View source for EMD-API - Climate Data Access

== Origin and Purpose ==
[[File:EMDAPI_451x303.jpg|thumb|350px|right]]EMDAPI is a software library by EMD delivering a unified interface to a wide range of climate data. EMDAPI helps consultants, analysts and scientists working with high-resolution climate data in achieving their goals in an efficient way, it has the following key-features: 

* '''40+ climate datasets''': EMDAPI provides access more than 40 of the best climate datasets and allows access to more than 1Pb of data. 
* '''Unified interface''': The unified interface which allows for integration to internal processes and tools - and also very efficient uncertainty analysis with gigabytes of data easily accessed. 
* '''Trusted datasets''': The EMDAPI builds upon the trusted data-bases and data-sources that have been used through the [http://help.emd.dk/mediawiki/index.php?title=Main_Page online-data services] in windPRO for more than a decade. 
* '''Built on open standards''': he EMDAPI is a [https://en.wikipedia.org/wiki/Representational_state_transfer REST] based service that implements the [https://swagger.io/specification/ OpenAPI] standard]. 
* '''Available from any development tool''': Access to the climate databases is available from your preferred development platform - C#, R, python, html, java, php, scala and swift. Just use the OpenAPI tools to generate the client software for your preferred platform.

== API Access  ==

The API is currently (August 2020) in beta-release. 
To see more documentation and to access the data-services, please visit the API through the following URL:

* http://api.emd.dk

== Python - Installation and Test == 
[[Image:EgmondAanZee.jpg|thumb|350px|right|Data nodes near the Egmond Aan Zee Offhore ]]The simplest way to use the EMDAPI with python is to install the client software in a virtual environment. If you are using CONDA or [https://docs.conda.io/en/latest/miniconda.html MINICONDA], we recommend that you create a new virtual environment and use a recent 3.x version of python. When the virtual environment is created, then activate the environment.
<pre>
conda create -n emdapi python=3.8
conda activate emdapi
</pre>

Install the required packages needed in order to do data-science and use the examples provided within the jupyter notebooks:
<pre>
conda install pandas numpy matplotlib basemap basemap-data-hires jupyter 
</pre>

Download the [http://api.emd.dk/static/python-client-generated.zip zipped-file] holding the OpenAPI python client. Unpack the file and install it within your virtual environment:
<pre>
python setup.py install
</pre>

Give the installation a test-drive using the jupyter notebooks provided
<pre>
jupyter notebook
</pre>