Web Scraping - Real estate websites

To develop a scrapper (robot for the collection of web data) in python (Selenium, BeautifulSoup, PHP, Scrapy, etc.) of real estate buying and selling sites. The data extraction must include all the basic characteristics of the properties (type of property, price, construction meters, number of bedrooms, number of bathrooms, location, etc.) and contact information available for each ad (name of the advertiser, telephone, mail, etc.), as well as the images of the real estate properties associated with the advertisements. The information must be stored in a database (MongoDB, PostgreSQL or MySQL), so knowledge of databases is required. Important aspects to consider: a) the scrapper must be parameterizable, that is, it must allow searching by type of real estate / city / neighborhood, etc .; b) You must optionally enable the saving of images associated with each advertisement; c) it must integrate techniques that prevent the banning or blocking of the scrapper (real estate websites can contain more than 100,000 ads for large cities, usually they use dynamic pages and the detail of the information of the ads is in a second level); d) must generate a report with the summary of the scrapper result and / or the records injected into the database; e) the file "[login to view URL]" must be provided to do a python installation in a virtual environment with the required dependencies. The code must be properly commented. More details by direct contact.