Metadata-Version: 2.1
Name: SiteScraper
Version: 0.2.2
Summary: Scraping high intensity content sites
Author: Ibrahim
Author-email: string2025@gmail.com
Description-Content-Type: text/markdown
Requires-Dist: selenium

# SiteScraper

This repository contains the following methods:

## 'yt_vedio()'
This method uses Selenium and Firefox web driver to scrape YouTube videos' title, views, and upload time from a given URL. It returns a dictionary with keys 'title', 'views', and 'when', and corresponding values.

## 'yt_vedio_comment()'
This method uses Selenium and Firefox web driver to scrape YouTube comments' text, likes, and time posted from a given URL. It returns a Pandas DataFrame with columns 'comment_text', 'likes', and 'comment_time', and corresponding values.

To use these methods, you will need to have Python 3 installed, along with the following libraries: pandas, selenium, and geckodriver-autoinstaller.

To install the required libraries, you can use pip:


pip install pandas selenium geckodriver-autoinstaller


To run the methods, you will need to import the SiteScraper module and create an instance of the 'yt_vedio' or 'yt_vedio_comment' class:


import SiteScraper as ss

# create an instance of yt_vedio class
```
import SiteScraper as ss
import pandas as pd 
df = ss.yt_vedio()
new_data = df.yt_vedios_data('https://www.youtube.com/@campusx-official/videos')
dataframe = pd.DataFrame(new_data)
dataframe.to_csv('campusx.csv', index=False)
```

# create an instance of yt_vedio_comment class
```
import SiteScraper as ss
import pandas as pd 
df = ss.yt_vedio_comment()
new_data = df.yt_vedio_comment('https://www.youtube.com/watch?v=xxxxxxxx')
dataframe = pd.DataFrame(new_data)
dataframe.to_csv('youtube_comments.csv', index=False)
```


Note that you will need to replace the URL with the actual YouTube URL that you want to scrape.
#New methods will be commited for twitter and reddit 
