scrapy

爬虫 - scrapy之定制命令

六眼飞鱼酱① 提交于 2020-02-02 01:04:50
单爬虫运行 import sys from scrapy.cmdline import execute if __name__ == '__main__': execute(["scrapy","crawl","chouti","--nolog"]) 然后右键运行py文件即可运行名为‘chouti‘的爬虫 同时运行多个爬虫 步骤如下: - 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)- 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 代码如下: 1 from scrapy.commands import ScrapyCommand 2 from scrapy.utils.project import get_project_settings 3 4 class Command(ScrapyCommand): 5 6 requires_project = True 7 8 def syntax(self): 9 return '[options]' 10 11 def short_desc(self): 12 return 'Runs all of the spiders' 13 14 def

scrapy框架自定制命令

南楼画角 提交于 2020-02-01 19:51:24
写好自己的爬虫项目之后,可以自己定制爬虫运行的命令。 一、单爬虫 在项目的根目录下新建一个py文件,如命名为start.py,写入如下代码: from scrapy.cmdline import execute if __name__ == "__main__": execute(["scrapy", "crawl", "chouti", "--nolog"]) 运行start.py即可。 二、多爬虫运行 1、在spiders的同级目录创建文件夹,如commands; 2、在这个新建的文件夹下创建一个py文件,如命名为crawlall.py,编写代码: from scrapy.commands import ScrapyCommand class Command(ScrapyCommand): requires_project = True def syntax(self): return "[options]" def short_desc(self): return "Run all of the spiders" # 自定义命令描述 def run(self, args, opts): spider_list = self.crawler_process.spiders.list() # 获取爬虫列表 for name in spider_list: # 循环列表

scrapy框架自定制命令

大城市里の小女人 提交于 2020-02-01 15:33:40
scrapy框架自定制命令 写好自己的爬虫项目之后,可以自己定制爬虫运行的命令。 一、单爬虫 在项目的根目录下新建一个py文件,如命名为start.py,写入如下代码: from scrapy.cmdline import execute if __name__ == "__main__": execute(["scrapy", "crawl", "chouti", "--nolog"]) 运行start.py即可。 二、多爬虫运行 1、在spiders的同级目录创建文件夹,如commands; 2、在这个新建的文件夹下创建一个py文件,如命名为crawlall.py,编写代码: from scrapy.commands import ScrapyCommand class Command(ScrapyCommand): requires_project = True def syntax(self): return "[options]" def short_desc(self): return "Run all of the spiders" # 自定义命令描述 def run(self, args, opts): spider_list = self.crawler_process.spiders.list() # 获取爬虫列表 for name in spider_list

scrapy自定制命令

99封情书 提交于 2020-02-01 15:31:01
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) 1 from scrapy.commands import ScrapyCommand 2 from scrapy.utils.project import get_project_settings 3 4 5 class Command(ScrapyCommand): 6 7 requires_project = True 8 9 def syntax(self): 10 return '[options]' 11 12 def short_desc(self): 13 return 'Runs all of the spiders' 14 15 def run(self, args, opts): 16 spider_list = self.crawler_process.spiders.list() 17 for name in spider_list: 18 self.crawler_process.crawl(name, **opts.__dict__) 19 self.crawler_process.start() crawlall.py 在settings.py 中添加配置 COMMANDS_MODULE = '项目名称

scrapy之自定制命令

做~自己de王妃 提交于 2020-02-01 15:30:18
写好自己的爬虫项目之后,可以自己定制爬虫运行的命令。 一、单爬虫 在项目的根目录下新建一个py文件,如命名为start.py,写入如下代码: from scrapy.cmdline import execute if __name__ == "__main__": execute(["scrapy", "crawl", "chouti", "--nolog"]) 运行start.py即可。 二、多爬虫运行 1、在spiders的同级目录创建文件夹,如commands; 2、在这个新建的文件夹下创建一个py文件,如命名为crawlall.py,编写代码: from scrapy.commands import ScrapyCommand class Command(ScrapyCommand): requires_project = True def syntax(self): return "[options]" def short_desc(self): return "Run all of the spiders" # 自定义命令描述 def run(self, args, opts): spider_list = self.crawler_process.spiders.list() # 获取爬虫列表 for name in spider_list: # 循环列表

Extract embedded pdf

北战南征 提交于 2020-02-01 09:55:10
问题 I noted that docplayer.net embeds many pdfs. Example: http://docplayer.net/72489212-Excellence-in-prevention-descriptions-of-the-prevention-programs-and-strategies-with-the-greatest-evidence-of-success.html However, how does the process of extracting these pdfs (i.e. downloading them) using an automated workflow work? 回答1: You can notice in browser's developer tools under Network/XHR tab that the actual document is being requested. In your particular case given it's on URL http://docplayer

Extract embedded pdf

依然范特西╮ 提交于 2020-02-01 09:55:07
问题 I noted that docplayer.net embeds many pdfs. Example: http://docplayer.net/72489212-Excellence-in-prevention-descriptions-of-the-prevention-programs-and-strategies-with-the-greatest-evidence-of-success.html However, how does the process of extracting these pdfs (i.e. downloading them) using an automated workflow work? 回答1: You can notice in browser's developer tools under Network/XHR tab that the actual document is being requested. In your particular case given it's on URL http://docplayer

Scrapy项目 - 项目源码 - 实现腾讯网站社会招聘信息爬取的爬虫设计

倾然丶 夕夏残阳落幕 提交于 2020-01-31 23:39:35
1.tencentSpider.py # -*- coding: utf-8 -*- import scrapy from Tencent.items import TencentItem #创建爬虫类 class TencentspiderSpider(scrapy.Spider): name = 'tencentSpider'#爬虫名字 allowed_domains = ['tencent.com']#容许爬虫的作用范围 # 定义开始的URL offset = 0 url = 'https://hr.tencent.com/position.php?&start=' #urll='#a' start_urls = [url + str(offset)] # 爬虫开始的URL def parse(self, response): # 继承 item = TencentItem() # 根节点 movies = response.xpath("//tr[@class='odd']|//tr[@class='even']") for each in movies: item['zhiwei']=each.xpath(".//td[@class='l square']/a/text()").extract()[0] item['lianjie'] = each.xpath("./

How to limit scrapy request objects?

社会主义新天地 提交于 2020-01-31 20:04:52
问题 So I have a spider that I thought was leaking memory, turns out it is just grabbing too many links from link rich pages (sometimes it puts upwards of 100,000) when I check the telnet console >>> prefs() Now I have been over the docs and google again and again and I can't find a way to limit the requests that the spider takes in. What I want is to be able to tell it to hold back on taking requests once a certain amount goes into the scheduler. I have tried setting a DEPTH_LIMIT but that only

Scraping all text using Scrapy without knowing webpages' structure

一个人想着一个人 提交于 2020-01-31 15:12:45
问题 I am conducting a research which relates to distributing the indexing of the internet. While several such projects exist (IRLbot, Distributed-indexing, Cluster-Scrapy, Common-Crawl etc.), mine is more focused on incentivising such behavior. I am looking for a simple way to crawl real webpages without knowing anything about their URL or HTML structure and: extract all their text (in order to index it) Collect all their URLs and add them to the URLs to crawl Prevent crashing and elegantly