Start Your Project with Us

Whatever your project size is, we will handle it well with all the standards fulfilled! We are here to give 100% satisfaction.

  • Any feature, you ask, we develop
  • 24x7 support worldwide
  • Real-time performance dashboard
  • Complete transparency
  • Dedicated account manager
  • Customized solutions to fulfill data scraping goals
Careers

For job seekers, please visit our Career Page or send your resume to hr@actowizsolutions.com

How-to-Scrape-Netflix-Data-with-Python.jpg

Netflix is an OTT platform where it’s easy to watch unlimited movies and Shows. You can extract Netflix data to collect all episode names, ratings, cast, plan pricing, similar shows, etc. With this data, it’s easy to analyze what the users watch these days, and it will help in sentiment analysis.

We will use Python here to scrape Netflix data. We assume that you have installed Python on your PC. Let’s start with data scraping now!

Scrape Netflix Data

To start here, we will make a folder to install the different libraries we need during this tutorial.

Here, we will install a couple of libraries

1. Requests will assist us in making an HTTP connection using Netflix.

2. BeautifulSoup will assist us in making an HTML tree to get smooth data scraping.

BeautifulSoup.jpg

We will extract Netflix page data. Within this folder, it’s easy to make a Python file where we would write the code. Our interest would be:

1.jpg 2.jpg 3.jpg
  • Name of show
  • Total seasons
  • Subject
  • Episode Names
  • Genre
  • Episode Overview
  • Category
  • Cast
  • Social media links

We understand this is a longer data list; however, in the end, you will get a readymade code to scrape Netflix data for any page.

Let’s find the locations of all these elements

4.jpg

The title gets stored under the h1 tag of a class title-title.

5.jpg

Total seasons get stored under the span tag in a duration class.

6.jpg

The about segment gets stored under the div tag in a class hook-text.

7.jpg

The episode’s title gets stored under the p tag having class episode-synopsis.

8.jpg

Genre gets stored under the span tag having class item-genres.

9.jpg

The show category data gets stored under the span tag having a class item-mood-tag.

10.jpg

Social Media links could be available under the tag having a class name called social-link.

11.jpg

The cast gets stored under the span tag having class item-cast.

Let’s begin with making the regular GET requests to the targeted webpage and observe what happens.

Lets-begin-with-making-the-regular-GET-requests.jpg

If you find 200, then you have successfully extracted our targeted page. Now, let’s scrape details from this data with BeautifulSoup.

If-you-find-200-then-you-have-successfully-extracted.jpg

Let us initially scrape all data properties in sequence. As discussed here, we would be using similar HTML locations.

Let-us-initially-scrape-all-data-properties-in-sequence.jpg

Now, let’s scrape the episode data.

Now-lets-scrape-the-episode-data.jpg

The whole data is within ol tag. Therefore, we initially get the ol tag and all li tags within it. After that, we utilized a loop to scrape title & description data.

Now, let’s scrape the genre data.

Now-lets-scrape-the-genre-data.jpg

The genre could be available under the class item-genre. Here, we have utilized a loop to scrape all genres.

Let’s scrape the rest of the data properties having similar techniques.

Lets-scrape-the-rest-of-the-data-properties-having-similar-techniques.jpg We-have-managed-to-scrape-all-the-data-from-Netflix.jpg

We have succeeded in extracting all data from Netflix.

Complete Code

Complete-Code.jpg

Using this code, we have extracted Name, Seasons name, Subject, Genre, Mood, Cast, Social links, etc. By making some changes in this code, you can scrape data from Netflix.

Conclusion

You can utilize Web Scraping API for scraping data from Netflix without being blocked. This is a fast way to scrape complete Netflix pages. By changing a show title ID you can extract nearly all shows from Netflix. You need to get IDs of these shows. Instead of BS4, you can use Xpath for creating HTML tree for web scraping services.

We hope you have liked this small tutorial about scraping Netflix data. Let us know if you want any help with your web extraction and Mobile App Scraping Services demands.

RECENT BLOGS

View More

How Can You Scrape Google Maps POI Data Without Getting Blocked?

Learn effective techniques to Scrape Google Maps POI Data safely, avoid IP blocks, and gather accurate location-based insights for business or research needs.

How to Build a Scalable Amazon Web Crawler with Python in 2025?

Learn how to build a scalable Amazon web crawler using Python in 2025. Discover techniques, tools, and best practices for effective product data extraction.

RESEARCH AND REPORTS

View More

Research Report - Grocery Discounts This Black Friday 2024: Actowiz Solutions Reveals Key Pricing Trends and Insights

Actowiz Solutions' report unveils 2024 Black Friday grocery discounts, highlighting key pricing trends and insights to help businesses & shoppers save smarter.

Analyzing Women's Fashion Trends and Pricing Strategies Through Web Scraping Gucci Data

This report explores women's fashion trends and pricing strategies in luxury clothing by analyzing data extracted from Gucci's website.

Case Studies

View More

Case Study - Revolutionizing Global Tire Business with Tyre Pricing and Market Intelligence

Leverage tyre pricing and market intelligence to gain a competitive edge, optimize strategies, and drive growth in the global tire industry.

Case Study: Data Scraping for Ferry and Cruise Price Optimization

Explore how data scraping optimizes ferry schedules and cruise prices, providing actionable insights for businesses to enhance offerings and pricing strategies.

Infographics

View More

Crumbl’s Expansion: Fresh Locations, Fresh Cookies

Crumbl is growing sweeter with every bite! Check out thier recently opened locations and see how they are bringing their famous cookies closer to you with our web scraping services. Have you visited one yet

How to Use Web Scraping for Extracting Costco Product Specifications?

Web scraping enables businesses to access and analyze detailed product specifications from Costco, including prices, descriptions, availability, and reviews. By leveraging this data, companies can gain insights into customer preferences, monitor competitor pricing, and optimize their product offerings for better market performance.