Is it legal to scrape data from Weather.com?

Scraping weather data for personal use or internal research is generally considered fair use. However, redistributing their proprietary forecasts for commercial profit may violate their Terms of Service; always check the site's robots.txt and consider their official API for commercial ventures.

Does Weather.com have an official API?

Yes, Weather.com offers an official API through IBM's The Weather Company. While the API is highly reliable, scraping is often used by developers for small-scale projects or when they need data types not covered by basic API tiers.

How do I bypass the Akamai protection on Weather.com?

Bypassing Akamai requires a combination of high-quality residential proxies, realistic browser fingerprinting, and a tool that can handle JavaScript execution like Playwright. Avoid making too many requests in a short period to prevent IP flagging.

What is the best way to handle dynamic CSS classes?

Weather.com uses obfuscated class names that change frequently. The most stable way to select elements is using the 'data-testid' attribute (e.g., [data-testid="TemperatureValue"]) which remains consistent across most site updates.

Can I scrape historical weather data from Weather.com?

Weather.com primarily focuses on current and future forecasts. For deep historical archives, websites like Weather Underground (also owned by the same company) are better targets for historical meteorological scraping.

How often does the weather data update?

Current conditions on the site typically update every 15 to 60 minutes depending on the location and station. Forecasts are updated multiple times per day as meteorological models are recalculated.

What format can I export the scraped data into?

Using tools like Automatio or custom scripts, you can export the extracted weather data into CSV for spreadsheets, JSON for application integration, or directly into a Google Sheet for real-time monitoring.

How to Scrape Weather.com: A Guide to Weather Data Extraction

Learn how to scrape real-time weather data, forecasts, and air quality from Weather.com. Discover techniques to bypass Akamai and extract global...

Start Scraping Free

weather.comHard

Coverage:GlobalUnited StatesEuropeAsiaAustralia

Available Data7 fields

TitleLocationDescriptionImagesPosting DateCategoriesAttributes

All Extractable Fields

Current TemperatureFeels Like TemperatureHumidity PercentageWind Speed & DirectionAir Quality Index (AQI)UV IndexVisibility DistanceBarometric PressureDew PointSunrise/Sunset TimesMoon PhaseHourly Forecast Details10-Day Forecast High/LowChance of PrecipitationTree/Grass/Weed Pollen LevelsSevere Weather Alerts

Technical Requirements

JavaScript Required

No Login

No Pagination

Official API Available

Anti-Bot Protection Detected

Akamai Bot ManagerBrowser FingerprintingRate LimitingIP BlockingCanvas Fingerprinting

View API Documentation

About Weather.com

Learn what Weather.com offers and what valuable data can be extracted from it.

Global Meteorological Authority

Weather.com, the digital flagship of The Weather Channel and owned by The Weather Company (an IBM subsidiary), is one of the world's most sophisticated weather forecasting platforms. It provides hyper-localized data ranging from hourly temperature fluctuations to 10-day forecasts, severe weather alerts, and high-resolution radar imagery for millions of locations worldwide.

Comprehensive Atmospheric Insights

The platform goes beyond basic temperature, offering structured data on air quality indices (AQI), UV radiation levels, allergy risks (pollen counts), and even flu activity trackers. This vast repository of environmental metrics is generated through proprietary forecasting models and a global network of sensors, making it a primary source for both consumer planning and enterprise-level risk management.

Strategic Value of Weather Data

Scraping Weather.com is invaluable for industries where atmospheric conditions dictate operational success. From agriculture and logistics to renewable energy and retail, automated data extraction allows businesses to build predictive models, optimize supply chains, and mitigate weather-related financial risks with real-time accuracy.

Why Scrape Weather.com?

Discover the business value and use cases for extracting data from Weather.com.

Monitor real-time severe weather alerts to protect logistics and transportation assets.

Predict energy consumption peaks for utility grids based on temperature and humidity trends.

Optimize agricultural irrigation schedules using localized precipitation and evaporation data.

Conduct market research for retail businesses to align seasonal inventory with upcoming weather patterns.

Aggregate global climate data for academic research or environmental monitoring projects.

Enhance outdoor event planning by monitoring hyper-local wind and storm forecasts.

Scraping Challenges

Technical challenges you may encounter when scraping Weather.com.

Akamai Bot Manager protection which identifies and blocks non-browser traffic patterns.

Heavy reliance on React.js, requiring a headless browser to render the DOM before data is accessible.

