How to Install and Uninstall python36-azure-agrifood-farming Package on openSuSE Tumbleweed

Last updated: May 18,2024

Deprecated! Installation of this package may no longer be supported.

1. Install "python36-azure-agrifood-farming" package

In this section, we are going to explain the necessary steps to install python36-azure-agrifood-farming on openSuSE Tumbleweed


    
        
            $
        

        
            
                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                python36-azure-agrifood-farming
            
                    
    
    Copied

2. Uninstall "python36-azure-agrifood-farming" package

This tutorial shows how to uninstall python36-azure-agrifood-farming on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                python36-azure-agrifood-farming
            
                    
    
    Copied

3. Information about the python36-azure-agrifood-farming package on openSuSE Tumbleweed

Information for package python36-azure-agrifood-farming:
--------------------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python36-azure-agrifood-farming
Version : 1.0.0b1-1.2
Arch : noarch
Vendor : openSUSE
Installed Size : 3,2 MiB
Installed : No
Status : not installed
Source package : python-azure-agrifood-farming-1.0.0b1-1.2.src
Summary : Microsoft Azure AgriFood Farming client library
Description :
FarmBeats is a B2B PaaS offering from Microsoft that makes it easy for AgriFood companies
to build intelligent digital agriculture solutions on Azure. FarmBeats allows users to
acquire, aggregate, and process agricultural data from various sources (farm equipment,
weather, satellite) without the need to invest in deep data engineering resources. Customers
can build SaaS solutions on top of FarmBeats and leverage first class support for model
building to generate insights at scale.
Use FarmBeats client library for Python to do the following.
* Create & update farmers, farms, fields, seasonal fields and boundaries.
* Ingest satellite and weather data for areas of interest.
* Ingest farm operations data covering tilling, planting, harvesting
and application of farm inputs.