Python爬虫实战 - 模拟登陆各大网站 包含但不限于：滑块验证、拼多多、美团、百度、bilibili、大众点评、淘宝，如果喜欢请start ❤️

Possibly the best practice of Scrapy 🕷 and renting a house 🏡

대량의 뉴스 데이터를 수집하기 위해 만들어진 뉴스 크롤러입니다.

DotnetCrawler is a straightforward, lightweight web crawling/scrapying library for Entity Framework Core output based on dotnet core. This library designed like other strong crawler libraries like WebMagic and Scrapy but for enabling extandable your custom requirements. Medium link : https://medium.com/@mehmetozkaya/creating-custom-web-crawler-with-dotnet-core-using-entity-framework-core-ec8d23f0ca7c

OLX Scraper in Python Scrapy

Web Scraping Craigslist's Engineering Jobs in NY with Scrapy

使用python爬取水木清华和北大未名的实习信息，在微信客户端进行展示。

金融问答平台文本数据采集/爬取，数据源涉及上交所，深交所，全景网及新浪股吧

Scrapy project for scraping data from IMDB with Movie Dataset including 58,623 movies' data.

一个科研论文采集助手，可以在google学术和百度学术上搜索领域论文，并且自动找到综述类论文，有利于文献综述的写作和科研入门者的学习A scientific assistant collecting academic papers

爬取腾讯新闻首页所有新闻及其评论

A bot that scrapes Twitter.

More than 50 web scraping examples using: Requests | Scrapy | Selenium | LXML | BeautifulSoup

Lets learn web scraping and apply them in real application.

Explorando Técnicas de Web Scraping com Python

Very simple VideoPlayer

Scrapy spiders to crawl daily betting tips from website, automatically uploading to google sheets.

👔 Web scraper for http://www.prodirectselect.com/ 👞

Finance and Investment Info Spider Collections - 投融资信息爬虫集合

Machine Learning project to predict popularity of Instagram posts

ANP Price Collector

Scraping the real estate agencies for up-to-date house listings as soon as they arrive!

Search given query on Google, and crawls for emails & phones related to the result

Scrapy middleware interface to scrape using ProxyCrawl proxy service

LinkedIn Scraper

Use Scrapy to crawl text reviews & images from Dianping.com and generate pretty static pages!

Projects using selenium, requests, bs4, and scrapy for web scraping on google images, google trends and others

基于scrapy的中国国内各大新闻网站内容爬虫

A project which implements the Data Science pipeline - Extracting raw data, Data Cleaning, Feature Extraction, Entity Matching, Data Matching, Data Merging and OLAP style exploration. The two entities chosen are Yelp and Zomato. Restaurant data from the same localities will be extracted from both sites and similar restaurants will be merged into one big table. OLAP style exploration will be done on that table to find out the insights from the collected data (Eg, Which is the most highly rated restaurant in California)