Metadata-Version: 2.1
Name: vencopy
Version: 0.1.0
Summary: Vehicle Energy Consumption in Python: A tool to simulate load flexibility of electric vehicle fleets.
Home-page: https://gitlab.com/dlr-ve/vencopy
Author: Niklas Wulff
Author-email: niklas.wulff@dlr.de
License: BSD 3-clause
Description: [![License: BSD 3-Clause](https://img.shields.io/badge/license-BSD%203--Clause-blue.svg)](https://github.com/TechSmith/hyde/blob/master/LICENSE.txt)
        
        
        
        # VencoPy README File
        - Authors: Niklas Wulff, Fabia Miorelli
        - Contact: niklas.wulff@dlr.de
        - Version: 0.1.0
        
        Contents
        ========
        
         * [Description](#description)
         * [Installation](#installation)
         * [Codestyle](#codestyle)
         * [Documentation](#documentation)
         * [Want to contribute?](#want-to-contribute)
        
        Description
        ---
        A data processing tool offering hourly demand and flexibility profiles for future electric vehicle fleets in an aggregated manner.
        
        Installation
        ---
        Install using the environment management system conda, open the conda console navigate to your VencoPy folder and run the following commands
        
        ```python
        conda create -f requirements.yml
        [confirm]
        ```
        
        An environment named "VencoPy_env" will be created. Activate by entering
        ```python
        conda activate VencoPy_env
        ```
        
        Build your package locally (compared to from the package index PyPI) by navigating to the folder that you checked out 
        and typing
        
        ```python
        pip install .
        ```
        
        Navigate to a parent directory where you want to create your VencoPy user folder in and type
        
        ```python
        vencopy
        ```
        
        You will be prompted for a userfolder name, type it and hit enter. Your VencoPy user folder will now be created. It
        will look like this
        
        .
        +-- FOLDERNAME
        |   +-- config
        |   |   +-- evaluatorConfig.yaml
        |   |   +-- flexConfig.yaml
        |   |   +-- globalConfig.yaml
        |   |   +-- gridConfig.yaml
        |   |   +-- localPathConfig.yaml
        |   |   +-- parseConfig.yaml
        |   |   +-- tripConfig.yaml
        |   +-- output
        |   |   +-- dataParser
        |   |   +-- evaluator
        |   |   +-- flexEstimator
        |   |   +-- gridModeler
        |   |   +-- tripDiaryBuilder
        |   +-- tutorials
        |   |   +-- ...
        |   +-- run.py
        
        The configs in the config folder are the main interface between the user and the code. In order to learn more about 
        them, check out our tutorials. For this you won't need any additional data.
        
        To run VencoPy in full mode, you will need the data set Mobilität in Deutschland (German for mobility in Germany), you
        can request it here from the clearingboard transport: https://daten.clearingstelle-verkehr.de/order-form.html Currently, 
        VencoPy is only tested with the B2 data set.
        
        In your localPathConfig.yaml, please enter the path to your local MiD STATA folder, it will end on .../B2/STATA/. Now
        open your user folder in an IDE, configure your interpreter (environment) or type 
        
        ```python
        python run.py
        ``` 
        
        and enjoy the tool!
        
        
        
        Codestyle
        ---
        We use PEP-8, with the exception of lowerCamelCase for method and variable names as well as UpperCamelCase for classes
        
        Documentation
        ---
        Build docu from a conda bash with activated environment typing
        
        sphinx-build -b html ./docs/ ./build/
        
        Want to contribute?
        ---
        Great, welcome on the VP team! Please read our contribute section in the docu and reach out to Niklas 
        (niklas.wulff@dlr.de). 
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
