【scrapy實踐】_爬取安居客_廣州_新樓盤數據

需求：爬取【安居客—廣州—新樓盤】的數據，具體到每個樓盤的詳情頁的若幹欄位。難點：樓盤類型各式各樣：住宅別墅商住商鋪寫字樓，不同樓盤欄位的名稱不一樣。然後同一種類型，比如住宅，又分為不同的情況，比如分為期房在售，現房在售，待售，尾盤。其他類型也有類似情況。所以欄位不能設置固定住。解決方案 ...

需求：爬取【安居客—廣州—新樓盤】的數據，具體到每個樓盤的詳情頁的若幹欄位。

難點：樓盤類型各式各樣：住宅別墅商住商鋪寫字樓，不同樓盤欄位的名稱不一樣。然後同一種類型，比如住宅，又分為不同的情況，比如分為期房在售，現房在售，待售，尾盤。其他類型也有類似情況。所以欄位不能設置固定住。

解決方案：目前想到的解決方案，第一種：scrapy中items.py中不設置欄位，spider中爬的時候自動識別欄位（也就是有啥欄位就保留下來），然後返回字典存起來。第二種，不同欄位的網頁分別寫規則單獨抓取。顯然不可取。我採用的是第一種方案。還有其他方案的朋友們，歡迎交流哈。

目標網址為：http://gz.fang.anjuke.com/ 該網頁下的樓盤數據

示例樓盤網址：http://gz.fang.anjuke.com/loupan/canshu-298205.html?from=loupan_tab

開始編寫scrapy腳本。建立工程步驟略過。

1、count.py

 1 __author__ = 'Oscar_Yang'
 2 #-*- coding= utf-8 -*-
 3 """
 4     查看mongodb存儲狀況的腳本count.py
 5 """
 6 import time
 7 import pymongo
 8 client = pymongo.MongoClient("localhost", 27017)
 9 db = client["SCRAPY_anjuke_gz"]
10 sheet = db["anjuke_doc1"]
11 
12 while True:
13     print(sheet.find().count())
14     print("____________________________________")
15     time.sleep(3)

1 """
2     entrypoint.py
3 """
4 from scrapy.cmdline import execute
5 execute(['scrapy', 'crawl', 'anjuke_gz'])

 1 # -*- coding: utf-8 -*-
 2 """
 3     settings.py
 4 """
 5 
 6 # Scrapy settings for anjuke_gz project
 7 #
 8 # For simplicity, this file contains only settings considered important or
 9 # commonly used. You can find more settings consulting the documentation:
10 #
11 #     http://doc.scrapy.org/en/latest/topics/settings.html
12 #     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
13 #     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
14 
15 BOT_NAME = 'anjuke_gz'
16 
17 SPIDER_MODULES = ['anjuke_gz.spiders']
18 NEWSPIDER_MODULE = 'anjuke_gz.spiders'
19 MONGODB_HOST = "127.0.0.1"
20 MONGODB_PORT = 27017
21 MONGODB_DBNAME="SCRAPY_anjuke_gz"
22 MONGODB_DOCNAME="anjuke_doc1"
23 
24 # Crawl responsibly by identifying yourself (and your website) on the user-agent
25 #USER_AGENT = 'anjuke_gz (+http://www.yourdomain.com)'
26 
27 # Obey robots.txt rules
28 ROBOTSTXT_OBEY = False
29 
30 # Configure maximum concurrent requests performed by Scrapy (default: 16)
31 #CONCURRENT_REQUESTS = 32
32 
33 # Configure a delay for requests for the same website (default: 0)
34 # See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
35 # See also autothrottle settings and docs
36 #DOWNLOAD_DELAY = 3
37 # The download delay setting will honor only one of:
38 #CONCURRENT_REQUESTS_PER_DOMAIN = 16
39 #CONCURRENT_REQUESTS_PER_IP = 16
40 
41 # Disable cookies (enabled by default)
42 #COOKIES_ENABLED = False
43 
44 # Disable Telnet Console (enabled by default)
45 #TELNETCONSOLE_ENABLED = False
46 
47 # Override the default request headers:
48 #DEFAULT_REQUEST_HEADERS = {
49 #   'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
50 #   'Accept-Language': 'en',
51 #}
52 
53 # Enable or disable spider middlewares
54 # See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
55 #SPIDER_MIDDLEWARES = {
56 #    'anjuke_gz.middlewares.AnjukeGzSpiderMiddleware': 543,
57 #}
58 
59 # Enable or disable downloader middlewares
60 # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
61 #DOWNLOADER_MIDDLEWARES = {
62 #    'anjuke_gz.middlewares.MyCustomDownloaderMiddleware': 543,
63 #}
64 
65 # Enable or disable extensions
66 # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
67 #EXTENSIONS = {
68 #    'scrapy.extensions.telnet.TelnetConsole': None,
69 #}
70 
71 # Configure item pipelines
72 # See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
73 ITEM_PIPELINES = {
74    'anjuke_gz.pipelines.AnjukeGzPipeline': 300,
75 }
76 
77 # Enable and configure the AutoThrottle extension (disabled by default)
78 # See http://doc.scrapy.org/en/latest/topics/autothrottle.html
79 #AUTOTHROTTLE_ENABLED = True
80 # The initial download delay
81 #AUTOTHROTTLE_START_DELAY = 5
82 # The maximum download delay to be set in case of high latencies
83 #AUTOTHROTTLE_MAX_DELAY = 60
84 # The average number of requests Scrapy should be sending in parallel to
85 # each remote server
86 #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
87 # Enable showing throttling stats for every response received:
88 #AUTOTHROTTLE_DEBUG = False
89 
90 # Enable and configure HTTP caching (disabled by default)
91 # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
92 HTTPCACHE_ENABLED = True
93 HTTPCACHE_EXPIRATION_SECS = 0
94 HTTPCACHE_DIR = 'httpcache'
95 HTTPCACHE_IGNORE_HTTP_CODES = []
96 HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

