👑 Attack on Titan Character Ranking 👑

Snowikin said:


Are you edited it ??

I've just seen Mikasa there...!

OtakuKun1 said:
I nominate:
https://myanimelist.net/character/45627/Levi?onetime=93f255310f9625549f2f6cad401644f55fd3bcd0f6f4cf054befcef82cb35b94&user_agent=mal-ios-app

backchodi said:
https://myanimelist.net/character/40882/Eren_Yeager/pics
Erin Yeager
https://myanimelist.net/character/40882/Eren_Yeager

nirererin said:

provide the Character's MAL link

acidic_water said:
I nominate Eren Yeager

kush_void said:


Now, let's move to the next important topic in the Python Learning Series

*Web Scraping using BeautifulSoup*

*What is Web Scraping?*

Web Scraping is the process of automatically extracting data from websites.

For example, if you want to collect all product names and prices from an e-commerce site — instead of copying them manually, you can write a Python script to do it for you.

*BeautifulSoup*: BeautifulSoup is a Python library used to extract data from websites. It works by parsing HTML or XML code and lets you find the exact parts of a webpage you want.

*requests*: Helps fetch the webpage’s HTML code.

*Step-by-Step Tutorial*

*Step 1: Install Required Libraries*

pip install requests
pip install beautifulsoup4


*Step 2: Fetch a Web Page*

import requests

url = "[url=https://quotes.toscrape.com"/]https://quotes.toscrape.com"[/url]
response = requests.get(url)

print(response.text) # prints the HTML content



*Step 3: Parse the HTML with BeautifulSoup*

from bs4 import BeautifulSoup

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


*Step 4: Extract Specific Data (e.g., Quotes & Authors)*

Each quote is inside a <div class="quote">, so:

quotes = soup.find_all('div', class_='quote')

for quote in quotes:
text = quote.find('span', class_='text').text
author = quote.find('small', class_='author').text
print(f"{text} — {author}")



*Step 5: Save to CSV* (Optional)

import csv

with open('quotes.csv', 'w', newline='', encoding='utf-8') as file:
writer = csv.writer(file)
writer.writerow(['Quote', 'Author'])

for quote in quotes:
text = quote.find('span', class_='text').text
author = quote.find('small', class_='author').text
writer.writerow([text, author])

*Useful Methods in BeautifulSoup*

- soup.find("tag"): Finds the first matching tag.

- soup.find_all("tag"): Finds all tags of that type.

- soup.select("css-selector"): Finds elements using CSS style (like .class or #id).

- .text: Extracts just the text inside the HTML tag.

- .attrs: Accesses tag attributes like href, src, etc.

*Always check a website’s robots.txt file or terms of service before scraping.*
*Avoid scraping sites that prohibit it or overload servers with frequent requests.*


*React with ❤️ once you're ready for the next quiz on web scrapping*

Web Scrapping Project: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a/205

Python Learning Series: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1527

kush_void said:
Levi Ackerman

Now, let's move to the next important topic in the Python Learning Series

*Web Scraping using BeautifulSoup*

*What is Web Scraping?*

Web Scraping is the process of automatically extracting data from websites.

For example, if you want to collect all product names and prices from an e-commerce site — instead of copying them manually, you can write a Python script to do it for you.

*BeautifulSoup*: BeautifulSoup is a Python library used to extract data from websites. It works by parsing HTML or XML code and lets you find the exact parts of a webpage you want.

*requests*: Helps fetch the webpage’s HTML code.

*Step-by-Step Tutorial*

*Step 1: Install Required Libraries*

pip install requests
pip install beautifulsoup4


*Step 2: Fetch a Web Page*

import requests

url = "https://quotes.toscrape.com"
response = requests.get(url)

print(response.text) # prints the HTML content



*Step 3: Parse the HTML with BeautifulSoup*

from bs4 import BeautifulSoup

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


*Step 4: Extract Specific Data (e.g., Quotes & Authors)*

Each quote is inside a <div class="quote">, so:

quotes = soup.find_all('div', class_='quote')

for quote in quotes:
text = quote.find('span', class_='text').text
author = quote.find('small', class_='author').text
print(f"{text} — {author}")



*Step 5: Save to CSV* (Optional)

import csv

with open('quotes.csv', 'w', newline='', encoding='utf-8') as file:
writer = csv.writer(file)
writer.writerow(['Quote', 'Author'])

for quote in quotes:
text = quote.find('span', class_='text').text
author = quote.find('small', class_='author').text
writer.writerow([text, author])

*Useful Methods in BeautifulSoup*

- soup.find("tag"): Finds the first matching tag.

- soup.find_all("tag"): Finds all tags of that type.

- soup.select("css-selector"): Finds elements using CSS style (like .class or #id).

- .text: Extracts just the text inside the HTML tag.

- .attrs: Accesses tag attributes like href, src, etc.

*Always check a website’s robots.txt file or terms of service before scraping.*
*Avoid scraping sites that prohibit it or overload servers with frequent requests.*


*React with ❤️ once you're ready for the next quiz on web scrapping*

Web Scrapping Project: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a/205

Python Learning Series: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1527

Donquixotefan said:
since erwins taken ill pick zeke

Reetesh-singh said:
i nominate Annie Leonhart