公众号原文
创建数据库
我在上一篇笔记中已经创建了数据库，具体查看《scrapy电影天堂实战(一)创建数据库》，这篇笔记创建scrapy实例，先熟悉下要用到到xpath知识
用到的xpath相关知识
reference: https://germey.gitbooks.io/python3webspider/content/4.1-XPath的使用.html
nodename 选取此节点的所有子节点
/ 从当前节点选取直接子节点
// 从当前节点选取子孙节点
. 选取当前节点
.. 选取当前节点的父节点
@ 选取属性
//title[@lang='eng']，
这就是一个 XPath 规则，它就代表选择所有名称为 title，同时属性 lang 的值为 eng 的节点。
- 属性多值匹配
from lxml import etree
text = '''
<li class="li li-first"><a href="link.html">first item</a></li>
'''
html = etree.HTML(text)
result = html.xpath('//li[@class="li"]/a/text()')
print(result)
在这里 HTML 文本中的 li 节点的 class 属性有两个值 li 和 li-first，但是此时如果我们还想用之前的属性匹配获取就无法匹配了, 如果属性有多个值就需要用 contains() 函数了
result = html.xpath('//li[contains(@class, "li")]/a/text()')
- 多属性匹配
from lxml import etree
text = '''
<li class="li li-first" name="item"><a href="link.html">first item</a></li>
'''
html = etree.HTML(text)
result = html.xpath('//li[contains(@class, "li") and @name="item"]/a/text()')
print(result)
在这里 HTML 文本的 li 节点又增加了一个属性 name，这时候我们需要同时根据 class 和 name 属性来选择，就可以 and 运算符连接两个条件，两个条件都被中括号包围。
- 按序选择
result = html.xpath('//li[position()<3]/a/text()')
result = html.xpath('//li[last()-2]/a/text()')
scrapy-python3的dockerfile(可忽略)
可用该dockerfile自行构建镜像
FROM ubuntu:latest
MAINTAINER vickeywu <vickeywu557@gmail.com>
RUN apt-get update
RUN apt-get install -y python3.6 python3-pip python3-dev &&
ln -snf /usr/bin/python3.6 /usr/bin/python
RUN apt-get clean &&
rm -rf /var/cache/apt/archives/* /var/lib/apt/lists/* /tmp/* /var/tmp/*
RUN pip3 install --upgrade pip &&
ln -snf /usr/local/bin/pip3.6 /usr/bin/pip &&
pip install --upgrade scrapy &&
pip install --upgrade pymysql &&
pip install --upgrade redis &&
pip install --upgrade bitarray &&
pip install --upgrade mmh3
WORKDIR /home/scrapy_project
CMD touch /var/log/scrapy.log && tail -f /var/log/scrapy.log
python2环境设置编码使用utf8 (使用python3环境可忽略)
- set var in settings.py
PAGE_ENCODING = 'utf8'
- quote in other file.py:
from scrapy.utils.project import get_project_settings
settings = get_project_settings()
PAGE_ENCODING = settings.get('PAGE_ENCODING')
- set utf8 directly
sys.setdefaultencoding('utf8')
body = (response.body).decode('utf8','ignore')
body = str((response.body).decode('utf16','ignore')).encode('utf8')
创建爬虫
现在正式创建scrapy实例
root@ubuntu:/home/vickey# docker pull vickeywu/scrapy-python3
root@ubuntu:/home/vickey# mkdir scrapy_project # 创建个文件夹存放scrapy项目
root@ubuntu:/home/vickey# cd scrapy_project/
root@ubuntu:/home/vickey/scrapy_project# docker run -itd --name scrapy_movie -v /home/vickey/scrapy_project/:/home/scrapy_project/ vickeywu/scrapy-python3 # 使用已构建好的镜像创建容器
84ae2ee9f02268c68e59cabaf3040d8a8d67c1b2d1442a66e16d4e3e4563d8b8
root@ubuntu:/home/vickey/scrapy_project# docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
84ae2ee9f022 vickeywu/scrapy-python3 "scrapy shell --nolog" 3 seconds ago Up 2 seconds scrapy_movie
d8afb121afc6 mysql "docker-entrypoint.s…" 4 days ago Up 3 hours 33060/tcp, 0.0.0.0:8886->3306/tcp scrapy_mysql
root@ubuntu:/home/vickey/scrapy_project# docker exec -it scrapy_movie /bin/bash
root@84ae2ee9f022:/home/scrapy_project# ls # 挂载的目录暂时没有任何东西，等下创建了项目便会将文件挂载到宿主机，方便修改
root@84ae2ee9f022:/home/scrapy_project# scrapy --help # 查看帮助命令
略
root@84ae2ee9f022:/home/scrapy_project# scrapy startproject movie_heaven_bar # 创建项目名为movie_heaven_bar
New Scrapy project 'movie_heaven_bar', using template directory '/usr/local/lib/python3.6/dist-packages/scrapy/templates/project', created in:
/home/scrapy_project/movie_heaven_bar
You can start your first spider with:
cd movie_heaven_bar
scrapy genspider example example.com
root@84ae2ee9f022:/home/scrapy_project# ls
movie_heaven_bar
root@84ae2ee9f022:/home/scrapy_project# cd movie_heaven_bar/ # 进入项目后再创建爬虫
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar# ls
movie_heaven_bar scrapy.cfg
