Scrapy Sage-Scrapy Sage Python Web Scraping

Example

scrapy startproject example_project

Scenario

A user new to Scrapy wants to begin a new web scraping project. Scrapy Sage can guide through creating a new Scrapy project, structuring the project, and setting up necessary configurations to start scraping websites.

Example

class ExampleSpider(scrapy.Spider): name = 'example' start_urls = ['http://example.com'] def parse(self, response): title = response.css('h1::text').get() yield {'title': title}

Scenario

A researcher needs to collect data from several academic websites. Scrapy Sage can assist in crafting a spider to navigate and parse web pages, extract specific data like paper titles and publication dates, and store this data for further analysis.

Example

Using Scrapy-Splash or Scrapy-Playwright to handle websites that load data with JavaScript, enabling dynamic interaction and scraping of content not immediately available in the raw HTML.

Scenario

A data analyst needs data from a dynamic web application that loads content asynchronously. Scrapy Sage explains how to integrate Scrapy with browser-based tools to manage such sites, ensuring the scraper can access and extract the needed data.

Example

class ExamplePipeline: def process_item(self, item, spider): # Process or transform the item here return item

Scenario

An e-commerce business wants to regularly update its database with price changes from competitor websites. Scrapy Sage can help set up and customize data pipelines to clean, validate, and store scraped data into a database efficiently.