Web Scraping TikTok with Python




Web Scraping TikTok with Python

This tutorial demonstrates web scraping with Python. It is divided into two parts: one for scraping TikTok video URLs and the other for scraping hashtags.


Table of Contents


Introduction to Web Scraping
Web Scraping vs. Web Crawling
Installing BeautifulSoup
Part 1: Scraping for TikTok Video Links
Part 2: Scraping for TikTok Hashtags

Introduction to Web Scraping

Web scraping is the process of extracting data from websites. It involves sending HTTP requests to a website’s server, receiving the response, and parsing the HTML content to extract the desired information.

Web scraping can be done manually by a human user, but it is usually automated using software tools such as web crawlers or bots. These tools can send requests and parse responses much faster than a human user, allowing large amounts of data to be extracted in a short amount of time.

Web Scraping vs. Web Crawling

Web scraping and web crawling are related but distinct concepts. Web crawling refers to the process of automatically navigating through a website by following links, usually for the purpose of indexing its content. Web scraping, on the other hand, refers to the extraction of specific data from a website.

In other words, web crawling is about discovering and navigating through web pages, while web scraping is about extracting data from those pages.

Installing BeautifulSoup

BeautifulSoup is a Python library that makes it easy to parse HTML and XML documents. It provides methods to search, navigate, and modify the parse tree.

To install BeautifulSoup, you can use the pip command:

pip install beautifulsoup4

 

This command installs the latest version of BeautifulSoup from the Python Package Index (PyPI). You can find more information on how to install BeautifulSoup in the official documentation.

After installing BeautifulSoup, you can import it in your Python code using the following statement:

from bs4 import BeautifulSoup

 

Part 1: Scraping for TikTok Video Links

In the first part, the code imports necessary libraries such as urllib.requestrequestsretime, and BeautifulSoup from the bs4 library. Then, it opens a file named tiktoknaillinks.txt in write mode with utf-8 encoding.

The code then reads a file named tiktokmainlinks.txt line by line. For each line, it treats the line as a URL and uses urllib.request.urlopen(url).read() to get the HTML content of the page. The HTML content is then parsed using BeautifulSoup with the html.parser.

The code then uses the find_all method of the soup object to find all strong tags with a specific class name (tiktok-23vhki-StrongText ejg0rhn2). This class name is obtained by right-clicking on the video and looking for the tag strong that has the link of the video as text. If you are confused, you might have to watch YouTube videos on web scraping.

For each link found, the code writes its text to the file tiktoknaillinks.txt. After all links are processed, the file is closed and a message “done” is printed.

Here is a detailed explanation of each line of code in this part:

import urllib.request

import requests

import re

import time

from bs4 import BeautifulSoup

 

These lines import necessary libraries for web scraping such as urllib.requestrequestsretime, and BeautifulSoup from the bs4 library.

f = open('tiktoknaillinks.txt','w',encoding ="utf-8")

 

This line opens a file named tiktoknaillinks.txt in write mode with utf-8 encoding. The file will be used to store links to TikTok videos.

with open('tiktokmainlinks.txt','r') as fa:

    for line in fa:

        url = line

        html = urllib.request.urlopen(url).read()

        soup = BeautifulSoup(html, 'html.parser')

        links = soup.find_all('strong',class_='tiktok-23vhki-StrongText ejg0rhn2')

 

These lines read a file named tiktokmainlinks.txt line by line. For each line, it treats the line as a URL and uses urllib.request.urlopen(url).read() to get the HTML content of the page. The HTML content is then parsed using BeautifulSoup with the html.parser.

The code then uses the find_all method of the soup object to find all strong tags with a specific class name (tiktok-23vhki-StrongText ejg0rhn2). This class name is obtained by right-clicking on the video and looking for the tag strong that has the link of the video as text. If you are confused, you might have to watch YouTube videos on web scraping.

for i in links:

    f.write(i.text)

    f.write('\n')

 

These lines iterate over each link found and write its text to the file tiktoknaillinks.txt. A newline character is also written after each link.

f.close()

print('done')

 

These lines close the file and print a message “done” to indicate that the process is complete.

Part 2: Scraping for TikTok Hashtags

In the second part, the code again imports necessary libraries and opens a file named tiktokmainlinks.txt in write mode with utf-8 encoding. It then defines a URL for a TikTok hashtag page and uses urllib.request.urlopen(url).read() to get its HTML content.

