Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.1%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: areleu
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: main
  • Size: 61.5 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed over 2 years ago
Metadata Files
Readme Contributing License Citation

README.md

Welcome to venco.py!

  • Authors: Niklas Wulff, Fabia Miorelli
  • Contact: vencopy@dlr.de

Contents

Description

A data processing tool estimating hourly electric demand and flexibility profiles for future electric vehicle fleets. Profiles are targeted to be scalable for the use in large-scale energy system models.

Installation

Depending on if you want to use venco.py or if you want to contribute, there are two different installation procedures described in venco.py's documentation:

I want to apply the tool

I want to contribute to the codebase, the documentation or the tutorials

In order to start using venco.py, check out our tutorials. For this you won't need any additional data.

To run venco.py 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 Alternatively you can use venco.py with any National Travel Survey or mobility pattern dataset.

Codestyle

We use PEP-8, with the exception of UpperCamelCase for class names.

Documentation

The documentation can be found here: https://dlr-ve.gitlab.io/esy/vencopy/vencopy/ To build the documentation from a conda bash with an activated environment type:

python sphinx-build -b html ./docs/ ./build/

Useful Links

  • Documentation: https://dlr-ve.gitlab.io/esy/vencopy/vencopy/
  • Source code: https://gitlab.com/dlr-ve/vencopy
  • PyPI release: https://pypi.org/project/vencopy/
  • Licence: https://opensource.org/licenses/BSD-3-Clause

Want to contribute?

Great, welcome on the venco.py team! Please read our contribute section in the documentation and reach out to Niklas (niklas.wulff@dlr.de). If you experience difficulties on set up or have other technical questions, join our gitter community

Owner

  • Name: e_arel
  • Login: areleu
  • Kind: user
  • Company: DLR

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: venco.py
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Niklas
    family-names: Wulff
    email: niklas.wulff@dlr.de
    affiliation: German Aerospace Center (DLR)
    orcid: "https://orcid.org/0000-0002-4659-6984"
  - given-names: Fabia
    family-names: Miorelli
    email: fabia.miorelli@dlr.de
    affiliation: German Aerospace Center (DLR)
    orcid: "https://orcid.org/0000-0001-5095-5401"
repository-code: "https://gitlab.com/dlr-ve/esy/vencopy/vencopy"
license: BSD-3-Clause
version: 1.0.0
date-released: "2024-02-01"

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Dependencies

pyproject.toml pypi
  • click >= 8.1.3, < 9
  • matplotlib >= 3.7.2
  • pandas <= 1.5.2
  • pyyaml >= 6.0, < 7
  • scipy >= 1.9.3