的url
url = scrapy.Field()
spiders/sunwz.py
Spider 版本
# -*- coding: utf-8 -*-
import scrapy
from dongguan.items import DongguanItem
class SunSpider(CrawlSpider):
name = 'sun'
allowed_domains = ['wz.sun0769.com']
url = 'http://wz.sun0769.com/index.php/question/questionType?type=4&page='
offset = 0
start_urls = [url + str(offset)]
def parse(self, response):
# 取出每個頁面裡帖子連結列表
links = response.xpath("//div[@class='greyframe']/table//td/a[@class='news14']/@href").extract()
# 迭代傳送每個帖子的請求，呼叫parse_item方法處理
for link in links:
yield scrapy.Request(link, callback = self.parse_item)
# 設定頁碼終止條件，並且每次傳送新的頁面請求呼叫parse方法處理
if self.offset <= 71130:
self.offset += 30
yield scrapy.Request(self.url + str(self.offset), callback = self.parse)
# 處理每個帖子裡
def parse_item(self, response):
item = DongguanItem()
# 標題
item['title'] = response.xpath('//div[contains(@class, "pagecenter p3")]//strong/text()').extract()[0]
# 編號
item['number'] = item['title'].split(' ')[-1].split(":")[-1]
# 文字內容，預設先取出有圖片情況下的文字內容列表
content = response.xpath('//div[@class="contentext"]/text()').extract()
# 如果沒有內容，則取出沒有圖片情況下的文字內容列表
if len(content) == 0:
content = response.xpath('//div[@class="c1 text14_2"]/text()').extract()
# content為列表，通過join方法拼接為字串，並去除首尾空格
item['content'] = "".join(content).strip()
else:
item['content'] = "".join(content).strip()
# 連結
item['url'] = response.url
yield item
CrawlSpider 版本
# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
from dongguan.items import DongguanItem
import time
class SunSpider(CrawlSpider):
name = 'sun'
allowed_domains = ['wz.sun0769.com']
start_urls = ['http://wz.sun0769.com/index.php/question/questionType?type=4&page=']
# 每一頁的匹配規則
pagelink = LinkExtractor(allow=('type=4'))
# 每個帖子的匹配規則
contentlink = LinkExtractor(allow=r'/html/question/\d+/\d+.shtml')
rules = [
# 本案例為特殊情況，需要呼叫deal_links方法處理每個頁面裡的連結
Rule(pagelink, process_links = "deal_links", follow = True),
Rule(contentlink, callback = 'parse_item')
]
# 需要重新處理每個頁面裡的連結，將連結裡的‘Type&type=4?page=xxx’替換為‘Type?type=4&page=xxx’（或者是Type&page=xxx?type=4’替換為‘Type?page=xxx&type=4’），否則無法傳送這個連結
def deal_links(self, links):
for link in links:
link.url = link.url.replace("?","&").replace("Type&", "Type?")
