Going online (first public version)

This commit is contained in:
Karim shoair
2024-10-13 23:38:48 +03:00
parent ab0e2779f9
commit a721073b7c
37 changed files with 3065 additions and 140 deletions
@@ -0,0 +1,23 @@
"""
I only made this example to show how Scrapling features can be used to scrape a website without writing any selector
so this script doesn't depend on the website structure.
"""
import requests
from scrapling import Adaptor
response = requests.get('https://stackoverflow.com/questions/tagged/web-scraping?sort=MostVotes&filters=NoAcceptedAnswer&edited=true&pagesize=50&page=2')
page = Adaptor(response.text, url=response.url)
# First we will extract the first question title and its author based on the text content
first_question_title = page.find_by_text('Run Selenium Python Script on Remote Server')
first_question_author = page.find_by_text('Ryan')
# If you want you can extract other questions tags like below
first_question = first_question_title.find_ancestor(
lambda ancestor: ancestor.attrib.get('id') and 'question-summary' in ancestor.attrib.get('id')
)
rest_of_questions = first_question.find_similar()
# But since nothing to rely on to extract other titles/authors from these elements without CSS/XPath selectors due to the website nature
# We will get all the rest of the titles/authors in the page depending on the first title and the first author we got above as a starting point
for i, (title, author) in enumerate(zip(first_question_title.find_similar(), first_question_author.find_similar()), start=1):
print(i, title.text, author.text)