This project utilizes Selenium, Helium, and HTTP GET requests to retrieve user information from Facebook, Instagram, TikTok, and Twitter. It is crucial to note that such actions are in violation of the terms of service of these platforms. Consequently, it is crucial to proceed with caution when deploying these scripts.
Additionally, the project incorporates a wrapper for the Sherlock Project.
# clone the repo
$ git clone https://github.com/oscarmmv/social-crawler.git
# change the working directory to social crawler
$ cd social-crawler
- Project requires Google Chrome to be installed. (You can change to your perfered OS, please read WebDriver Documentation)
- Supported Operating Systems:
- win64
- macx64
- linuxx64
- if you are using an unsupported OS, download the appropriate chromium drivers from https://chromedriver.chromium.org and set the driver path
driver_path = "path-to-drivers/chromedriver-<your-operating-system>/chromedriver"
Import
# Install the required dependencies
# Import the scrape_facebook function into your Python script
from facebook_scraper import scrape_facebook
Usage
data = scrape_facebook(url)
Return Type The function returns a JSON object with the following structure:
data = {
"Name": "user_name",
"Status": "user_status",
"Bio": "user_bio",
"Followers": followers_count,
"Likes": likes_count,
"Email": "user_email",
"Links": ["link_1", "link_2", ...]
}
Import
# Install the required dependencies
# Import the scrape_instagram_user function into your Python script
from instagram_scraper import scrape_instagram_user
Usage
data = scrape_instagram_user(url)
Return Type The function returns a JSON object with the following structure:
data = {
"Name": "user_name",
"Followers": followers_count,
"Following": following_count,
"Posts": post_count
}
# Install the required dependencies
# Import the scrape_tiktok_profile function into your Python script
from tiktok_scraper import scrape_tiktok_profile
Usage
data = scrape_tiktok_profile(url)
Return Type The function returns a JSON object with the following structure:
data = {
"Name": "name",
"Username": "user_name",
"Bio": "user_bio",
"Link": link,
"Followers": follower_count,
"Following": following_count,
"Like_Count": like_count
}
Import
# Install the required dependencies
# Import the scrape_twitter_profile function into your Python script
from twitter_scraper import scrape_twitter_profile
Usage
# !!!Set username and password!!!
data = scrape_twitter_profile(url)
Return Type The function returns a JSON object with the following structure:
data = {
"Name": "name",
"Bio": "user_bio",
"Followers": follower_count,
"Following": following_count,
"Account Age": account_age,
"Link": link,
}
This is a wrapper for the Sherlock Project
Usage
# Install the required dependencies
# run the tracker.py script
python3 tracker.py
Input:"username" ---> returns all social media accounts associated to that username