EMD-API - Wind Energy Index Service: Difference between revisions

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* Also note, that we provide a python (jupyter notebook) example to get you kick-started in using our API-services and to integrate towards your own services and tools.
* Also note, that we provide a python (jupyter notebook) example to get you kick-started in using our API-services and to integrate towards your own services and tools.


== Get Help, Get Access or See Operational Status ==  
== Access ==
* ''Access:'' Contact the emd-sales department to obtain access: [mailto:sales@emd.dk sales@emd.dk].
The API is currently (November 2020) in beta-release. To see more documentation and to access the data-services, please visit the API through the following URL's:
* ''Help:''
 
** Contact the EMD support hotline: [mailto:support@emd.dk support@emd.dk].
* EMD-API Overview (Wiki) - [https://help.emd.dk/mediawiki/index.php?title=Category%3AEMD-API here].
** Contact our technical specialist -  Senior Consultant Henrik S. Pedersen: [mailto:hsp@emd.dk hsp@emd.dk].
* EMD-API Main Page (API) - [https://api.emd.dk here].
* ''Operational Status'' - at separate [[EMD-API - Operational Status|Operational Status]] wiki-page
* EMD-API Climate Data UI (API) -  [https://api.emd.dk/climate-data/ui/ here].


== Python - Installation ==  
== Python - Installation ==  

Revision as of 16:25, 16 December 2020

Comissioning of On-Shore Wind Turbines in Denmark.

Introduction

The wind-energy-index service is available as a global service - providing reliable wind-index information for any part of the world. The service is available from a REST / OPENAPI interface. This page describes how to install the service - and how to consume it from a python client. Resources for the OpenAPI standard and the data model are here:

Please note:

  • This EMD-API introduction is aimed at programmers, modellers or analysts who are working with machine-driven interfaces and workflows, typically using programming languages like python or R.
  • Also note, that we provide a python (jupyter notebook) example to get you kick-started in using our API-services and to integrate towards your own services and tools.

Access

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

  • EMD-API Overview (Wiki) - here.
  • EMD-API Main Page (API) - here.
  • EMD-API Climate Data UI (API) - here.

Python - Installation

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.

Open your Anaconda Prompt. Copy-paste the following lines: 

conda create -n emdapiwindindex python=3.8.5
conda activate emdapiwindindex

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).

In the Anaconda Prompt, copy-paste the following lines, one by one: 

conda install -c conda-forge pandas=1.1.0 numpy=1.19.1
conda install -c conda-forge jupyter=1.0.0 ipykernel=5.3.4

Download the zip-file holding the OpenAPI python client for the emdapi wind-index-service.
Unpack the file and install it within your virtual environment:

In the Anaconda Prompt: Move to the folder, where you have unpacked the zipped file. Copy-paste the following line: 

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=emdapiwindindex
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