A module designed to automate the extraction of follower counts and post details from a public Facebook page.
Project description
MetaDataScraper
MetaDataScraper is a Python package designed to automate the extraction of information like follower counts, and post details & interactions from a public Facebook page, in the form of a list. It uses Selenium WebDriver for web automation and scraping.
The module provides two classes: LoginlessScraper
and LoggedInScraper
. The LoginlessScraper
class does not require any authentication or API keys to scrape the data. However, it has a drawback of being unable to access some Facebook pages.
The LoggedInScraper
class overcomes this drawback by utilising the credentials of a Facebook account (of user) to login and scrape the data.
Installation
You can install MetaDataScraper using pip:
pip install MetaDataScraper
Make sure you have Python 3.x and pip installed.
Usage
To use MetaDataScraper, follow these steps:
-
Import the
LoginlessScraper
or theLoggedInScraper
class:from MetaDataScraper import LoginlessScraper, LoggedInScraper
-
Initialize the scraper with the Facebook page ID:
page_id = "your_target_page_id" scraper = LoginlessScraper(page_id) email = "your_facebook_email" password = "your_facebook_password" scraper = LoggedInScraper(page_id, email, password)
-
Scrape the Facebook page to retrieve information:
result = scraper.scrape()
-
Access the scraped data from the result dictionary:
print(f"Followers: {result['followers']}") print(f"Post Texts: {result['post_texts']}") print(f"Post Likes: {result['post_likes']}") print(f"Post Shares: {result['post_shares']}") print(f"Is Video: {result['is_video']}") print(f"Video Links: {result['video_links']}")
Features
- Automated Extraction: Automatically fetches follower counts, post texts, likes, shares, and video links from Facebook pages.
- Comprehensive Data Retrieval: Retrieves detailed information about each post, including text content, interaction metrics (likes, shares), and multimedia (e.g., video links).
- Flexible Handling: Adapts to diverse post structures and various types of multimedia content present on Facebook pages, like post texts or reels.
- Enhanced Access with Logged-In Scraper: Overcomes limitations faced by anonymous scraping (loginless) by utilizing Facebook account credentials for broader page access.
- Headless Operation: Executes scraping tasks in headless mode, ensuring seamless and non-intrusive data collection without displaying a browser interface.
- Scalability: Supports scaling to handle large volumes of data extraction efficiently, suitable for monitoring multiple Facebook pages simultaneously.
- Dependency Management: Utilizes Selenium WebDriver for robust web automation and scraping capabilities, compatible with Python 3.x environments.
- Ease of Use: Simplifies the process with straightforward initialization and method calls, facilitating quick integration into existing workflows.
Dependencies
- selenium
- webdriver_manager
License
This project is licensed under the Apache Software License Version 2.0 - see the LICENSE file for details.
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