Python package to scrap facebook's pages front end with no limitations
Project description
Facebook Page Scraper
No registration, No need of API key, No limitation on number of requests. Import the library and Just Do It !
Prerequisites
- Internet Connection
- Python 3.6+
- Chrome or Firefox browser installed on your machine
Installation:
Installing from source:
git clone https://github.com/shaikhsajid1111/facebook_page_scraper
Inside project's directory
python3 setup.py install
Installing with pypi
pip3 install facebook-page-scraper
How to use?
#import Facebook_scraper class from facebook_page_scraper
from facebook_page_scraper import Facebook_scraper
#instantiate the Facebook_scraper class
page_name = "facebookai"
posts_count = 10
browser = "firefox"
facebook_ai = Facebook_scraper(page_name,posts_count,browser)
Parameters for Facebook_scraper(page_name,posts_count,browser)
class
Parameter Name | Parameter Type | Description |
page_name | string | name of the facebook page |
posts_count | integer | number of posts to scrap, if not passed default is 10 |
browser | string | which browser to use, either chrome or firefox. if not passed,default is chrome |
Done with instantiation?. Let the scraping begin!
For post's data in JSON format:
#call the scrap_to_json() method
json_data = facebook_ai.scrap_to_json()
print(json_data)
Output:
{
"1739843239525955": {
"name": "Facebook AI",
"shares": 43,
"reactions": {
"likes": 129,
"loves": 11,
"wow": 8,
"cares": 0,
"sad": 0,
"angry": 0,
"haha": 0
},
"reaction_count": 148,
"comments": 3,
"content": "We’re transitioning the Visdom project to the team at FOSSASIA. Visdom is a flexible tool for creating, organizing, and sharing visualizations of live, rich data. It aims to facilitate visualization of remote data with an emphasis on supporting scientific experimentation. We’re excited to see where the team, in collaboration with the developer and user community, take the project.",
"posted_on": "2021-01-05T17:22:54",
"video": "https://www.facebook.com/facebookai/videos/1739843239525955",
"image": [
"https://scontent-bom1-2.xx.fbcdn.net/v/t1.0-0/s526x296/135871741_1739843246192621_8564947121610203331_o.png?_nc_cat=108&ccb=2&_nc_sid=da1649&_nc_ohc=Hk7peLe8e-cAX_xLejp&_nc_ht=scontent-bom1-2.xx&_nc_tp=30&oh=856a17109cbc4a6657dbb68564dfc568&oe=60291FC7"
],
"post_url": "https://www.facebook.com/facebookai/posts/1739843239525955"
}, ...
}
Output Structure for JSON format:
{
"id": {
"name": string,
"shares": integer,
"reactions": {
"likes": integer,
"loves": integer,
"wow": integer,
"cares": integer,
"sad": integer,
"angry": integer,
"haha": integer
},
"reaction_count": integer,
"comments": integer,
"content": string,
"video" : string,
"image" : list,
"posted_on": datetime, //string containing datetime in ISO 8601
"post_url": string
}
}
For saving post's data directly to CSV file
#call scrap_to_csv(filename,directory) method
filename = "data_file" #file name without CSV extension,where data will be saved
directory = "E:\data" #directory where CSV file will be saved
facebook_ai.scrap_to_csv(filename,directory)
content of data_file.csv
:
id,name,shares,likes,loves,wow,cares,sad,angry,haha,reactions_count,comments,content,posted_on,video,image,post_url
1791700921006853,Facebook AI,45,150,19,5,0,0,0,0,174,8,"Facebook AI has built TimeSformer, an entirely new architecture for video understanding. It’s the first that’s based exclusively on the self-attention mechanism used in Transformers. TimeSformer outperforms the state of the art while being more efficient than 3D ConvNets for video.",2021-03-15T17:14:30,,https://scontent-bom1-2.xx.fbcdn.net/v/t39.2365-6/p540x282/156274680_471569777206221_706631440205169419_n.jpg?_nc_cat=110&ccb=1-3&_nc_sid=eaa83b&_nc_ohc=eyfETEUuHzQAX8DqwMU&_nc_ht=scontent-bom1-2.xx&tp=6&oh=2e9c6490fe3ad19a398905b3b615c88b&oe=6075FFE4,https://www.facebook.com/FacebookAI/posts/1791700921006853?__xts__%5B0%5D=68.ARCfsjOoZa0yc0TPws1koBr9ezS44Xf6Up04CqOhWnoDqrO35NdIdgjNSTWBrsUtm_y7MamZTjc_-p2rTobXe5WvxWd_eywuSzt98B7Vaj5hobF4OTZhe7VRgVJJY1wxEeAJf4nCZSs1tF1gWJJ0s5pPUGMmJsfD1UM5a3eERo-2t1JnTBHOSYs9Xsj5fV0iL-FiWAms_2-9KNRGqoojg9KfSAlffh_qxL8ztgznqC1sxfcU6MwAqdPN2va_T8cez29ZvJ1Er1j26VR7pnpWGyTMuW5wMrNxC-pz_8pVls8uk0iDramIOA&__tn__=-R
...
Parameters for scrap_to_csv(filename,directory)
method.
Parameter Name | Parameter Type | Description |
filename | string | name of the CSV file where post's data will be saved |
directory | string | directory where CSV file have to be stored. |
Keys of the outputs:
Key | Type | Description |
id | string | Post Identifier(integer casted inside string) |
name | string | Name of the page |
shares | integer | share count of post |
reactions | dictionary |
dictionary containing reactions as keys and its count as value. Keys => ["likes","loves","wow","cares","sad","angry","haha"]
|
reaction_count | integer | total reaction count of post |
comments | integer | comments count of post |
content | string | content of post as text |
video | string | URL of video present in that post |
image | list | python's list containing URLs of all images present in the post |
posted_on | datetime | time at which post was posted(in ISO 8601 format) |
post_url | string | URL for that post |
Privacy
This scraper only scrapes public data available to unauthenticated user and does not holds the capability to scrap anything private.
Tech
This project uses different libraries to work properly.
If you encounter anything unusual please feel free to create issue here
LICENSE
MITProject details
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