Dynamic and obfuscated CSS classes that change frequently, making standard selectors unstable.

Geographic sensitivity where content and units (Metric vs Imperial) vary by IP address.

Scrape Weather.com with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

Describe What You Need

Tell the AI what data you want to extract from Weather.com. Just type it in plain language — no coding or selectors needed.

AI Extracts the Data

Our artificial intelligence navigates Weather.com, handles dynamic content, and extracts exactly what you asked for.

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Effortlessly bypasses Akamai and other complex anti-bot systems without manual configuration.

Handles full JavaScript execution automatically to capture data from dynamic React components.

Allows for scheduled data extraction to maintain a continuous stream of real-time updates.

Supports residential proxy integration to scrape data from any global location without being blocked.

Start Scraping Free

No credit card requiredFree tier availableNo setup needed

No-Code Web Scrapers for Weather.com

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Weather.com. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

Install browser extension or sign up for the platform

Navigate to the target website and open the tool

Point-and-click to select data elements you want to extract

Configure CSS selectors for each data field

Set up pagination rules to scrape multiple pages

Handle CAPTCHAs (often requires manual solving)

Configure scheduling for automated runs

Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Note: Weather.com uses Akamai; simple requests are often blocked.
# We use a real User-Agent to try and pass basic filters.
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9'
}

url = 'https://weather.com/weather/today/l/USNY0996:1:US'

try:
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Use data-testid as CSS classes are dynamic
        temp = soup.find('span', {'data-testid': 'TemperatureValue'})
        if temp:
            print(f'Current Temperature: {temp.text}')
        else:
            print('Element not found. The site likely requires JavaScript rendering.')
    else:
        print(f'Failed to retrieve data: Status Code {response.status_code}')
except Exception as e:
    print(f'Error: {e}')

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

●Fastest execution (no browser overhead)
●Lowest resource consumption
●Easy to parallelize with asyncio
●Great for APIs and static pages

Limitations

●Cannot execute JavaScript
●Fails on SPAs and dynamic content
●May struggle with complex anti-bot systems

from playwright.sync_api import sync_playwright

def scrape_weather():
    with sync_playwright() as p:
        # Launching a headed or headless browser to handle Akamai and React
        browser = p.chromium.launch(headless=True)
        page = browser.new_page()
        
        # Navigate to a specific location (New York City in this case)
        page.goto('https://weather.com/weather/today/l/USNY0996:1:US')
        
        # Wait for the specific React-rendered element to appear
        page.wait_for_selector('[data-testid="TemperatureValue"]')
        
        # Extract data using stable data-testid attributes
        data = {
            'temp': page.inner_text('[data-testid="TemperatureValue"]'),
            'location': page.inner_text('h1[class*="CurrentConditions"]'),
            'details': page.inner_text('[data-testid="precipPhrase"]')
        }
        
        print(f"Weather for {data['location']}: {data['temp']} - {data['details']}")
        browser.close()

scrape_weather()

When to Use

Use when content loads dynamically via JavaScript, or when you need to interact with the page (clicks, scrolls, form fills). Handles modern anti-bot detection better.

Advantages

●Executes JavaScript like a real browser
●Handles SPAs and dynamic content
●Better anti-bot evasion with stealth plugins
●Can take screenshots and PDFs

Limitations

●Slower than HTTP requests
●Higher memory/CPU usage
●More complex to set up

import scrapy

class WeatherSpider(scrapy.Spider):
    name = 'weather_spider'
    start_urls = ['https://weather.com/weather/today/l/USNY0996:1:US']

    def parse(self, response):
        # Scrapy alone cannot handle the JS rendering on Weather.com
        # Integration with Scrapy-Playwright or Scrapy-Splash is required
        yield {
            'location': response.css('h1[class*="CurrentConditions"]::text').get(),
            'temperature': response.css('[data-testid="TemperatureValue"]::text').get(),
            'humidity': response.xpath('//span[@data-testid="PercentageValue"]/text()').get(),
            'uv_index': response.css('[data-testid="uvIndexValue"]::text').get()
        }

When to Use

Ideal for large-scale crawling projects that need to scrape thousands of pages. Built-in support for rate limiting, retries, and data pipelines.

