HG Weather API

Overview

HG Weather offers an API service designed to provide developers with access to current, historical, and forecast weather data on a global scale. The API supports various data points, including temperature, humidity, wind speed and direction, atmospheric pressure, and precipitation. It is structured as a RESTful API, allowing for standard HTTP requests and JSON responses, making it compatible with most programming languages and application environments. The service focuses on delivering data for use cases such as real-time dashboards for logistics, agricultural planning, renewable energy optimization, and risk assessment systems.

Developers frequently utilize HG Weather for applications requiring granular hourly and daily forecasts, as well as for retrieving historical data necessary for trend analysis or machine learning model training. For example, an agricultural application might query historical precipitation data for a specific region to inform planting schedules, while a logistics platform could use real-time wind speed data to optimize delivery routes for drone operations. The API's capabilities extend to providing access to weather maps, which can be embedded in applications to offer visual representations of weather patterns, such as radar, satellite imagery, and temperature overlays.

The service is designed for developers and technical buyers aiming to integrate weather intelligence without managing their own weather data infrastructure. HG Weather's approach emphasizes clear API documentation and code examples across multiple programming languages, which aids in quicker integration. The developer experience notes indicate that the API is straightforward to implement, with a focus on providing current, historical, and forecast data through a consistent interface. This design principle helps reduce the complexity often associated with processing large volumes of meteorological data, allowing developers to focus on their core application logic rather than data acquisition.

Use cases for HG Weather span multiple industries. In smart city initiatives, the API can power environmental monitoring systems, providing data on air quality and localized weather conditions. For the insurance sector, historical weather data can be used to assess risk for property damage claims or to inform actuarial models. Energy companies can leverage forecast data to predict demand fluctuations based on temperature changes, optimizing grid management. The API's ability to provide both point-in-time data and historical trends makes it suitable for both operational decisions and long-term strategic planning. Its global coverage ensures that applications can retrieve weather data for virtually any location, supporting international operations and geographically diverse user bases. This broad applicability makes HG Weather a candidate for a range of data-driven projects that require environmental context.

Key features

• Real-time Weather Data: Provides current weather conditions for any global location, including temperature, humidity, pressure, wind, and visibility.
• Historical Weather Data: Offers access to past weather conditions, enabling analysis of trends and pattern recognition for specific dates and locations.
• Forecast Weather Data: Delivers future weather predictions, including hourly and daily forecasts, essential for planning and predictive modeling.
• Weather Maps: Allows integration of visual weather maps with layers such as radar, satellite, and temperature, enhancing user interfaces.
• Global Coverage: Supports weather data retrieval for locations worldwide, facilitating international application development.
• RESTful API: Utilizes a standard REST architecture for easy integration with various programming languages and platforms.
• Extensive Documentation: Provides clear and detailed API documentation with code examples in Python, Node.js, PHP, Ruby, Java, and Go, as described in the HG Weather documentation.

Pricing

HG Weather offers a tiered pricing model that includes a free plan and scales up to custom enterprise solutions.

Pricing as of May 2026. For the most current pricing details, refer to the official HG Weather pricing page.

Common integrations

• Web Applications: Integrate real-time weather into websites for travel, news, or e-commerce platforms using JavaScript frameworks.
• Mobile Applications: Power location-based weather features in iOS and Android apps for navigation, fitness, or daily utilities.
• IoT Devices: Connect with smart home systems or industrial sensors to provide environmental context for automated actions.
• Data Analytics Platforms: Combine weather data with business intelligence tools for deeper insights into operational efficiency or market trends.
• Cloud Platforms: Deploy applications leveraging HG Weather on platforms like Google Cloud, AWS, or Azure for scalable infrastructure.
• CRM Systems: Enhance customer relationship management by providing weather-related context for sales calls or marketing campaigns.

Alternatives

• OpenWeatherMap: Offers current weather, forecasts, and historical data with a focus on community contributions and a range of subscription plans.
• AccuWeather: Provides global weather data and forecasts, often used for professional and media applications, with various API tiers.
• Weatherstack: Specializes in real-time and historical weather data, known for its simple API interface and extensive global coverage.

Getting started

To begin using the HG Weather API, you typically need an API key. Once you have registered and obtained your key, you can make HTTP requests to the API endpoints. Below is an example of fetching current weather data for a specific city using Python's requests library. This example demonstrates a basic query for London, providing a foundational understanding of the API's request and response structure.

import requests

API_KEY = "YOUR_API_KEY"
CITY_NAME = "London"

def get_current_weather(api_key, city):
    base_url = "https://api.hgweather.com/current"
    params = {
        "key": api_key,
        "city": city
    }
    try:
        response = requests.get(base_url, params=params)
        response.raise_for_status() # Raise an exception for HTTP errors
        data = response.json()
        return data
    except requests.exceptions.RequestException as e:
        print(f"API request failed: {e}")
        return None

if __name__ == "__main__":
    weather_data = get_current_weather(API_KEY, CITY_NAME)
    if weather_data:
        print(f"Current weather in {CITY_NAME}:")
        print(f"Temperature: {weather_data.get('main', {}).get('temp')}°C")
        print(f"Description: {weather_data.get('weather', [{}])[0].get('description')}")
        print(f"Humidity: {weather_data.get('main', {}).get('humidity')}%")
    else:
        print("Could not retrieve weather data.")

This Python script sends a GET request to the HG Weather current weather endpoint, passing the API key and city name as parameters. The response, if successful, is parsed as JSON, and relevant weather information such as temperature, description, and humidity is extracted and printed. Developers can adapt this pattern for other endpoints, such as historical data or forecasts, by modifying the base_url and params accordingly. For detailed endpoint specifications and parameter options, refer to the HG Weather API reference documentation.