How to Scrape News Articles with Python and AI Using ProxyTee

In today's digital age, news data is a treasure trove of information for market research, trend analysis, and more. But manually collecting this data is a time-consuming and inefficient task. That’s where web scraping comes in. This post will guide you through building a news scraper using both AI and Python, or how you can simplify the process with ready-made APIs, and how ProxyTee can help you achieve your goal. ProxyTee is known for its reliable rotating residential proxies, making it an ideal solution for this task.

What is a News Scraper?

A news scraper is an automated tool that extracts data from news websites. It can gather information such as headlines, publication dates, authors, tags, and the main article content. This information can be used for research, trend analysis, or creating news aggregators, saving time compared to manually collecting data.

Data to Scrape from News Articles

When building a news scraper, you can target several types of data, such as:

• Headlines: The main title and subtitles of the article.
• Publication Date: When the article was published.
• Author: The journalist or writer of the article.
• Content: The body of the article.
• Tags/Topics: Keywords or categories assigned to the article.
• Multimedia Attachments: Images, videos, or other media within the article.
• URLs: Links to other relevant articles or sources.
• Related Articles: Links to other articles on the same topic.

How to Build a News Scraper with ProxyTee

There are two primary approaches when building a news scraper: Using AI, or building custom scraping scripts. ProxyTee's rotating residential proxies make both of these methods viable by providing stable and reliable IP addresses for your scraping needs. Here, let’s take a look at how both methods work with help from ProxyTee

Using AI for Data Extraction

AI models can be used to extract key information from news articles by either supplying the HTML content of a news article to an AI model for data extraction. Another method is to give a URL of an article to a Large Language Model (LLM) provider and ask it to extract data like the title and main content.

Pros:

• Works with nearly all news websites.
• Automates the data extraction process.
• Preserves the formatting like indentation, structure, bolding and etc.

Cons:

• Advanced AI models can be expensive
• You have limited control over the scraping process.
• Results might contain inaccuracies.

Building Custom Scraping Scripts

This method uses manual code, i.e. a scraping bot, to connect to a target website, parse the HTML code, and extract relevant data. Using ProxyTee's rotating residential proxies can help avoid detection from websites.

Pros:

• Full control over the data extraction process.
• Can be tailored for specific needs.
• Cost-effective without third-party providers.

Cons:

• Requires coding skills for implementation and maintenance.
• Each news site needs its own dedicated scraping script.
• Handling exceptions may be hard.

How ProxyTee Enhances Your Scraping Process

When building a news scraper, the reliability of your proxy provider is important. Here is how ProxyTee makes your experience better:

1. Rotating Residential Proxies: ProxyTee provides rotating residential proxies which means you get access to a huge pool of IP addresses. This reduces the chances of your IP getting blocked and ensures reliable data extraction from different websites. The auto-rotation feature from ProxyTee can be customized to change IPs every 3 to 60 minutes, adapting to different scraping needs.

2. Global IP Coverage: With over 20 million IP addresses across 100+ countries, ProxyTee is perfect if you want to access geo-specific content.

3. Unlimited Bandwidth: ProxyTee's unlimited bandwidth helps when you scrape lots of data and won’t cost extra.

4. Protocol Flexibility: ProxyTee supports HTTP and SOCKS5 protocols ensuring compatibility with any application.

5. User-Friendly Interface and API Integration: The platform has an easy to use GUI interface, along with an API integration for developers, so both individuals and businesses can start quickly.

AI-Powered News Scraping Steps with ProxyTee

1. Collect Data: With ProxyTee, retrieve HTML from the target news page using a Python HTTP client, or if using a tool like ChatGPT, just pass the URL to have it do the heavy lifting automatically.
2. Preprocess Data: When using HTML, ensure to clean it up before feeding it to the AI, you want to only focus on important elements like title, authors and article body.
3. Send Data to the AI Model: Pass the URL or cleaned HTML to the AI to extract and return structured data.
4. Handle AI Output: Process and format the output using your scripts.
5. Export: Save data to your preferred format such as databases or CSV files.

