Open-Meteo SDKs & Libraries: Official and Community Tools (2026)

SDKs overview

Open-Meteo provides Software Development Kits (SDKs) and client libraries to facilitate integration with its various weather APIs. These tools abstract the underlying HTTP requests and JSON parsing, allowing developers to focus on utilizing weather data within their applications. The available SDKs support multiple programming languages, reflecting common development environments. Open-Meteo's API design prioritizes simplicity, which is reflected in the straightforward nature of its official client libraries, as noted in their Open-Meteo API documentation.

The primary benefit of using an SDK or client library is the reduction of boilerplate code. Instead of manually constructing URLs, handling API keys, and deserializing responses, developers can interact with the API through native language constructs. This approach helps minimize errors and speeds up the development process. Most Open-Meteo SDKs are designed to work with all core APIs, including the Open-Meteo Weather Forecast API, Historical Weather API, and Marine Weather API, providing a consistent interface across different data types.

While official SDKs are provided by Open-Meteo, the open-source nature of many programming ecosystems also fosters community-contributed libraries. These community efforts can sometimes offer alternative approaches, additional helper functions, or specialized integrations not present in the official offerings. Developers often consult official documentation for detailed API specifications, as provided by Mozilla Developer Network HTTP status codes documentation, when troubleshooting SDK behavior or designing robust error handling.

Official SDKs by language

Open-Meteo offers official client libraries for several widely used programming languages. These libraries are maintained by the Open-Meteo team to ensure compatibility with the latest API versions and features. Each SDK provides methods corresponding to the various API endpoints, allowing developers to request specific weather parameters, historical data, or marine forecasts with structured function calls.

The official SDKs are typically found on language-specific package managers, making installation and dependency management straightforward. They often include examples and clear documentation directly integrated into the code, helping developers get started quickly. The following table outlines some of the key official SDKs:

Each of these SDKs is designed to encapsulate the API's request parameters and response structures. For instance, a Python developer using openmeteo-requests would pass latitude, longitude, and desired forecast variables as arguments to a function, receiving a Python object containing the parsed weather data. This approach is consistent across languages, aiming to provide a native feel for each development environment.

Installation

Installing Open-Meteo SDKs typically involves using the standard package manager for the respective programming language. Each method ensures that the library and its dependencies are correctly downloaded and made available within your project.

Python

For Python, the openmeteo-requests library can be installed using pip, the Python package installer. This command retrieves the latest version from the Python Package Index (PyPI).

pip install openmeteo-requests

After installation, you can import the library into your Python scripts. Python's robust ecosystem, supported by resources like the official Python documentation, makes managing these external packages efficient.

Node.js

Node.js developers can install the openmeteo package via npm (Node Package Manager). This command adds the package to your project's node_modules directory and updates your package.json file.

npm install openmeteo

Alternatively, if you're using Yarn, you can install it with:

yarn add openmeteo

PHP

PHP projects commonly use Composer for dependency management. To install the Open-Meteo PHP SDK:

composer require open-meteo/php-sdk

This command downloads the necessary files and updates your composer.json and composer.lock files.

Java

For Java projects, Open-Meteo SDKs are typically included as dependencies in your build configuration, such as Maven or Gradle. You would add the appropriate entry to your pom.xml (Maven) or build.gradle (Gradle) file. Specific dependency coordinates can be found in the Open-Meteo documentation for Java.

Example Maven dependency (coordinates might vary):

<dependency>
    <groupId>com.openmeteo</groupId>
    <artifactId>openmeteo-java</artifactId>
    <version>1.0.0</version>
</dependency>

Go

Go modules are used to install the Go SDK. Run the following command in your terminal within your Go project:

go get github.com/open-meteo/go-sdk

Ruby

RubyGems is the package manager for Ruby. To install the Open-Meteo Ruby gem:

gem install openmeteo-ruby

R

For R, packages are installed directly from CRAN or other repositories:

install.packages("openmeteo")

Quickstart example

This section provides a quickstart example using the Python SDK to fetch current weather data for a specific location. This demonstrates the basic process of initializing the client, making a request, and accessing the returned data.

Python Quickstart

The following Python code snippet illustrates how to retrieve current temperature, wind speed, and weather code for a given latitude and longitude using the openmeteo-requests library.

import openmeteo_requests
import requests_cache

# Setup a cache for requests to reduce redundant API calls
cache_session = requests_cache.CachedSession('.cache', expire_after=3600)
openmeteo = openmeteo_requests.Client(session=cache_session)

# Define the API endpoint and parameters
url = "https://api.open-meteo.com/v1/forecast"
params = {
    "latitude": 52.52,
    "longitude": 13.41,
    "current": ["temperature_2m", "wind_speed_10m", "weather_code"],
    "timezone": "Europe/Berlin"
}

# Make the API request
responses = openmeteo.weather_api(url, params=params)

# Process the response
response = responses[0] # Assuming a single location request

print(f"Coordinates {response.Latitude()}°N {response.Longitude()}°E")
print(f"Timezone {response.Timezone()} {response.TimezoneAbbreviation()}")
print(f"Elevation {response.Elevation()} m asl")

current = response.Current()
current_temperature_2m = current.Variables(0).Value()
current_wind_speed_10m = current.Variables(1).Value()
current_weather_code = current.Variables(2).Value()

print(f"Current time: {current.Time()}")
print(f"Current temperature_2m: {current_temperature_2m}°C")
print(f"Current wind_speed_10m: {current_wind_speed_10m} m/s")
print(f"Current weather_code: {current_weather_code}")

This example demonstrates setting up a cached session, defining the target API URL and parameters, executing the request, and extracting specific data points from the structured response object. The use of a CachedSession (from requests_cache) is a common practice for reducing unnecessary API calls and improving performance, especially in development. Open-Meteo's APIs typically return data in arrays, allowing for requests to multiple locations or time series data in a single call, as detailed in the Open-Meteo current weather API reference.

For more advanced usage, such as historical data retrieval or marine forecasts, the parameter structure would change, but the overall method of using the SDK remains consistent. Developers should refer to the specific API documentation pages on Open-Meteo's website for the exact parameters required for each endpoint.

Community libraries

Beyond the official SDKs, the developer community has contributed various libraries and wrappers for Open-Meteo. These community-driven projects can offer different features, architectural styles, or cater to niche use cases not covered by official offerings. They typically leverage the underlying HTTP API, similar to how official SDKs operate, but might provide alternative interfaces or additional convenience methods.

Examples of community contributions might include:

• Specialized data visualization tools: Libraries that directly integrate Open-Meteo data with charting or mapping libraries.
• Framework-specific integrations: Wrappers designed for particular web frameworks (e.g., a Django or Flask plugin for Python, or a Laravel package for PHP).
• Additional utility functions: Helpers for common tasks like unit conversion, more advanced error handling, or specific data transformations.
• Alternative language support: Libraries for languages not officially supported by Open-Meteo, extending accessibility.

When considering a community library, it is advisable to evaluate its maintenance status, community support, and alignment with the official API specifications. Checking the project's repository (e.g., GitHub) for recent commits, open issues, and pull requests can provide insight into its ongoing viability. While the official Open-Meteo documentation remains the primary source for API details, community libraries can sometimes offer practical examples or solutions to specific integration challenges.

Developers who use community libraries should be aware that support and updates might vary compared to official SDKs. It's often beneficial to understand the core API structure when using community tools, as this knowledge facilitates debugging and ensures proper data interpretation. The Open-Meteo community forums or discussion boards (if available) can also be valuable resources for discovering and getting support for these unofficial integrations, complementing the information found on general developer resources such as Google's Open Source initiatives.