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar# scrapy genspider movie_heaven_bar www.dytt8.net # 创建爬虫名为movie_heaven_bar失败，不能与项目同名。。改个名
Cannot create a spider with the same name as your project
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar# scrapy genspider newest_movie www.dytt8.net # 创建爬虫名为newest_movie
Created spider 'newest_movie' using template 'basic' in module:
movie_heaven_bar.spiders.newest_movie
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar# cd movie_heaven_bar/
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar/movie_heaven_bar# ls
__init__.py __pycache__ items.py middlewares.py pipelines.py settings.py spiders
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar/movie_heaven_bar# cd spiders/
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar/movie_heaven_bar/spiders# ls # 创建的爬虫文件会在项目的spiders文件夹下
__init__.py __pycache__ newest_movie.py
root@84ae2ee9f022:/home/scrapy_project/movie_heaven_bar/movie_heaven_bar/spiders# exit # 退出容器
exit
root@ubuntu:/home/vickey/scrapy_project# ls # 退出容器后可以看到创建的项目文件已经挂载到宿主机本地，接下来在宿主机撸代码即可
movie_heaven_bar
撸代码
- items.py
# -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html
import scrapy
from scrapy.item import Item, Field
class MovieHeavenBarItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
#pass
movie_link = Field()
movie_name = Field()
movie_director = Field()
movie_actors = Field()
movie_publish_date = Field()
movie_score = Field()
movie_download_link = Field()
- settings.py
数据库设置、延时设置、启用pipeline、日志设置，暂时只用到这些
BOT_NAME = 'movie_heaven_bar'
SPIDER_MODULES = ['movie_heaven_bar.spiders']
NEWSPIDER_MODULE = 'movie_heaven_bar.spiders'
# db settings
DB_SETTINGS = {
'DB_HOST': '192.168.229.128',
'DB_PORT': 8886,
'DB_DB': 'movie_heaven_bar',
'DB_USER': 'movie',
'DB_PASSWD': '123123',
}
# obey ROBOTS.txt set True if raise error set False
ROBOTSTXT_OBEY = True
# delay 3 seconds
DOWNLOAD_DELAY = 3
# enable pipeline
ITEM_PIPELINES = {
'movie_heaven_bar.pipelines.MovieHeavenBarPipeline': 300,
}
# log settings
LOG_LEVEL = 'INFO'
LOG_FILE = '/var/log/scrapy.log'
- pipelines.py
reference: https://docs.scrapy.org/en/latest/topics/item-pipeline.html?highlight=filter#item-pipeline
项目爬虫(
scrapy genspider spidername命令生成到爬虫文件)抓取到数据之后将它们发送到项目管道(项目下到pipelines.py文件里定义到各种class)，管道通过settings.py里面定义的ITEM_PIPELINES优先级顺序(0~1000从小到大)来处理数据。
作用：1.清洗数据 2.验证数据（检查项目是否包含某些字段） 3.检查重复项（并删除它们） 4.将数据存储到数据库
reference: http://scrapingauthority.com/scrapy-database-pipeline/
# -*- coding: utf-8 -*-
# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
import pymysql
from scrapy.exceptions import NotConfigured
class MovieHeavenBarPipeline(object):
def __init__(self, host, port, db, user, passwd):
self.host = host
self.port = port
self.db = db
self.user = user
self.passwd = passwd
# reference: doc.scrapy.org/en/latest/topics/item-pipeline.html#from_crawler
@classmethod
def from_crawler(cls, crawler):
db_settings = crawler.settings.getdict('DB_SETTINGS')
if not db_settings:
raise NotConfigured
host = db_settings['DB_HOST']
port = db_settings['DB_PORT']
db = db_settings['DB_DB']
user = db_settings['DB_USER']
passwd = db_settings['DB_PASSWD']
return cls(host, port, db, user, passwd)
def open_spider(self, spider):
self.conn = pymysql.connect(
host=self.host,
port=self.port,
db=self.db,
user=self.user,
passwd=self.passwd,
charset='utf8',
use_unicode=True,
)
self.cursor = self.conn.cursor()
def process_item(self, item, spider):
sql = 'INSERT INTO newest_movie(movie_link, movie_name, movie_director, movie_actors, movie_publish_date, movie_score, movie_download_link) VALUES (%s, %s, %s, %s, %s, %s, %s)'
self.cursor.execute(sql, (item.get('movie_link'), item.get('movie_name'), item.get('movie_director'), item.get('movie_actors'), item.get('movie_publish_date'), item.get('movie_score'), item.get('movie_download_link')))
self.conn.commit()
return item
def close_spider(self, spider):
self.conn.close()