print link.url
return links
def parse_item(self, response):
print response.url
item = DongguanItem()
# 標題
item['title'] = response.xpath('//div[contains(@class, "pagecenter p3")]//strong/text()').extract()[0]
# 編號
item['number'] = item['title'].split(' ')[-1].split(":")[-1]
# 文字內容，預設先取出有圖片情況下的文字內容列表
content = response.xpath('//div[@class="contentext"]/text()').extract()
# 如果沒有內容，則取出沒有圖片情況下的文字內容列表
if len(content) == 0:
content = response.xpath('//div[@class="c1 text14_2"]/text()').extract()
# content為列表，通過join方法拼接為字串，並去除首尾空格
item['content'] = "".join(content).strip()
else:
item['content'] = "".join(content).strip()
# 連結
item['url'] = response.url
yield item
pipelines.py
# -*- coding: utf-8 -*-
# 檔案處理類庫，可以指定編碼格式
import codecs
import json
class JsonWriterPipeline(object):
def __init__(self):
# 建立一個只寫檔案，指定文字編碼格式為utf-8
self.filename = codecs.open('sunwz.json', 'w', encoding='utf-8')
def process_item(self, item, spider):
content = json.dumps(dict(item), ensure_ascii=False) + "\n"
self.filename.write(content)
return item
def spider_closed(self, spider):
self.file.close()
settings.py
ITEM_PIPELINES = {
'dongguan.pipelines.DongguanPipeline': 300,
}
# 日誌檔名和處理等級
LOG_FILE = "dg.log"
LOG_LEVEL = "DEBUG"
在專案根目錄下新建main.py檔案,用於除錯
from scrapy import cmdline
cmdline.execute('scrapy crawl sunwz'.split())
執行程式
py2 main.py
(實戰專案三)新浪網分類資訊爬蟲
爬取新浪網導航頁所有下所有大類、小類、小類裡的子連結，以及子連結頁面的新聞內容。
效果演示圖：
items.py
import scrapy
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
class SinaItem(scrapy.Item):
# 大類的標題 和 url
parentTitle = scrapy.Field()
parentUrls = scrapy.Field()
# 小類的標題 和 子url
subTitle = scrapy.Field()
subUrls = scrapy.Field()
# 小類目錄儲存路徑
subFilename = scrapy.Field()
# 小類下的子連結
sonUrls = scrapy.Field()
# 文章標題和內容
head = scrapy.Field()
content = scrapy.Field()
spiders/sina.py
# -*- coding: utf-8 -*-
# -*- coding: utf-8 -*-
from Sina.items import SinaItem
import scrapy
import os
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
class SinaSpider(scrapy.Spider):
name= "sina"
allowed_domains= ["sina.com.cn"]
start_urls= [
"http://news.sina.com.cn/guide/"
]
def parse(self, response):
items= []
# 所有大類的url 和 標題
parentUrls = response.xpath('//div[@id=\"tab01\"]/div/h3/a/@href').extract()
parentTitle = response.xpath("//div[@id=\"tab01\"]/div/h3/a/text()").extract()
# 所有小類的ur 和 標題
subUrls = response.xpath('//div[@id=\"tab01\"]/div/ul/li/a/@href').extract()
subTitle = response.xpath('//div[@id=\"tab01\"]/div/ul/li/a/text()').extract()
#爬取所有大類
for i in range(0, len(parentTitle)):
# 指定大類目錄的路徑和目錄名
parentFilename = "./Data/" + parentTitle[i]
#如果目錄不存在，則建立目錄
if(not os.path.exists(parentFilename)):
os.makedirs(parentFilename)
# 爬取所有小類
for j in range(0, len(subUrls)):
item = SinaItem()
# 儲存大類的title和urls
item['parentTitle'] = parentTitle[i]
item['parentUrls'] = parentUrls[i]
# 檢查小類的url是否以同類別大類url開頭，如果是返回True (sports.sina.com.cn 和 sports.sina.com.cn/nba)
if_belong = subUrls[j].startswith(item['parentUrls'])
# 如果屬於本大類，將儲存目錄放在本大類目錄下
if(if_belong):
subFilename =parentFilename + '/'+ subTitle[j]
# 如果目錄不存在，則建立目錄
if(not os.path.exists(subFilename)):
os.makedirs(subFilename)
# 儲存 小類url、title和filename欄位資料
item['subUrls'] = subUrls[j]
item['subTitle'] =subTitle[j]
item['subFilename'] = subFilename
