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Plan comparison chart
Feature | Free | Pro 1 Day | Pro Monthly |
No. of films per file | 5 | 50 | 50 |
Max. no. of file uploads processed | 5 | 20 | 20 |
Trusted User Benefits (Bypass reCAPTCHA) | No | Yes | Yes |
Use Sedona Bulk Movie Metadata IMDB Tool to obtain movie ratings and additional information from IMDb and TMDb in batch or bulk.
Example file upload sample template
01. International Films 20240811084215.docx
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-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)
-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)-(_)
Related helpful articles around the web for reference
Why Scrape IMDb?

IMDb is a widely recognized repository of entertainment data, containing extensive and varied information on movies, TV shows, and video games. It offers details such as movie summaries, cast lists, ratings, trivia, related titles, awards, and user-generated reviews. This rich data can be utilized for various applications including market research, movie recommendation systems, and strategic marketing efforts. Additionally, user reviews provide valuable insights for sentiment analysis, enhancing our understanding of audience preferences.
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Setting Up for
IMDb Scraping
To start scraping IMDb using Python, ensure you have Python 3.8 or later installed. This guide assumes you’re using Python 3.8+.
Creating a Virtual Environment
A virtual environment isolates project dependencies, preventing them from affecting your global Python setup. Create one with the following commands:
- For Windows:
python -m venv imdb_env
- For Mac and Linux:
python3 -m venv imdb_env
Activating the Virtual Environment
Activate the environment with:
- For Windows:
.\imdb_env\Scripts\Activate
- For Mac and Linux:
source imdb_env/bin/activate
You should see the environment’s name in the terminal, indicating it’s active.
Installing Required Libraries
Install the requests library for HTTP requests and pandas for data manipulation:
pip install requests pandas
Your project environment is now ready for IMDb data scraping. Next, we’ll explore the structure of IMDb data.
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Overview of the Web Scraper API
Oxylabs’ Web Scraper API simplifies data extraction from complex websites. Here’s a basic example of how it works:
print(response.json())
Replace the credentials with those from your Web Scraper API subscription or free trial. The payload specifies what and how to scrape.
Save this code as scraper_api_demo.py and run it to see the full HTML of the page along with additional Scraper API information.
Scraper API Parameters
The crucial parameter is source. Set this to universal for IMDb. The url parameter should be the direct link to the IMDb page you’re scraping. To get parsed data, set parse to True and provide parsing_instructions. For instance, to get a JSON of the page title:
{‘title’: ‘IMDb Top 250 Movies’}
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Scraping Movie Information from a List
Inspect the IMDb Top 250 list in Chrome, right-click the movie list, and select “Inspect” to examine the page structure. Use the XPath:
//li[contains(@class,’ipc-metadata-list-summary-item’)]
Create placeholders for movies and use XPath to iterate over items to extract titles, years, and ratings.
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Using BeautifulSoup for IMDb Scraping
To scrape IMDb movie ratings and details using Python, you’ll need:
- requests: For HTTP requests.
- html5lib: For parsing HTML.
- bs4 (BeautifulSoup): For scraping and parsing HTML.
- pandas: For data manipulation.
Steps to Implement Web Scraping:
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Import Required Modules
: Use the necessary libraries for scraping.
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Scrape Data
: Fetch and process the IMDb data using BeautifulSoup.
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Save Data
: Store the scraped information in a .csv file.
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Legal and API Considerations
Legality of Scraping IMDb
: Generally, web scraping is legal, but some sites have specific rules. IMDb allows content use for non-commercial purposes. Check IMDb’s Conditions of Use for details. Extensive or commercial-scale scraping is typically prohibited without permission.
IMDb API
s
: IMDb offers four APIs for accessing various types of data, including titles, performers, and ratings. These APIs are available on the AWS Marketplace, though they can be expensive. A one-month free trial is available for evaluation.
Types of Data You Can Extract:
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Title Details
: Basic information like title, year, genre, etc.
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Cast & Crew
: Lists of actors, directors, and producers.
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Biographies
: Profiles of cast and crew.
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Images
: Posters and other media.
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Release Dates
: Domestic and international release information.
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Awards & Nominations
: Awards won or nominated.
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User Ratings & Reviews
: User-submitted ratings and reviews.
Benefits of Scraping IMDb Data:
-
Market Research
: Understand industry trends and market preferences.
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Sentiment Analysis
: Analyze user reviews to gauge audience sentiment.
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Personal Database
: Create a custom database for personal use.
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Scraping IMDb Data Without Coding
Tools like Octoparse can scrape IMDb data without coding. Follow these steps:
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Create a Task
: Enter the target URL.
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Select Data Fields
: Use auto-detection to identify data.
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Create a Workflow
: Configure data extraction steps.
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Scrape Data
: Extract data from detail pages.
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Run and Export
: Execute the task and export data as needed.
Octoparse also offers preset templates for IMDb data scraping.
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Scraping IMDb Data with Python
You can use Python to gather movie details such as names, release dates, and directors. Sample Python code is available for extracting this information.
Wrap-Up
IMDb is a valuable resource for media enthusiasts and researchers. Its extensive data can be accessed programmatically for detailed insights or scraped using tools for those without coding experience. Whether you’re interested in market trends, sentiment analysis, or personal data management, scraping IMDb can provide valuable information efficiently.