There are many different scraping frameworks that can be used to scrape tables from websites. Here are a few popular ones with examples:<ol><li>Beautiful Soup (Python): Beautiful Soup is a Python library that is used for web scraping purposes to pull the data out of HTML and XML files.</li></ol>Example:<pre class="ql-syntax" spellcheck="false">python

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import requests from bs4 import BeautifulSoup url = "https://www.example.com/table" response = requests.get(url) soup = BeautifulSoup(response.text, "html.parser") table = soup.find("table") for row in table.find_all("tr"): cells = row.find_all("td") if len(cells) &gt; 0: print(cells[0].text, cells[1].text)
</pre><ol><li>Scrapy (Python): Scrapy is an open-source and collaborative web crawling framework for Python. It is used to extract the data from websites and store it in a structured format.</li></ol>Example:<pre class="ql-syntax" spellcheck="false">css

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import scrapy class TableSpider(scrapy.Spider): name = "table_spider" start_urls = [ "https://www.example.com/table" ] def parse(self, response): for row in response.css("table tr"): yield { "cell_1": row.css("td:nth-child(1) ::text").get(), "cell_2": row.css("td:nth-child(2) ::text").get(), }
</pre><ol><li>Cheerio (JavaScript): Cheerio is a fast, flexible, and lean implementation of core jQuery designed specifically for the server. It allows you to extract data from an HTML document with a similar syntax as jQuery.</li></ol>Example:<pre class="ql-syntax" spellcheck="false">javascript

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const cheerio = require("cheerio"); const axios = require("axios"); async function scrapeTable() { const response = await axios.get("https://www.example.com/table"); const $ = cheerio.load(response.data); $("table tr").each(function() { console.log($(this).find("td").eq(0).text(), $(this).find("td").eq(1).text()); }); } scrapeTable();
</pre>These are just a few examples of the many scraping frameworks that can be used to scrape tables. The choice of framework will depend on the specific requirements of the project, such as the language you prefer to code in, the complexity of the data you need to scrape, and the performance requirements of the project.

There are many different scraping frameworks that can be used to scrape tables from websites. Here are a few popular ones with examples:  Beautiful Soup (Python): Beautiful Soup is a Python library that is used for web scraping purposes to pull the data out of HTML and XML files. Example:  python Copy code import requests from bs4 import BeautifulSoup  url = "https://www.example.com/table"  response = requests.get(url) soup = BeautifulSoup(response.text, "html.parser") table = soup.find("table")  for row in table.find_all("tr"):     cells = row.find_all("td")     if len(cells) > 0:         print(cells[0].text, cells[1].text) Scrapy (Python): Scrapy is an open-source and collaborative web crawling framework for Python. It is used to extract the data from websites and store it in a structured format. Example:  css Copy code import scrapy  class TableSpider(scrapy.Spider):     name = "table_spider"     start_urls = [         "https://www.example.com/table"     ]          def parse(self, response):         for row in response.css("table tr"):             yield {                 "cell_1": row.css("td:nth-child(1) ::text").get(),                 "cell_2": row.css("td:nth-child(2) ::text").get(),             } Cheerio (JavaScript): Cheerio is a fast, flexible, and lean implementation of core jQuery designed specifically for the server. It allows you to extract data from an HTML document with a similar syntax as jQuery. Example:  javascript Copy code const cheerio = require("cheerio"); const axios = require("axios");  async function scrapeTable() {     const response = await axios.get("https://www.example.com/table");     const $ = cheerio.load(response.data);     $("table tr").each(function() {         console.log($(this).find("td").eq(0).text(), $(this).find("td").eq(1).text());     }); }  scrapeTable(); These are just a few examples of the many scraping frameworks that can be used to scrape tables. The choice of framework will depend on the specific requirements of the project, such as the language you prefer to code in, the complexity of the data you need to scrape, and the performance requirements of the project. | blogue

Scraping Tables with various scraper frameworks with examples

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