python爬虫练手项目，scrapy爬虫爬取京东所有商品分类、商品列表、商品详情、价格信息，可爬取京东全站商品
2021-09-18 14:48:49
15KB
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#5.2_高效无忧的_Scrapy_爬虫库_(爬虫_scraping_基础)
2021-09-01 21:00:26
24.47MB
scrapy爬取51cto博客文章列表保存到本地数据库。这个是本人最近学习爬虫的一个实践案例，源码解析详情请移步博文：https://blog.csdn.net/xiaocy66/article/details/83834261
2021-08-24 16:56:45
14KB
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【建立目标】
同样在做任何事情之前都需要明确目标，那这次我们的目标是爬取一些技术性的文章并存储到数据库中。这就需要有目标网址和数据库结构，数据库我们选择使用MySql，目标网站我们找了一个叫脚本之家的内容站。我们这里首先准备好一张用于存储文章的表结构：
CREATE TABLE `articles` (
`id` mediumint(8) AUTO_INCREMENT NOT NULL,
`title` varchar(255) DEFAULT NULL,
`content` longtext,
`add_date` int(11) DEFAULT 0,
`hits` int(11) DEFAULT '0',
`origin` varchar(500) DEFAULT '',
`tags` varchar(45) DEFAULT '',
PRIMARY KEY (`id`),
KEY `add_date` (`add_date`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci;
2021-07-10 21:02:56
804KB
基于Python Scrapy实现的拉勾网全站职位数据采集 爬虫系统 含数据库处理和全部源代码
# -*- coding: utf-8 -*-
import scrapy
from meiju100.items import Meiju100Item
class MeijuSpider(scrapy.Spider):
name = "meiju"
allowed_domains = ["meijutt.com"]
start_urls = ['http://www.meijutt.com/new100.html']
def parse(self, response):
items = []
subSelector = response.xpath('//ul[@class="top-list fn-clear"]/li')
for sub in subSelector:
item = Meiju100Item()
item['storyName'] = sub.xpath('./h5/a/text()').extract()
item['storyState'] = sub.xpath('./span[1]/font/text()').extract()
if item['storyState']:
pass
else:
item['storyState'] = sub.xpath('./span[1]/text()').extract()
item['tvStation'] = sub.xpath('./span[2]/text()').extract()
if item['tvStation']:
pass
else:
item['tvStation'] = [u'未知']
item['updateTime'] = sub.xpath('./div[2]/text()').extract()
if item['updateTime']:
pass
else:
item['updateTime'] = sub.xpath('./div[2]/font/text()').extract()
items.append(item)
return items
2021-07-10 17:02:48
14KB
基于Python Scrapy实现的爬取豆瓣读书9分榜单的书籍数据采集爬虫系统 含数据集和全部源代码
# -*- coding: utf-8 -*-
import scrapy
import re
from doubanbook.items import DoubanbookItem
class DbbookSpider(scrapy.Spider):
name = "dbbook"
# allowed_domains = ["https://www.douban.com/doulist/1264675/"]
start_urls = (
'https://www.douban.com/doulist/1264675/',
)
URL = 'https://www.douban.com/doulist/1264675/?start=PAGE&sort=seq&sub_type='
def parse(self, response):
# print response.body
item = DoubanbookItem()
selector = scrapy.Selector(response)
books = selector.xpath('//div[@class="bd doulist-subject"]')
for each in books:
title = each.xpath('div[@class="title"]/a/text()').extract()[0]
rate = each.xpath('div[@class="rating"]/span[@class="rating_nums"]/text()').extract()[0]
author = re.search('(.*?)
2021-07-10 17:02:47
19KB
基于Python Scrapy实现的蜂鸟数据采集爬虫系统 含代理、日志处理和全部源代码等
import scrapy
from fengniao.items import FengniaoItem
from scrapy.spidermiddlewares.httperror import HttpError
from twisted.internet.error import TimeoutError, TCPTimedOutError, DNSLookupError, ConnectionRefusedError
class FengniaoclawerSpider(scrapy.Spider):
name = 'fengniaoClawer'
allowed_domains = ['fengniao.com']
# 爬虫自定义设置，会覆盖 settings.py 文件中的设置
custom_settings = {
'LOG_LEVEL': 'DEBUG', # 定义log等级
'DOWNLOAD_DELAY': 0, # 下载延时
'COOKIES_ENABLED': False, # enabled by default
'DEFAULT_REQUEST_HEADERS': {
# 'Host': 'www.fengniao.com',
'Referer': 'https://www.fengniao.com',
},
# 管道文件，优先级按照由小到大依次进入
'ITEM_PIPELINES': {
'fengniao.pipelines.ImagePipeline': 100,
'fengniao.pipelines.FengniaoPipeline': 300,
},
# 关于下载图片部分
'IMAGES_STORE': 'fengniaoPhoto', # 没有则新建
'IMAGES_EXPIRES': 90, # 图片有效期,已经存在的图片在这个时间段内不会再下载
'IMAGES_MIN_HEIGHT': 100, # 图片最小尺寸（高度），低于这个高度的图片不会下载
'IMAGES_MIN_WIDTH': 100, # 图片最小尺寸（宽度），低于这个宽度的图片不会下载
# 下载中间件，优先级按照由小到大依次进入
'DOWNLOADER_MIDDLEWARES': {
'fengniao.middlewares.ProxiesMiddleware': 400,
'fengniao.middlewares.HeadersMiddleware': 543,
'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware': None,
},
'DEPTH_PRIORITY': 1, # BFS，是以starts_url为准，局部BFS，受CONCURRENT_REQUESTS影响
'SCHEDULER_DISK_QUEUE': 'scrapy.squeues.PickleFifoDiskQueue',
'SCHEDULER_MEMORY_QUEUE': 'scrapy.squeues.FifoMemoryQueue',
'REDIRECT_PRIORITY_ADJUST': 2, # Default: +2
'RETRY_PRIORITY_ADJUST': -1, # Default: -1
'RETRY_TIMES': 8, # 重试次数
# Default: 2, can also be specified per-request using max_retry_times attribute of Request.meta
'DOWNLOAD_TIMEOUT': 30,
# This timeout can be set per spider using download_timeout spider attribute and per-request using download_timeout Request.meta key
# 'DUPEFILTER_CLASS': "scrapy_redis.dupefilter.RFPDupeFilter",
# 'SCHEDULER': "scrapy_redis.scheduler.Scheduler",
# 'SCHEDULER_PERSIST': False, # Don't cleanup red
2021-07-10 17:02:46
14KB