Shubham Published: November 3, 2022 · 3 minutes read

Web data scraping is the building block of many artificial intelligence applications today. Applications use web data scraping APIs to augment their datasets and operate with the most up-to-date data. Web data scraping API Python are easily automated and regularly feed the dataset with up-to-date data.

The increase in the data set improves the test processes in applications and ensures the creation of products with a very low error rate. At this point, the task of web data scraping APIs is quite large. Web data scraping APIs should regularly stream data unhindered. At the same time, the accuracy of the data scraped from the target websites should be high.

While the task of web data scraping APIs is so important, it is necessary to be careful in choosing a web scraping API, and choose the best one. Zenscrape provides the most popular API that offers web data scraping today. With the zenscrape API, users can obtain data from target websites with high accuracy and very quickly. Zenscrape has a very large IP pool and flexible proxy settings. For this reason, it does not cause any delays and blocks to its users in web scraping.

With more than 10,000 customers today, zenscrape supports all programming languages ​​and integrates quickly. Python programming language is generally used in web data scraping. In this article, we will talk about how we integrate the zenscrape web data scraping API into the Python programming language in a few short steps.

Integration zenscrape API to Python programming language

Before integrating the zenscrape API with the Python programming language, we need to obtain an API key to use the zenscrape API. From here we can see all the flexible and affordable packages that zenscrape has to offer, including the free packages. We choose one of these packages and register, and after registration we obtain an API key.

Then we create a file named ‘’ on the desktop. Paste the code below into the file we created.

You should write your own API key in the ‘apikey’ field.

import requests;

headers = {
  "apikey": "d5*****db"}

param = (

response = requests.get('', headers=headers, params=params);

Now we will download the ‘requests’ library. Let’s run the following command in our terminal.

pip install requests

Yes, everything looks ready now. We will scrape the data from the target website Let’s run the application with the following command.


After the application is running, we see that the following information is printed on the console screen of the application.

        <pre style="word-wrap: break-word; white-space: pre-wrap;">
                "origin": ""

As we will see from the response printed to the console, the zenscrape API scraped all the data of the target website without any incompleteness. The fact that it does the scraping process in just seconds without any obstacles is a very happy situation for the users.

Now let’s replace our url with and run the application again.

The scraped data after the application is running is as follows.

<html style="height: 100%;">
        <meta name="viewport" content="width=device-width, minimum-scale=0.1" />
        <title>html-tutorial-beginners-header.jpg (1280×592)</title>
    <body style="margin: 0px; background: #0e0e0e; height: 100%;">
        <img style="-webkit-user-select: none; margin: auto; background-color: hsl(0, 0%, 90%); transition: background-color 300ms;" src="" />


We have integrated it into the Python programming language in just a few short steps using the zenscrape API for web data scraping. To take a closer look at the world of web data scraping and get more detailed information, let’s take a look at the powerful documentation of the zenscrape API.