Scrape a JS Lazy load page by Python requests

The JS loading page is usually scraped by Selenium or another browser emulator. Yet, for a certain shopping website we’ve
found a way to perform a pure Python requests scrape.

NetNut.io Review

The most successful enterprises are always the ones which manage to stay a step ahead of their rivals. And to remain ahead, you have to be able to access the industry information faster and more consistently than anybody else. This is especially true for e-commerce and online retail industries, where the pricing contest is extremely fierce. Thus, the smallest developments in information processes can result in large changes in the outcomes.

What is legal: scrape, or scrape & sell, or code a scraper

Which of the following is illegal:
(1) Scrape emails from a site and send one email to each address.
(2) Scrape emails from a website and sell them.
(3) Make a scraping script a sell it without using it.
Note: The target website Terms of Use (ToU) state that no one can crawl/scrape it.

Netpeak Software sales and offers

If you haven’t meet Netpeak Spider and Checker yet, let us explain to you why it worth your attention. These tools help SEOs and webmasters with in-depth SEO auditing, website and search engine scraping, comprehensive analysis, data aggregation from top SEO services (Ahrefs, Moz, SimilarWeb, Whois,…), and many more.Netpeak (April 2020 Special Offer)

Bulk db prepared insert with rollback even if 1 record fails, PHP

Recently I needed to make a bulk insert into db with   prepared statement query. The task was to do it so that if one record failed one can rollback all records and return an error. That way no data is affected by faulty code and/or wrong data provided.

ScrapingBee, an API for web scraping

scrapingbee_smallThe web is becoming increasingly difficult to scrape. There are more and more websites using single page application frameworks like Vue.js / Angular.js / React.js and you need to use headless browsers to extract data from those websites.

Using headless Chrome on your local computer is easy. But scaling to dozens of Chrome instances in production is a difficult task. There are many problems, you need powerful servers with plenty of RAM, you’ll get into random crashes, zombie processes…

Problem scraping javascript site – help needed

Problem

I am trying to scrape the page https://tienda.mercadona.es/categories/112 and I have installed the docker and followed all the required steps given in the post. Splash works well, but the spyder does not and I don’t know why. The IP of the splash_url is correct but I can’t see in the response object when I write scrapy shell “webpage” the complete page, ie, the page has not rendered correctly.

Choosing affordable residential proxies for web scraping

Proxies are an integrated part of most major web scraping and data mining projects. Without them, data collection becomes sloppy and biased. This is why it’s essential to know how to find the best affordable proxies for any web scraping project.

One of the best proxy types you could use for scraping is residential proxies. In this post, you’ll learn what they are, how they are priced and what to look for before committing your project’s budget.

Scrape text, parse it with BeautifulSoup and save it as Pandas data frame

We want to share with you how to scrape text and store it as Pandas data frame using BeautifulSoup (Python). The code below works to store html li items in the ‘engine, ‘trans’, ‘colour’ and ‘interior’ columns.

from bs4 import BeautifulSoup
import pandas as pd
import requests

main_url = "https://www.example.com/"

def getAndParseURL(url):
    result = requests.get(url)
    soup = BeautifulSoup(result.text, 'html.parser')
    return(soup)

soup = getAndParseURL(main_url) 
ul = soup.select('ul[class="list-inline lot-breakdown-list"] li', recursive=True)
lis_e = []
for li in ul:
    lis = []
    lis.append(li.contents[1])
    lis_e.extend(lis)

engine.append(lis_e[0])
trans.append(lis_e[1])
colour.append(lis_e[2])
interior.append(lis_e[3])

scraped_data = pd.DataFrame({'engine': engine, 
'transmission': trans, 'colour': colour,
'interior': interior})
By default, Beautiful Soup searches through all of the child elements. So, setting recursive = False (line 13) will restrict the search to the first found element and its child only.

The code was provided by Ahmed Soliman.

What is a Web Crawler and how does it work?

Nowadays, when having some questions, it almost comes naturally for us to just type it in a search bar and get helpful answers. But we rarely wonder how all that information is available and how it appears as soon as we start typing. Search engines provide easy access to information, but web crawling/scraping tools who are not so much known players have a crucial role in wrapping up online content. Over the years, these tools have become a true game-changer in many businesses including e-commerce. So, if you are still unfamiliar with it, keep reading to learn more.