- spiders/newest_movie.py
# -*- coding: utf-8 -*-
import scrapy
import time
import logging
from scrapy.http import Request
from movie_heaven_bar.items import MovieHeavenBarItem
class NewestMovieSpider(scrapy.Spider):
name = 'newest_movie'
allowed_domains = ['www.dytt8.net']
#start_urls = ['http://www.dytt8.net/']
# 从该urls列表开始爬取
start_urls = ['http://www.dytt8.net/html/gndy/dyzz/']
def parse(self, response):
item = MovieHeavenBarItem()
domain = "https://www.dytt8.net"
urls = response.xpath('//b/a/@href').extract() # list type
#print('urls', urls)
for url in urls:
url = domain + url
yield Request(url=url, callback=self.parse_single_page, meta={'item': item}, dont_filter = False)
# 爬取下一页
last_page_num = response.xpath('//select[@name="sldd"]//option[last()]/text()').extract()[0]
last_page_url = 'list_23_' + last_page_num + '.html'
next_page_url = response.xpath('//div[@class="x"]//a[last() - 1]/@href').extract()[0]
if next_page_url != last_page_url:
url = 'https://www.dytt8.net/html/gndy/dyzz/' + next_page_url
logging.log(logging.INFO, '***************** page num ***************** ')
logging.log(logging.INFO, 'crawling page: ' + next_page_url)
yield Request(url=url, callback=self.parse, meta={'item': item}, dont_filter = False)
def parse_single_page(self, response):
item = response.meta['item']
item['movie_link'] = response.url
detail_row = response.xpath('//*[@id="Zoom"]//p/text()').extract() # str type list
# 将网页提取的str列表类型数据转成一个长字符串, 以圆圈为分隔符，精确提取各个字段具体内容
detail_list = ''.join(detail_row).split('◎')
logging.log(logging.INFO, '******************log movie detail*******************')
item['movie_name'] = detail_list[1][5:].replace(6*u'u3000', u', ')
logging.log(logging.INFO, 'movie_link: ' + item['movie_link'])
logging.log(logging.INFO, 'movie_name: ' + item['movie_name'])
# 找到包含特定字符到字段
for field in detail_list:
if '主u3000u3000演' in field:
# 将字段包含杂质去掉[5:].replace(6*u'u3000', u', ')
item['movie_actors'] = field[5:].replace(6*u'u3000', u', ')
logging.log(logging.INFO, 'movie_actors: ' + item['movie_actors'])
if '导u3000u3000演' in field:
item['movie_director'] = field[5:].replace(6*u'u3000', u', ')
logging.log(logging.INFO, 'movie_directors: ' + item['movie_director'])
if '上映日期' in field:
item['movie_publish_date'] = field[5:].replace(6*u'u3000', u', ')
logging.log(logging.INFO, 'movie_publish_date: ' + item['movie_publish_date'])
if '豆瓣评分' in field:
item['movie_score'] = field[5:].replace(6*u'u3000', u', ')
logging.log(logging.INFO, 'movie_score: ' + item['movie_score'])
# 此处获取的是迅雷磁力链接，安装好迅雷，复制该链接到浏览器地址栏迅雷会自动打开下载链接，个别网页结构不一致会获取不到链接
try:
item['movie_download_link'] = ''.join(response.xpath('//p/a/@href').extract())
logging.log(logging.INFO, 'movie_download_link: ' + item['movie_download_link'])
except Exception as e:
item['movie_download_link'] = response.url
logging.log(logging.WARNING, e)
yield item
启动爬虫
root@ubuntu:/home/vickey/scrapy_project/movie_heaven_bar# docker exec -it scrapy_movie /bin/bash
root@1040aa3b7363:/home/scrapy_project# ls
movie_heaven_bar
root@1040aa3b7363:/home/scrapy_project# cd movie_heaven_bar/
root@1040aa3b7363:/home/scrapy_project/movie_heaven_bar# ls
movie_heaven_bar run.sh scrapy.cfg
root@1040aa3b7363:/home/scrapy_project/movie_heaven_bar# sh run.sh & # 后台运行脚本，日志输出可以在/var/log/scrapy.log中看到
root@1040aa3b7363:/home/scrapy_project/movie_heaven_bar# exit
exit
root@ubuntu:/home/vickey/scrapy_project/movie_heaven_bar# ls
movie_heaven_bar README.md run.sh scrapy.cfg
root@ubuntu:/home/vickey/scrapy_project/movie_heaven_bar# docker logs -f scrapy_movie # 使用docker logs -f --tail 20 scrapy_movie也可以看到scrapy的日志输出。
- scrapy爬虫日志截图
- scrapy数据库截图
结语
大功告成，现在我想看哪部电影只需要将movie_download_link的链接复制到浏览器打开，即可自动打开迅雷链接下载电影了(前提是已经安装迅雷)，然后就可以在迅雷边下边看了，美滋滋。
不过，如果我中途停止了爬取，又要从头开始爬，所以就会有数据重复，很烦。下一篇笔记写下scrapy的去重方法，这样就不会有数据重复了，也可以节省爬取耗时。
代码已上传至github: https://github.com/Vickey-Wu/movie_heaven_bar