items.append(item)
#傳送每個小類url的Request請求，得到Response連同包含meta資料 一同交給回撥函式 second_parse 方法處理
for item in items:
yield scrapy.Request( url = item['subUrls'], meta={'meta_1': item}, callback=self.second_parse)
#對於返回的小類的url，再進行遞迴請求
def second_parse(self, response):
# 提取每次Response的meta資料
meta_1= response.meta['meta_1']
# 取出小類裡所有子連結
sonUrls = response.xpath('//a/@href').extract()
items= []
for i in range(0, len(sonUrls)):
# 檢查每個連結是否以大類url開頭、以.shtml結尾，如果是返回True
if_belong = sonUrls[i].endswith('.shtml') and sonUrls[i].startswith(meta_1['parentUrls'])
# 如果屬於本大類，獲取欄位值放在同一個item下便於傳輸
if(if_belong):
item = SinaItem()
item['parentTitle'] =meta_1['parentTitle']
item['parentUrls'] =meta_1['parentUrls']
item['subUrls'] = meta_1['subUrls']
item['subTitle'] = meta_1['subTitle']
item['subFilename'] = meta_1['subFilename']
item['sonUrls'] = sonUrls[i]
items.append(item)
#傳送每個小類下子連結url的Request請求，得到Response後連同包含meta資料 一同交給回撥函式 detail_parse 方法處理
for item in items:
yield scrapy.Request(url=item['sonUrls'], meta={'meta_2':item}, callback = self.detail_parse)
# 資料解析方法，獲取文章標題和內容
def detail_parse(self, response):
item = response.meta['meta_2']
content = ""
head = response.xpath('//h1[@id=\"main_title\"]/text()')
content_list = response.xpath('//div[@id=\"artibody\"]/p/text()').extract()
# 將p標籤裡的文字內容合併到一起
for content_one in content_list:
content += content_one
item['head']= head
item['content']= content
yield item
pipelines.py
from scrapy import signals
import sys
reload(sys)
sys.setdefaultencoding("utf-8")
class SinaPipeline(object):
def process_item(self, item, spider):
sonUrls = item['sonUrls']
# 檔名為子連結url中間部分，並將 / 替換為 _，儲存為 .txt格式
filename = sonUrls[7:-6].replace('/','_')
filename += ".txt"
fp = open(item['subFilename']+'/'+filename, 'w')
fp.write(item['content'])
fp.close()
return item
settings.py
BOT_NAME = 'Sina'
SPIDER_MODULES = ['Sina.spiders']
NEWSPIDER_MODULE = 'Sina.spiders'
ITEM_PIPELINES = {
'Sina.pipelines.SinaPipeline': 300,
}
LOG_LEVEL = 'DEBUG'
在專案根目錄下新建main.py檔案,用於除錯
from scrapy import cmdline
cmdline.execute('scrapy crawl sina'.split())
執行程式
py2 main.py
Cosplay圖片下載爬蟲
items.py
class CoserItem(scrapy.Item):
url = scrapy.Field()
name = scrapy.Field()
info = scrapy.Field()
image_urls = scrapy.Field()
images = scrapy.Field()
spiders/coser.py
# -*- coding: utf-8 -*-
from scrapy.selector import Selector
import scrapy
from scrapy.contrib.loader import ItemLoader
from Cosplay.items import CoserItem
class CoserSpider(scrapy.Spider):
name = "coser"
allowed_domains = ["bcy.net"]
start_urls = (
'http://bcy.net/cn125101',
'http://bcy.net/cn126487',
'http://bcy.net/cn126173'
)
def parse(self, response):
sel = Selector(response)
for link in sel.xpath("//ul[@class='js-articles l-works']/li[@class='l-work--big']/article[@class='work work--second-created']/h2[@class='work__title']/a/@href").extract():
link = 'http://bcy.net%s' % link
request = scrapy.Request(link, callback=self.parse_item)
yield request
def parse_item(self, response):
item = ItemLoader(item=CoserItem(), response=response)
item.add_xpath('name', "//h1[@class='js-post-title']/text()")
item.add_xpath('info', "//div[@class='post__info']/div[@class='post__type post__info-group']/span/text()")
