How to Scrape Weather Data in 5 Lines of Python

Web scraping allows developers to extract data from websites automatically. Whether you're building a price tracker or an automated news aggregator, extracting HTML elements is a core skill.

In this quick tutorial, you'll learn how to scrape live weather information using Python's requests and BeautifulSoup libraries.

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Prerequisites

Before starting, make sure you have Python installed, then install the required libraries via your terminal:

bash
pip install requests beautifulsoup4
import requests
from bs4 import BeautifulSoup

Step 1: Fetch the HTML Page
First, import the required modules and send an HTTP request to fetch the web page HTML:

url = "[https://wttr.in/London](https://wttr.in/London)"
response = requests.get(url)

print(f"Status Code: {response.status_code}")

Step 2: Parse and Extract Data
Now, pass the page content into BeautifulSoup to locate and clean up the weather report text:

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

# Extract plain text content from the output
weather_data = soup.get_text()

# Print the top lines of the report
print("\n--- Current Weather Output ---")
print("\n".join(weather_data.splitlines()[:7]))

### Future Improvements

* **Save to CSV:** Export the scraped weather data into a CSV file for tracking trends over time.
* **Automate via Cron Job:** Schedule the script to run automatically every morning at 8 AM.
* **Send Email Alerts:** Integrate the `smtplib` library to email yourself a daily weather report.

Conclusion
With just a few lines of Python, you've fetched web content and extracted useful data! From here, you can schedule this script to run daily or save the scraped data to a JSON or CSV file.

![ ](https://dev-to-uploads.s3.us-east-2.amazonaws.com/uploads/articles/kkkvii2q5eybow1vh1zh.png)