Web-Scraping | Web Scraping with Beautiful Soup and Selenium | Scraper library

Here i am trying to create a list of physiotherapist from German yellow pages. The actual number are 90+ and here i am getting 52, where 50 of them are the list and 2 of them are unwanted items. The yellow markings are the unwanted items. How can i remove those from the list and expand it all so that i get all the list from that page.

web_address ='https://www.gelbeseiten.de/Suche/Physiotherapie%20praxis/Rostock'

I've created a script to parse the titles and their associated links from a webpage and write the same to an excel file using openpyxl library. The script is doing fine. However, what I can't do is draw border around the cells the results to be written.

I've tried so far:

I'm new in Node.js programmation and I need someone for help. I'm developing a web-scraping program and I'm using puppeteer; my problem is that I need a function for counting the number of pharmacy so I'm using the function:

I have a request for you.

I wanna to scrape the following product https://www.decathlon.it/p/kit-manubri-e-bilanciere-bodybuilding-93kg/_/R-p-10804?mc=4687932&c=NERO#

The prodcuts have two possible status:

1. "ATTUALMENTE INDISPONIBILE"
2. "Disponibile"

In a nutshell I wanna to create a script that monitors for all minutes if the product is available, recording all data in the shell.

The output could be the following:

I am hoping someone can please help me out and put me out of my misery. I have recently started to learn Python and wanted to challenge myself with some web-scraping.

Over the past couple of days I have been trying to web-scrape this website (https://ebn.eu/?p=members). On the website, I am interesting in:

1. Clicking on each logo image which brings up a pop-up
2. From the pop-up scrape the link which is behind the text "VIEW FULL PROFILE"
3. Move to the next logo and do the same for each

I have managed to get Selenium up and running but the issue is that it keeps opening the first logo and copying the same link as opposed to moving to the next one. I have tried in various different ways but came up against a brick wall.

My code so far:

According to the reply I found in my previous question, I am able to grab the table by web scraping in Python from the URL: https://www.nytimes.com/interactive/2021/world/covid-vaccinations-tracker.html But it only grabs partially until the row "Show all" is appeared.

How can I grab the complete table in Python which is hidden beyond "Show all" ?

Here is the code I am using:

I am trying to read the content of the following webpage (as shown in the Inspect Element tool of my browser) into R:

Etoro Discover People

Since the content is apparently Javascript-rendered, it is not possible to retrieve content by using common web scraping functions like read_html from xml2 package. I have come across the following post that suggests using rvest and V8 packages, but I could not get it to work for my problem:

https://datascienceplus.com/scraping-javascript-rendered-web-content-using-r/

I have also seen very similar questions on Stack Overflow (like this and this), but the answers to those questions (the hidden api solution and the Request URL in the Network tab) did not work for me.

For starters, I am interested in reading the public ID of people in the list (the div.user-nickname node). My guess is that either I am specifying the node incorrectly or the website does not allow web scraping at all.

Any help would be greatly appreciated.

I am scraping a grocery website (https://www.paknsaveonline.co.nz) to do some meal planning before I shop. The price of products varies with the location of the store. I want to extract prices from my local store (Albany).

I am new to web-scraping, but I am assuming my code must

1. change the default store to my local store (Albany, using this url: https://www.paknsaveonline.co.nz/CommonApi/Store/ChangeStore?storeId=65defcf2-bc15-490e-a84f-1f13b769cd22)
2. maintain a single requests "session", to ensure I scrape all of my products from the same store site.

My scraping code successfully scrapes the price of broccoli, but the price does not align with the price from my local store. At the time of posting my scraped price for broccoli is $1.99, but when I manually check the price at the Albany store, the price is $0.99. I assume my code to switch to the correct store isn't working as intended.

Can anyone point out what I am doing wrong and suggest a solution?

Environment details:

• requests==2.23.0
• beautifulsoup4==4.6.3
• Python 3.7.10

Code below, with an associated link to Google Colab file.

how to create and refresh index in pymongo to speed up update queries. As mentioned in the article[1] section, the following is code works fine for small set of entries