Building a Custom News Scraping Script with ProxyTee

Before you create your own scraping script, examine the target site to identify its structure, the type of data you wish to extract, and the proper tools to use. When working with simple websites you can just use Requests and Beautiful Soup:

• Requests: Used for HTTP requests, retrieves HTML code
• Beautiful Soup: This python library is used for parsing and extracting HTML or XML content.

If there are more complexities you might need to use a tool for browser automation, such as Selenium. With ProxyTee, here are steps you'd take:

1. Connect to the target site: use ProxyTee's proxies to ensure reliable HTML access from the site.
2. Select elements: Find specific HTML elements on the page, i.e. title and content.
3. Extract data: Extract info from these identified elements.
4. Clean up: Remove unnecessary information if needed
5. Export: Save data in your preferred format.

Example Scripts

Let’s take a look at how we can implement the scraping process for a couple news websites:

CNN Scraping with ProxyTee

CNN's website does not have an extensive blocking measure in place. For that we can simply use the requests library, with the help of ProxyTee's residential proxies for IP rotation.

import requests
from bs4 import BeautifulSoup
import json

# URL of the CNN article
url = "https://www.cnn.com/2024/11/28/weather/thanksgiving-weekend-weather-arctic-storm/index.html"

# Use a ProxyTee residential proxy here
proxies = {
    "http": "http://YOUR_MYPROXY_USERNAME:YOUR_MYPROXY_password@gate.proxytee.com:PORT",
    "https": "http://YOUR_MYPROXY_USERNAME:YOUR_MYPROXY_password@gate.proxytee.com:PORT",
}

# Send an HTTP GET request to the article page through the proxy
response = requests.get(url, proxies=proxies)

# Parse the HTML content of the page
soup = BeautifulSoup(response.content, "html.parser")

# Extract the title
title_element = soup.select_one("h1")
title = title_element.get_text(strip=True)

# Extract the article content
article_content = soup.select_one(".article__content")
content = article_content.get_text(strip=True)

# Prepare the data to be exported as JSON
article = {
    "title": title,
    "content": content
}

# Export data to a JSON file
with open("article.json", "w", encoding="utf-8") as json_file:
    json.dump(article, json_file, ensure_ascii=False, indent=4)

Remember to replace the placeholder values for username, password and port. This code generates a JSON file containing the extracted title and content of the CNN article. Remember that CNN might update their website structure in the future, so code maintenance would be needed. You can apply similar methods to other similar websites that don’t have a lot of antibot measures. The IP rotation, along with the large pool of IPs from ProxyTee will enable smooth and efficient data scraping.

Reuters Scraping with ProxyTee

Reuters, unlike CNN, has anti-bot measures to block automated requests that aren’t coming from browsers. This is where tools like Selenium come in handy. With ProxyTee and Selenium, you can bypass such measures. Here’s how you’d go about it:

from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.chrome.options import Options
import json

# Initialize Chrome options and add proxy
chrome_options = Options()

# ProxyTee integration
proxy = "YOUR_MYPROXY_USERNAME:YOUR_MYPROXY_password@gate.proxytee.com:PORT"
chrome_options.add_argument(f'--proxy-server=http://{proxy}')

driver = webdriver.Chrome(service=Service(), options=chrome_options)

# URL of the Reuters article
url = "https://www.reuters.com/world/europe/excitement-relief-paris-notre-dame-cathedral-prepares-reopen-2026-11-29/"

# Open the URL in the browser
driver.get(url)

# Extract the title from the <h1> tag
title_element = driver.find_element(By.CSS_SELECTOR, "h1")
title = title_element.text

# Select all text elements
paragraph_elements = driver.find_elements(By.CSS_SELECTOR, "[data-testid^=\"paragraph-\"]")

# Aggregate their text
content = " ".join(p.text for p in paragraph_elements)

# Prepare the data to be exported as JSON
article = {
    "title": title,
    "content": content
}

# Export data to a JSON file
with open("article.json", "w", encoding="utf-8") as json_file:
    json.dump(article, json_file, ensure_ascii=False, indent=4)

driver.quit()

Remember to replace the placeholder for username, password and port. This script uses the Selenium browser to scrape content which bypasses the blocks and outputs a JSON file containing title and content from the article.