urls = item.get_xpath('//img[@class="detail_std detail_clickable"]/@src')
urls = [url.replace('/w650', '') for url in urls]
item.add_value('image_urls', urls)
item.add_value('url', response.url)
return item.load_item()
pipelines.py
import requests
from Cosplay import settings
import os
class ImageDownloadPipeline(object):
def process_item(self, item, spider):
if 'image_urls' in item:
images = []
dir_path = '%s/%s' % (settings.IMAGES_STORE, spider.name)
if not os.path.exists(dir_path):
os.makedirs(dir_path)
for image_url in item['image_urls']:
us = image_url.split('/')[3:]
image_file_name = '_'.join(us)
file_path = '%s/%s' % (dir_path, image_file_name)
images.append(file_path)
if os.path.exists(file_path):
continue
with open(file_path, 'wb') as handle:
response = requests.get(image_url, stream=True)
for block in response.iter_content(1024):
if not block:
break
handle.write(block)
item['images'] = images
return item
settings.py
ITEM_PIPELINES = {'Cosplay.pipelines.ImageDownloadPipeline': 1}
IMAGES_STORE = '../Images'
DOWNLOAD_DELAY = 0.25 # 250 ms of delay
在專案根目錄下新建main.py檔案,用於除錯
from scrapy import cmdline
cmdline.execute('scrapy crawl coser'.split())
執行程式
py2 main.py
用Pymongo儲存資料
爬取豆瓣電影top250movie.douban.com/top250的電影資料，並儲存在MongoDB中。
items.py
class DoubanspiderItem(scrapy.Item):
# 電影標題
title = scrapy.Field()
# 電影評分
score = scrapy.Field()
# 電影資訊
content = scrapy.Field()
# 簡介
info = scrapy.Field()
spiders/douban.py
import scrapy
from doubanSpider.items import DoubanspiderItem
class DoubanSpider(scrapy.Spider):
name = "douban"
allowed_domains = ["movie.douban.com"]
start = 0
url = 'https://movie.douban.com/top250?start='
end = '&filter='
start_urls = [url + str(start) + end]
def parse(self, response):
item = DoubanspiderItem()
movies = response.xpath("//div[@class=\'info\']")
for each in movies:
title = each.xpath('div[@class="hd"]/a/span[@class="title"]/text()').extract()
content = each.xpath('div[@class="bd"]/p/text()').extract()
score = each.xpath('div[@class="bd"]/div[@class="star"]/span[@class="rating_num"]/text()').extract()
info = each.xpath('div[@class="bd"]/p[@class="quote"]/span/text()').extract()
item['title'] = title[0]
# 以;作為分隔，將content列表裡所有元素合併成一個新的字串
item['content'] = ';'.join(content)
item['score'] = score[0]
item['info'] = info[0]
# 提交item
yield item
if self.start <= 225:
self.start += 25
yield scrapy.Request(self.url + str(self.start) + self.end, callback=self.parse)
pipelines.py
from scrapy.conf import settings
import pymongo
class DoubanspiderPipeline(object):
def __init__(self):
# 獲取setting主機名、埠號和資料庫名
host = settings['MONGODB_HOST']
port = settings['MONGODB_PORT']
dbname = settings['MONGODB_DBNAME']
# pymongo.MongoClient(host, port) 建立MongoDB連結
client = pymongo.MongoClient(host=host,port=port)
# 指向指定的資料庫
mdb = client[dbname]
# 獲取資料庫裡存放資料的表名
self.post = mdb[settings['MONGODB_DOCNAME']]
def process_item(self, item, spider):
data = dict(item)
# 向指定的表裡新增資料
self.post.insert(data)
return item
settings.py
BOT_NAME = 'doubanSpider'
SPIDER_MODULES = ['doubanSpider.spiders']
NEWSPIDER_MODULE = 'doubanSpider.spiders'
ITEM_PIPELINES = {
'doubanSpider.pipelines.DoubanspiderPipeline' : 300
}
