MetaWeather SDKs & Libraries: Past Availability (2026)

SDKs overview

MetaWeather, a service that provided weather data through an API, ceased operations on March 31, 2023. Consequently, all previously available official SDKs and community libraries are no longer supported or functional. The former MetaWeather domain now redirects to a different weather service. This page details the historical context of MetaWeather's SDKs and libraries, examining how developers previously interacted with the API for fetching weather forecasts and location-based weather information.

Before its shutdown, developers utilized various SDKs to integrate MetaWeather's data into their applications. These SDKs typically abstracted the underlying HTTP requests, handling API authentication, request formatting, and response parsing. This facilitated quicker development cycles by reducing the boilerplate code required to interact with the RESTful API endpoints. While the service is no longer active, understanding its past ecosystem provides insight into common API integration patterns and the role of SDKs in developer experience for external services.

Official SDKs by language

Prior to its discontinuation, MetaWeather did not officially maintain a broad suite of first-party SDKs across all popular programming languages. Instead, the developer community often filled this gap with widely adopted third-party libraries. However, some unofficial wrappers gained significant traction due to their adherence to the API's structure and ease of use. It is important to note that as of March 2023, there are no official or actively supported SDKs for MetaWeather, and any previously existing ones are now obsolete.

The MetaWeather API primarily exposed a RESTful interface, which allowed developers to consume data using standard HTTP client libraries in any programming language. This approach is common for many web APIs, as described in the IBM definition of REST APIs. While specific official SDKs were limited, developers typically created their own client implementations or relied on community-driven projects.

A hypothetical representation of what an official SDK table might have looked like:

These entries are illustrative of common community patterns for API wrappers rather than an exhaustive or definitive list of MetaWeather's offerings, which were largely community-driven.

Installation

The installation process for MetaWeather SDKs and community libraries historically followed the standard package management practices of their respective programming languages. For instance, Python libraries were typically installed via pip, JavaScript libraries via npm or yarn, and Ruby gems via gem. This allowed developers to easily add the client libraries to their project dependencies.

A typical installation command for a Python-based MetaWeather library would have involved using the pip package manager, which is the standard tool for installing Python packages, as detailed in the PyPI pip documentation. The command would specify the package name, fetching it from the Python Package Index and making it available in the project's environment. Similarly, JavaScript libraries residing on npm would be installed using the npm install command, adding the dependency to the project's node_modules directory.

Example of historical installation commands:

• Python:

  pip install metaweather-api-client

• JavaScript (Node.js/NPM):

  npm install metaweather-js-wrapper

• Ruby (Bundler/Gem):

  gem install metaweather-client

These commands would fetch the specified library and its dependencies, making the MetaWeather API client accessible within the developer's project. However, as MetaWeather is no longer operational, these commands will either fail or install outdated, non-functional libraries.

Quickstart example

A quickstart example for MetaWeather would have demonstrated how to initialize a client and make a basic API call, such as looking up a location or fetching weather for a specific WoeID (Where on Earth ID). The code would typically abstract the HTTP request details, allowing developers to focus on data retrieval and processing.

Considering a hypothetical Python library, a quickstart might have involved importing the client, instantiating it, and then calling a method like get_location_weather() with the relevant parameters. The response would typically be a JSON object containing weather data, which could then be parsed and used in the application. Again, it is crucial to remember that this example is purely illustrative of past functionality.

Hypothetical Python quickstart snippet (non-functional):

import requests

# NOTE: MetaWeather API is discontinued. This code is illustrative only and will not function.

BASE_URL = "https://www.metaweather.com/api/location/"

def get_weather_by_woeid(woeid):
    try:
        response = requests.get(f"{BASE_URL}{woeid}/")
        response.raise_for_status()  # Raise an HTTPError for bad responses (4xx or 5xx)
        return response.json()
    except requests.exceptions.HTTPError as http_err:
        print(f"HTTP error occurred: {http_err}")
    except requests.exceptions.ConnectionError as conn_err:
        print(f"Connection error occurred: {conn_err}")
    except requests.exceptions.Timeout as timeout_err:
        print(f"Timeout error occurred: {timeout_err}")
    except requests.exceptions.RequestException as req_err:
        print(f"An unexpected error occurred: {req_err}")
    return None

# Example WOEID for London
london_woeid = 44418
weather_data = get_weather_by_woeid(london_woeid)

if weather_data:
    print(f"Weather for {weather_data['title']} (WOEID: {london_woeid}):")
    if 'consolidated_weather' in weather_data and weather_data['consolidated_weather']:
        today_weather = weather_data['consolidated_weather'][0]
        print(f"  Temperature: {today_weather['the_temp']:.2f}°C")
        print(f"  Condition: {today_weather['weather_state_name']}")
        print(f"  Min Temp: {today_weather['min_temp']:.2f}°C")
        print(f"  Max Temp: {today_weather['max_temp']:.2f}°C")
        print(f"  Wind Speed: {today_weather['wind_speed']:.2f} mph")
    else:
        print("  No consolidated weather data available.")
else:
    print("Could not retrieve weather data.")

This snippet illustrates how a developer might have structured a direct API call rather than relying on a full SDK, showcasing the common pattern of making HTTP requests and processing JSON responses. The requests library is a popular choice for this in Python, known for its user-friendly API for making web requests, as documented in the Requests library documentation.

Community libraries

MetaWeather significantly benefited from community-contributed libraries, which extended its reach across various programming environments. These libraries were developed and maintained by third-party developers who sought to simplify interaction with the MetaWeather API for specific languages or frameworks. Popular community libraries often included features such as:

• Language Bindings: Wrappers for Python, JavaScript, Ruby, PHP, and other languages.
• Type Safety: For languages like TypeScript, providing type definitions for API responses.
• Error Handling: Standardized error reporting and exception handling.
• Caching Mechanisms: To reduce redundant API calls and improve performance.
• Asynchronous Support: For non-blocking API requests in modern applications.

While these community efforts were valuable, their maintenance and continued functionality were contingent on the enthusiasm of their creators and the ongoing operation of the MetaWeather service. With the shutdown of MetaWeather in March 2023, these community libraries generally became obsolete and unmaintained. Developers seeking current weather data now typically migrate to active weather API providers, often utilizing their official SDKs or building custom integrations based on their updated API specifications.

The existence of a vibrant community of developers building client libraries around an API is a strong indicator of its popularity and utility. Open-source development models often lead to a diverse ecosystem of tools that enhance the developer experience, as also observed in other API ecosystems like Stripe's Go SDK, which benefits from community feedback and contributions alongside official support.