Metadata-Version: 2.1
Name: dse_do_utils
Version: 0.3.0.1
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.
        
        ## 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.
        6. DeployedDOModel. Interfacing from Python to a deployed DO model.
        
        ## Installation (CPDv2.5)
        (For Cloud Pak for Data v2.5)
        
        CPDv2.5 is very different from the previous versions and it has a significant impact on how the dse-do-utils can be installed and used.
        
        Options:
        1. Install using pip in a customized environment. This applies to both Jupyter and JupyterLab.
        2. Install as a package in JupyterLab.
        3. Install as modules in Jupyter
        4. Install/use as modules in the DO Model Builder
        
        ### Install in customized environment
        CPDv2.5 allows for easy customization of environments.
        Add the following to the customization configuration:
        ```
        - pip:
            - dse-do-utils=0.3.0.0
        ```
        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
        3. Install package from wheel/zip
        
        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) 
        Next, set the environment customization to:
        ```
        - pip:
            - dse-do-utils --no-index --find-links=/project_data/data_asset/dse_do_utils-0.3.0.0.tar.gz
        ```
        
        See the `InstallationReadMe.md` for many 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. CPDv2.1 (version 0.2.2.3 is preferred. But version 0.3.0.0 should be backwards compatible.)
        2. CPDv2.5 (version 0.3.0.0 and up)
        3. WSLv1.2.3 with Python 2.7 (version 0.2.2.3 only)
        
        ## Requirements
        This package requires:
        1. [dd-scenario](https://pages.github.ibm.com/IBMDecisionOptimization/dd-scenario-api/dd-scenario-client-python/doc/build/html/). This package provides an interface to the DO scenarios. 
        This package is only available within WSL and ICPd. It cannot be pip installed in other environments.
        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