# Crawl responsibly by identifying yourself (and your website) on the user-agent
USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/48.0.2564.116 Safari/537.36'
# MONGODB 主機環回地址127.0.0.1
MONGODB_HOST = '127.0.0.1'
# 埠號，預設是27017
MONGODB_PORT = 27017
# 設定資料庫名稱
MONGODB_DBNAME = 'DouBan'
# 存放本次資料的表名稱
MONGODB_DOCNAME = 'DouBanMovies'
執行
啟動MongoDB資料庫需要兩個命令：
mongod：是mongoDB資料庫程式本身
mongo：是命令列shell客戶端
sudo mongod # 首先啟動資料庫服務，再執行Scrapy
sudo mongo # 啟動資料庫shell
在mongo shell下使用命令:
# 檢視當前資料庫
> db
# 列出所有的資料庫
> show dbs
# 連線DouBan資料庫
> use DouBan
# 列出所有表
> show collections
# 檢視錶裡的資料
> db.DouBanMoives.find()
三種Scrapy模擬登陸策略
注意：模擬登陸時，必須保證settings.py裡的 COOKIES_ENABLED(Cookies中介軟體) 處於開啟狀態
COOKIES_ENABLED = True或# COOKIES_ENABLED = False
策略一：直接POST資料（比如需要登陸的賬戶資訊)
只要是需要提供post資料的，就可以用這種方法。下面示例裡post的資料是賬戶密碼：
# -*- coding: utf-8 -*-
import scrapy
class Renren1Spider(scrapy.Spider):
name = "renren1"
allowed_domains = ["renren.com"]
def start_requests(self):
url = 'http://www.renren.com/PLogin.do'
# FormRequest 是Scrapy傳送POST請求的方法
yield scrapy.FormRequest(
url = url,
formdata = {"email" : "mr_mao_hacker@163.com", "password" : "axxxxxxxe"},
callback = self.parse_page)
def parse_page(self, response):
with open("mao2.html", "w") as filename:
filename.write(response.body)
策略二：標準的模擬登陸步驟
正統模擬登入方法：
首先傳送登入頁面的get請求，獲取到頁面裡的登入必須的引數（比如說zhihu登陸介面的 _xsrf）
然後和賬戶密碼一起post到伺服器，登入成功
# -*- coding: utf-8 -*-
import scrapy
class Renren2Spider(scrapy.Spider):
name = "renren2"
allowed_domains = ["renren.com"]
start_urls = (
"http://www.renren.com/PLogin.do",
)
# 處理start_urls裡的登入url的響應內容，提取登陸需要的引數（如果需要的話)
def parse(self, response):
# 提取登陸需要的引數
#_xsrf = response.xpath("//_xsrf").extract()[0]
# 傳送請求引數，並呼叫指定回撥函式處理
yield scrapy.FormRequest.from_response(
response,
formdata = {"email" : "mr_mao_hacker@163.com", "password" : "axxxxxxxe"},#, "_xsrf" = _xsrf},
callback = self.parse_page
)
# 獲取登入成功狀態，訪問需要登入後才能訪問的頁面
def parse_page(self, response):
url = "http://www.renren.com/422167102/profile"
yield scrapy.Request(url, callback = self.parse_newpage)
# 處理響應內容
def parse_newpage(self, response):
with open("xiao.html", "w") as filename:
filename.write(response.body)
策略三：直接使用儲存登陸狀態的Cookie模擬登陸
如果實在沒辦法了，可以用這種方法模擬登入，雖然麻煩一點，但是成功率100%
# -*- coding: utf-8 -*-
import scrapy
class RenrenSpider(scrapy.Spider):
name = "renren"
allowed_domains = ["renren.com"]
start_urls = (
'http://www.renren.com/111111',
'http://www.renren.com/222222',
'http://www.renren.com/333333',
)
cookies = {
"anonymid" : "ixrna3fysufnwv",
"_r01_" : "1",
"ap" : "327550029",
"JSESSIONID" : "abciwg61A_RvtaRS3GjOv",
"depovince" : "GW",
"springskin" : "set",
"jebe_key" : "f6fb270b-d06d-42e6-8b53-e67c3156aa7e%7Cc13c37f53bca9e1e7132d4b58ce00fa3%7C1484060607478%7C1%7C1486198628950",
"t" : "691808127750a83d33704a565d8340ae9",
"societyguester" : "691808127750a83d33704a565d8340ae9",
"id" : "327550029",
"xnsid" : "f42b25cf",
"loginfrom" : "syshome"
}
# 可以重寫Spider類的start_requests方法，附帶Cookie值，傳送POST請求
def start_requests(self):
for url in self.start_urls:
yield scrapy.FormRequest(url, cookies = self.cookies, callback = self.parse_page)
# 處理響應內容
def parse_page(self, response):
print "===========" + response.url
with open("deng.html", "w") as filename:
filename.write(response.body)
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