接下來，是items。因為沒有設置欄位，為預設的代碼。

 1 # -*- coding: utf-8 -*-
 2 
 3 # Define here the models for your scraped items
 4 #
 5 # See documentation in:
 6 # http://doc.scrapy.org/en/latest/topics/items.html
 7 
 8 import scrapy
 9 
10 
11 class AnjukeGzItem(scrapy.Item):
12     # define the fields for your item here like:
13     # name = scrapy.Field()
14     pass

接下來，是piplines.py。在中設置了mongodb的配置。

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html


import pymongo
from scrapy.conf import settings

class AnjukeGzPipeline(object):
    def __init__(self):
        host=settings["MONGODB_HOST"]
        port=settings["MONGODB_PORT"]
        dbname=settings["MONGODB_DBNAME"]
        client=pymongo.MongoClient(port=port,host=host)
        tdb = client[dbname]
        self.post=tdb[settings["MONGODB_DOCNAME"]]
    def process_item(self,item,spider):
        info = dict(item)
        self.post.insert(info)
        return item

最後，是最主要的spider.py

 1 from scrapy.http import Request
 2 import scrapy
 3 from bs4 import BeautifulSoup
 4 import re
 5 import requests
 6 """
 7     spider腳本
 8 """
 9 class Myspider(scrapy.Spider):
10     name = 'anjuke_gz'
11     allowed_domains = ['http://gz.fang.anjuke.com/loupan/']
12     start_urls = ["http://gz.fang.anjuke.com/loupan/all/p{}/".format(i) for i in range(39)]
13 
14     def parse(self, response):
15         soup = BeautifulSoup(response.text,"lxml")
16         content=soup.find_all(class_="items-name") #返回每個樓盤的對應數據
17         for item in content:
18             code=item["href"].split("/")[-1][:6]
19             real_href="http://gz.fang.anjuke.com/loupan/canshu-{}.html?from=loupan_tab".format(code) #拼湊出樓盤詳情頁的url
20             res=requests.get(real_href)
21             soup = BeautifulSoup(res.text,"lxml")
22             a = re.findall(r'<div class="name">(.*?)</div>', str(soup))
23             b = soup.find_all(class_="des")
24             data = {}
25             for (i, j) in zip(range(len(b)), a):
26                 data[j] = b[i].text.strip().strip("\t")
27                 data["url"] = real_href
28             yield data

下麵是存入mongodb的情況。

　　因為針對不同的網頁結構，爬取的規則是一個，所以爬取的時候就不能針對每個欄位進行爬取，所以存到庫里的數據如果要是分析的話還需要清洗。

在python中使用mongodb的查詢語句，再配合使用pandas應該就很方便清洗了。