Advantages

●Built for scale (millions of pages)
●Automatic request throttling
●Built-in data export pipelines
●Middleware system for proxies/headers

Limitations

●Steeper learning curve
●Overkill for small projects
●No native JavaScript rendering

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();

  // Set a realistic User-Agent to avoid immediate block
  await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36');

  await page.goto('https://weather.com/weather/today/l/USNY0996:1:US', { waitUntil: 'networkidle2' });

  // Extracting data using the document evaluation
  const weatherData = await page.evaluate(() => {
    const temp = document.querySelector('[data-testid="TemperatureValue"]')?.innerText;
    const location = document.querySelector('h1[class*="CurrentConditions"]')?.innerText;
    return { temp, location };
  });

  console.log(weatherData);
  await browser.close();
})();

When to Use

Choose this if you're in a Node.js/JavaScript ecosystem or need tight integration with frontend tools. Similar capabilities to Playwright.

Advantages

●Native JavaScript/TypeScript support
●Chrome DevTools Protocol access
●Large ecosystem and community
●Good for JS-heavy projects

Limitations

●Chrome-only (vs Playwright's multi-browser)
●Similar overhead to Playwright
●Less mature stealth options

How to Scrape Weather.com with Code

Python + Requests

import requests
from bs4 import BeautifulSoup

# Note: Weather.com uses Akamai; simple requests are often blocked.
# We use a real User-Agent to try and pass basic filters.
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
    'Accept-Language': 'en-US,en;q=0.9'
}

url = 'https://weather.com/weather/today/l/USNY0996:1:US'

try:
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Use data-testid as CSS classes are dynamic
        temp = soup.find('span', {'data-testid': 'TemperatureValue'})
        if temp:
            print(f'Current Temperature: {temp.text}')
        else:
            print('Element not found. The site likely requires JavaScript rendering.')
    else:
        print(f'Failed to retrieve data: Status Code {response.status_code}')
except Exception as e:
    print(f'Error: {e}')

Python + Playwright

from playwright.sync_api import sync_playwright

def scrape_weather():
    with sync_playwright() as p:
        # Launching a headed or headless browser to handle Akamai and React
        browser = p.chromium.launch(headless=True)
        page = browser.new_page()
        
        # Navigate to a specific location (New York City in this case)
        page.goto('https://weather.com/weather/today/l/USNY0996:1:US')
        
        # Wait for the specific React-rendered element to appear
        page.wait_for_selector('[data-testid="TemperatureValue"]')
        
        # Extract data using stable data-testid attributes
        data = {
            'temp': page.inner_text('[data-testid="TemperatureValue"]'),
            'location': page.inner_text('h1[class*="CurrentConditions"]'),
            'details': page.inner_text('[data-testid="precipPhrase"]')
        }
        
        print(f"Weather for {data['location']}: {data['temp']} - {data['details']}")
        browser.close()

scrape_weather()

Python + Scrapy

import scrapy

class WeatherSpider(scrapy.Spider):
    name = 'weather_spider'
    start_urls = ['https://weather.com/weather/today/l/USNY0996:1:US']

    def parse(self, response):
        # Scrapy alone cannot handle the JS rendering on Weather.com
        # Integration with Scrapy-Playwright or Scrapy-Splash is required
        yield {
            'location': response.css('h1[class*="CurrentConditions"]::text').get(),
            'temperature': response.css('[data-testid="TemperatureValue"]::text').get(),
            'humidity': response.xpath('//span[@data-testid="PercentageValue"]/text()').get(),
            'uv_index': response.css('[data-testid="uvIndexValue"]::text').get()
        }

Node.js + Puppeteer

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();

  // Set a realistic User-Agent to avoid immediate block
  await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36');

  await page.goto('https://weather.com/weather/today/l/USNY0996:1:US', { waitUntil: 'networkidle2' });

  // Extracting data using the document evaluation
  const weatherData = await page.evaluate(() => {
    const temp = document.querySelector('[data-testid="TemperatureValue"]')?.innerText;
    const location = document.querySelector('h1[class*="CurrentConditions"]')?.innerText;
    return { temp, location };
  });

  console.log(weatherData);
  await browser.close();
})();

What You Can Do With Weather.com Data

Explore practical applications and insights from Weather.com data.

Supply Chain Risk Mitigation

Logistics companies can use scraped weather data to predict delays and reroute shipments before storms hit.

How to implement:

1Scrape real-time severe weather alerts and wind speeds for key shipping routes.
2Cross-reference weather data with current fleet GPS locations.
3Automatically notify dispatchers to reroute vehicles away from high-risk weather zones.

Use Automatio to extract data from Weather.com and build these applications without writing code.

More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents

Web Automation

Smart Workflows

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Pro Tips for Scraping Weather.com

Expert advice for successfully extracting data from Weather.com.

