Metadata-Version: 2.1
Name: dse-do-utils
Version: 0.5.5.1
Summary: Decision Optimization utilities for IBM Watson Studio projects
Home-page: https://github.com/IBM/dse-decision-optimization-utilities
Author: Victor Terpstra
Author-email: vterpstra@us.ibm.com
License: UNKNOWN
Project-URL: Source, https://github.com/IBM/dse-decision-optimization-utilities
Project-URL: Documentation, https://ibm.github.io/dse-decision-optimization-utilities/
Project-URL: IBM Decision Optimization, https://www.ibm.com/analytics/decision-optimization
Description: # DSE_DO_Utils
        Decision Optimization utilities for IBM Watson Studio Local and ICPd projects.
        
        [Source (GitHub)](https://github.com/IBM/dse-decision-optimization-utilities)<br>
        [Documentation (GitHubPages)](https://ibm.github.io/dse-decision-optimization-utilities/)
        
        This repository contains the package `dse_do_utils`. This can be installed using pip.
        
        ## Important
        From v0.5.0.0, the dse-do-utils require the package decision-optimization-client==1.0.0 and no longer the former dd-scenario.
        This package is NOT installed by default, neither in CPD3.5 not CPD4.0.
        DSE-DO-Utils v0.5.0.0 works in both CPD 3.5 and 4.0.
        dd-scenario works in CPDv3.5, but NOT in CPDv4.0.
        
        ## Main classes:
        1. ScenarioManager. Reads and writes table data from and to all combinations of csv-files, Excel spreadhseet and DO scenario.
        2. DataManager. A DataManager is mostly a container for data and functions for pre- and post-processing. 
        Can be subclassed and stored in a script to be able to share code between multiple notebooks. 
        Also contains some utilities for data manipulation, like the crossjoin.
        3. OptimizationEngine. Also mostly a container for functions around creating an optimization model and using the docplex APIs. 
        Can be subclassed and stored in a script to be able to share code between multiple notebooks.
        Also contains some functions to create dvars and export .lp files.
        4. ScenarioPicker. Interactively pick an existing scenario from a drop-down menu in a notebook. Typically used in visualization notebooks. 
        5. MapManager. For creating map visualizations using Folium.
        
        ## Installation on CPDv4.5
        For Cloud Pak for Data v4.5.
        
        ### Install in customized environment
        CPDv4.5 allows for easy customization of environments.
        Add the following to the customization configuration:
        
        ```
        channels:
        dependencies:
          - pip
          - pip:
            - dse-do-utils==0.5.5.0
            - decision-optimization-client==1.1.0
        ```
        This automatically downloads dse-do-utils from PyPI and installs the package.
        
        
        For air-gapped systems that have no access to PyPI:
        1. Download the package from PyPI/Conda from an internet connected system as a wheel/zip file
        2. Upload the wheel/zip as a data asset, or place in any location in the JupyterLab file system
        3. Add a pip dependency in the environment yaml:
        
        ```
        dependencies:
          - pip:
            - file:///userfs/packages/dse_do_utils-0.5.4.5b4-py3-none-any.whl
        ```
        
        This downloads the package as a wheel/zip and puts it in the data assets
        ```
        !pip download dse-do-utils -d /project_data/data_asset/
        ```
        Then move the wheel/zip to the Data Assets. 
        See the `InstallationReadMe.md` for more details on installation and usage in other cases.
        
        ## Import
        Then import the required classes from  `dse_do_utils`:
        ```
        from dse_do_utils import ScenarioManager, DataManager
        ```
        This is the basics. For many ore details on other usage, see `InstallationReadMe.md` 
        
        ## Target environments
        To be used within:
        1. CP4D on-prem v4.0 and up
        4. CP4DaaS / WS Cloud (version 0.4.0.0 and up)
        
        ## DO Model Builder and WML environments
        When developing and using optimization models, there are 3 different environments the Python DO model might run in:
        1. A notebook environment. 
        2. The DO Model Builder environment.
        3. The WML deployment environment.
        
        From CP4D 4.6, all environments can be customized from PyPI packages and wheel files
        
        ## Scope of classes/modules
        The classes `OptimizationEngine` and  `DataManager` are intended to be used within the optimization model code 
        that will run in the Model Builder and WML deployment. All other classes, in particular the `ScenarioManager` are 
        designed to be used outside of the Model Builder or WML, e.g. within `#dd-ignore` cells.
        
        ## Requirements
        This package requires:
        1. [decision-optimization-client](https://ibmdecisionoptimization.github.io/decision-optimization-client-doc/). This package provides an interface to the DO scenarios. 
        This package is available in PyPI, however it only runs within CP4D/CP4DaaS.
        2. [docplex](http://ibmdecisionoptimization.github.io/docplex-doc/mp/index.html). This package interfaces with the CPLEX and CP Optimizer optimization engines.
        3. [folium](https://github.com/python-visualization/folium). Map visualization. Only for the MapManager.
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Documentation :: Sphinx
Description-Content-Type: text/markdown