BBC Scraping with ProxyTee

Similar to CNN, BBC doesn't have major antibot measures, so requests and beautifulsoup are enough with help from ProxyTee:

import requests
from bs4 import BeautifulSoup
import json

# URL of the BBC article
url = "https://www.bbc.com/news/articles/cvg70jr949po"

# ProxyTee integration
proxies = {
    "http": "http://YOUR_MYPROXY_USERNAME:YOUR_MYPROXY_password@gate.proxytee.com:PORT",
    "https": "http://YOUR_MYPROXY_USERNAME:YOUR_MYPROXY_password@gate.proxytee.com:PORT",
}
# Send an HTTP GET request to the article page using the proxy
response = requests.get(url, proxies=proxies)

# Parse the HTML content of the page
soup = BeautifulSoup(response.content, "html.parser")

# Extract the title
title_element = soup.select_one("h1")
title = title_element.get_text(strip=True)

# Extract the article content
article_content_elements = soup.select("[data-component=\"text-block\"], [data-component=\"subheadline-block\"]")

# Aggregate their text
content = "\n".join(ace.text for ace in article_content_elements)

# Prepare the data to be exported as JSON
article = {
    "title": title,
    "content": content
}

# Export data to a JSON file
with open("article.json", "w", encoding="utf-8") as json_file:
    json.dump(article, json_file, ensure_ascii=False, indent=4)

Again, remember to replace the placeholders for the correct values from your ProxyTee account. With these methods we showed you simple but robust way to scrape news data with the help of ProxyTee's residential proxies for IP rotation, but also an unlimited bandwidth. With rotating IPs, you ensure efficient and reliable scraping across various websites.

Challenges in News Scraping

While the scripts here were pretty simple to use, there are still many challenges that you could encounter:

• Ensuring all the scraped data, keeps original formatting.
• Going beyond just title and content to get author, date, tags and etc.
• Automate process across various sites.

Overcoming the Challenges

• Learn and master techniques to bypass CAPTCHAs and other website protection measures.
• Use advanced scraping tools such as Playwright for more challenging websites.
• Consider dedicated News Scraper APIs, to get streamlined structured data.

Why Use ProxyTee Over Competitors

ProxyTee stands out from competitors by providing affordable, reliable, and easy-to-use rotating residential proxies. While services like Bright Data and Oxylabs may offer similar features, ProxyTee excels in several ways:

• Affordability: ProxyTee provides unlimited residential proxies at very competitive pricing with plans starting as low as 50% compared to the competition.
• Unlimited bandwidth: The unlimited bandwidth ensures data-intensive tasks like web scraping won’t incur extra costs
• Precise Geo-targeting: While some competitors might offer continental or random targeting, ProxyTee enables you to target specific countries, increasing scraping efficiency
• Ease of use: With clean GUI and API, you will quickly integrate proxies into your own setup and scraping solutions

Simplify Your Workflow With APIs or Ready-Made Datasets

If you don’t want to get into setting up scripts and complex data scraping techniques, consider using pre built APIs or datasets. APIs simplify data extractions by getting access to pre structured information. Consider these to reduce the hassle of data extractions.

Conclusion

Web scraping, particularly for news data, can be a complex task, however by leveraging AI or Python scripts together with a proper rotating residential proxies such as ProxyTee this can easily be solved. Whether you choose to build your custom scraper or utilize an API, using ProxyTee's proxies is critical for seamless, efficient, and cost effective results. Using ProxyTee's services allows you to collect data while avoiding detection. ProxyTee's proxies provide high speed, and unlimited bandwidth ensuring that you get fast reliable data from various news websites without worrying about IP bans.

Take a look at our pricing plans, or start your journey with a ProxyTee trial.