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---
## <div align=center>Support this package by donating here! ➡️ [](https://www.buymeacoffee.com/ishansurana) [](https://www.paypal.com/paypalme/ishansurana)</div><br>
# 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:
1. Import the `LoginlessScraper` or the `LoggedInScraper` class:
```python
from MetaDataScraper import LoginlessScraper, LoggedInScraper
```
2. Initialize the scraper with the Facebook page ID:
```python
page_id = "your_target_page_id"
scraper = LoginlessScraper(page_id)
email = "your_facebook_email"
password = "your_facebook_password"
scraper = LoggedInScraper(page_id, email, password)
```
3. Scrape the Facebook page to retrieve information:
```python
result = scraper.scrape()
```
4. Access the scraped data from the result dictionary:
```python
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](https://github.com/ishan-surana/MetaDataScraper/blob/main/LICENCE) file for details.
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