Difference between revisions of "EMD-API - Climate Data Access"

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(Python - Installation and Test)
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Install the required packages needed in order to do data-science and use the examples provided within the jupyter notebooks. We have have validated this setup using specific package versions (used in the commands below).  
 
Install the required packages needed in order to do data-science and use the examples provided within the jupyter notebooks. We have have validated this setup using specific package versions (used in the commands below).  
 
<pre>
 
<pre>
conda install pandas=1.1.0 numpy=1.19.1
+
conda install -c conda-forge pandas=1.1.0 numpy=1.19.1
conda install matplotlib=3.3.1 basemap=1.2.2 basemap-data-hires=1.2.2  
+
conda install -c conda-forge matplotlib=3.3.1 basemap=1.2.2 basemap-data-hires=1.2.2  
conda install jupyter=1.0.0 ipykernel=5.3.4  
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conda install -c conda-forge jupyter=1.0.0 ipykernel=5.3.4  
 
</pre>
 
</pre>
  

Revision as of 09:15, 8 September 2020

Origin and Purpose

EMDAPI 451x303.jpg
EMDAPI is a software library from EMD International. It delivers 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:
  • Instant data delivery: All datasets within the EMDAPI are ready processed and requests are served within seconds or minutes
  • 40+ climate datasets: EMDAPI provides access more than 40 of the best local, regional and global 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: EMDAPI builds upon the trusted data-bases and data-sources that have been used through the online-data services in windPRO for more than a decade.
  • Built on open standards: EMDAPI is a REST based service that implements the 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.

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:

Python - Installation and Test

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 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.
conda create -n emdapi python=3.8.5
conda activate emdapi

Install the required packages needed in order to do data-science and use the examples provided within the jupyter notebooks. We have have validated this setup using specific package versions (used in the commands below).

conda install -c conda-forge pandas=1.1.0 numpy=1.19.1
conda install -c conda-forge matplotlib=3.3.1 basemap=1.2.2 basemap-data-hires=1.2.2 
conda install -c conda-forge jupyter=1.0.0 ipykernel=5.3.4 

Download the zipped-file holding the OpenAPI python client.
Unpack the file and install it within your virtual environment:

python setup.py install

Make sure that the new emdapi virtual enviroment (python-kernel) is available to be used with jupyter-notebook environment:

python -m ipykernel install --user --name=emdapi

In order to test your setup and learn to use the EMDAPI, we suggest that you download the jupyter-notebook examples that we have created - here.
Unpack the zip files and run the command below in your terminal or command-shell.
If jupyter prompts for you to select another python-kernel, then select the emdapi kernel (may also be selected directly from the 'Kernel' drop-down menu).

jupyter notebook

Within the internet-browser (and jupyter user-interface), run select the notebook file (*.ipynb).
Then work your way through through each example provided.

Client Software Other Languages and Tools

A list of client software generated from the swagger editor is found below.

  1. Python
  2. CSharp
  3. HTML2
  4. Dynamic HTML
  5. R
  6. Java
  7. Scala
  8. PHP
  9. Swift5

If you want to generate the client libries yourself - or use other tool than mentioned above - one possible process is to:

  1. Download the OpenAPI (openapi.yaml) description file - here
  2. Load it into the swagger editor - here
  3. Choose to "Generate Client" from the drop-down menu within the swagger editor.