The HTML content is again parsed using BeautifulSoup with the html.parser. The code then uses the find_all method of the soup object to find all div tags with a specific class name (tiktok-yvmafn-DivVideoFeedV2 ecyq5ls0). This class name is obtained by right-clicking on the video and looking for the tag div that has the hashtag of the video as text. If you are confused, you might have to watch YouTube videos on web scraping.

For each link found, the code finds all a tags with an attribute href that matches a regular expression for URLs starting with “https:”. For each matching tag, it gets its href attribute value and writes it to the file tiktokmainlinks.txt. After all links are processed, the file is closed and a message “done” is printed.

Here is a detailed explanation of each line of code in this part:

import urllib.request

import requests

import re

import time

from bs4 import BeautifulSoup

 

These lines again import necessary libraries for web scraping such as urllib.requestrequestsretime, and BeautifulSoup from the bs4 library.

f = open('tiktokmainlinks.txt','w',encoding ="utf-8")

 

This line opens a file named tiktokmainlinks.txt in write mode with utf-8 encoding. The file will be used to store links to TikTok hashtags.

url = "https://www.tiktok.com/tag/nailart"

html = urllib.request.urlopen(url).read()

soup = BeautifulSoup(html, 'html.parser')

link = soup.find_all('div',{'class':'tiktok-yvmafn-DivVideoFeedV2 ecyq5ls0'})

 

These lines define a URL for a TikTok hashtag page and use urllib.request.urlopen(url).read() to get its HTML content. The HTML content is then parsed using BeautifulSoup with the html.parser.

The code then uses the find_all method of the soup object to find all div tags with a specific class name (tiktok-yvmafn-DivVideoFeedV2 ecyq5ls0). This class name is obtained by right-clicking on the video and looking for the tag div that has the hashtag of the video as text. If you are confused, you might have to watch YouTube videos on web scraping.

for i in link:

    iref = i.find_all('a',attrs ={'href':re.compile("https:")})

    for t in iref :

        f.write(t.get('href')

        f.write('\n')

 

These lines iterate over each link found and find all a tags with an attribute href that matches a regular expression for URLs starting with “https:”. For each matching tag, it gets its href attribute value and writes it to the file tiktokmainlinks.txt. A newline character is also written after each link.

f.close()

print('done')

 

These lines again close the file and print a message “done” to indicate that the process is complete.

In summary, this code demonstrates how to use web scraping techniques in Python to extract information from web pages. In this case, it extracts links to TikTok videos and their associated hashtags. <

 


 Tiktokscrapmain:

import urllib.request

import requests

import re

import time

from bs4 import BeautifulSoup

f = open('tiktoknaillinks.txt','w',encoding ="utf-8")

with open('tiktokmainlinks.txt','r') as fa:

    for line in fa:

        url = line

        html = urllib.request.urlopen(url).read()

        soup = BeautifulSoup(html, 'html.parser')

        links = soup.find_all('strong',class_='tiktok-23vhki-StrongText ejg0rhn2')/* get the class by right clicking on the video,look for the tag strong ,that has the link of the video as text, if you confused , you might have to watch youtube videos on webscraping*/

        for i in links:

            f.write(i.text)

            f.write('\n')

    f.close()

    print('done')

   

 

           

 

tiktok scrape video links

 

import urllib.request

import requests

import re

import time

from bs4 import BeautifulSoup

f = open('tiktokmainlinks.txt','w',encoding ="utf-8")

url = "https://www.tiktok.com/tag/nailart"

html = urllib.request.urlopen(url).read()

soup = BeautifulSoup(html, 'html.parser')

link = soup.find_all('div',{'class':'tiktok-yvmafn-DivVideoFeedV2 ecyq5ls0'})

/* get the class by right clicking on the video,look for the tag div ,that has the hashtag of the video as text , if you confused , you might have to watch youtube videos on webscraping*/

        for i in links:

 

for i in link:

    iref = i.find_all('a',attrs ={'href':re.compile("https:")})

    for t in iref :

        f.write(t.get('href')

        f.write('\n')

f.close()

print('done')

 

 

I did two web scraping , one to scrape for the links of the video and the other to scrape for the hashtags.

 


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