Focus on 'data-testid' attributes for selectors; Weather.com uses dynamic CSS classes (e.g., 'CurrentConditions--tempValue--3KcRf') that change with every site build.

Use residential proxies rather than datacenter proxies to avoid being flagged by Akamai's reputation-based blocking.

If you need global data, append specific location codes to the URL (e.g., '/l/UKXX0085:1:UK' for London) rather than using the search bar.

Monitor the 'Network' tab in Developer Tools for JSON responses from their internal APIs, which are often easier to parse than the rendered HTML.

Implement a 'stealth' plugin if using Playwright or Puppeteer to hide automated browser properties from fingerprinting scripts.

Scrape during off-peak hours for the target region to reduce the likelihood of triggering rate limits.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Mohammed Ibrahim

CEO, qannas.pro

Ben Bressington

CTO, AiChatSolutions

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Related Web Scraping

Frequently Asked Questions About Weather.com

Find answers to common questions about Weather.com

How to Scrape Weather.com: A Guide to Weather Data Extraction

About Weather.com

Global Meteorological Authority

Comprehensive Atmospheric Insights

Strategic Value of Weather Data

Why Scrape Weather.com?

Scraping Challenges

Scrape Weather.com with AI

How It Works

Why Use AI for Scraping

No-Code Web Scrapers for Weather.com

Typical Workflow with No-Code Tools

Common Challenges

Code Examples

What You Can Do With Weather.com Data

Supply Chain Risk Mitigation

Agricultural Yield Optimization

Dynamic Retail Merchandising

Energy Load Prediction

Health & Allergy Alert Services

Supercharge your workflow with AI Automation

Pro Tips for Scraping Weather.com

What Our Users Say

Related Web Scraping

How to Scrape GitHub | The Ultimate 2025 Technical Guide

How to Scrape Britannica: Educational Data Web Scraper

How to Scrape Worldometers for Real-Time Global Statistics

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How to Scrape Pollen.com: Local Allergy Data Extraction Guide

How to Scrape RethinkEd: A Technical Data Extraction Guide

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How to Scrape Poll-Maker: A Comprehensive Web Scraping Guide

Frequently Asked Questions About Weather.com

Is it legal to scrape data from Weather.com?

Does Weather.com have an official API?

How do I bypass the Akamai protection on Weather.com?

What is the best way to handle dynamic CSS classes?

Can I scrape historical weather data from Weather.com?

How often does the weather data update?

What format can I export the scraped data into?

How to Scrape Weather.com: A Guide to Weather Data Extraction

About Weather.com

Global Meteorological Authority

Comprehensive Atmospheric Insights

Strategic Value of Weather Data

Why Scrape Weather.com?

Scraping Challenges

Scrape Weather.com with AI

How It Works

Why Use AI for Scraping

How to scrape with AI:

Why use AI for scraping:

No-Code Web Scrapers for Weather.com

Typical Workflow with No-Code Tools

Common Challenges

No-Code Web Scrapers for Weather.com

Typical Workflow with No-Code Tools

Common Challenges

Code Examples

How to Scrape Weather.com with Code

Python + Requests

Python + Playwright

Python + Scrapy

Node.js + Puppeteer

What You Can Do With Weather.com Data

Supply Chain Risk Mitigation

Agricultural Yield Optimization

Dynamic Retail Merchandising

Energy Load Prediction

Health & Allergy Alert Services

What You Can Do With Weather.com Data

Supercharge your workflow with AI Automation

Pro Tips for Scraping Weather.com

What Our Users Say

Related Web Scraping

How to Scrape GitHub | The Ultimate 2025 Technical Guide

How to Scrape Britannica: Educational Data Web Scraper

How to Scrape Worldometers for Real-Time Global Statistics

How to Scrape Wikipedia: The Ultimate Web Scraping Guide

How to Scrape Pollen.com: Local Allergy Data Extraction Guide

How to Scrape RethinkEd: A Technical Data Extraction Guide

How to Scrape American Museum of Natural History (AMNH)

How to Scrape Poll-Maker: A Comprehensive Web Scraping Guide

Frequently Asked Questions About Weather.com

Is it legal to scrape data from Weather.com?

Does Weather.com have an official API?

How do I bypass the Akamai protection on Weather.com?

What is the best way to handle dynamic CSS classes?

Can I scrape historical weather data from Weather.com?

How often does the weather data update?

What format can I export the scraped data into?