.. _getting_started_label: ~~~~~~~~~~~~~~~ Getting started ~~~~~~~~~~~~~~~ DHNx is a toolbox for optimization and simulation of district heating and cooling systems. .. contents:: `Contents` :depth: 1 :local: :backlinks: top Using DHNx ================ Installation ------------ If you have a working Python3 environment, use pypi to install the latest oemof version: :: pip install dhnx For Installing the latest (dev) version, clone DHNx from github: :: git clone https://github.com/oemof/DHNx.git Now you can install it your local version of DHNx using pip: :: pip install -e .. note:: DHNx uses geopandas and osmnx as extra requirements for some functions related to the processing of spatial data. On Windows machines, you might encounter troubles installing geopandas via ``pip install geopandas``. Try to install geopandas in an EMTPY environment with ``conda install geopandas``, first. And second, install osmnx with ``pip install osmnx`` (tested with Python 3.8). Also check `geopandas.org `_. Examples -------- Examples are provided `here `_. Also, have a look at the :ref:`examples_label` section for some more explanation. Contributing to DHNx ========================== Contributions are welcome. You can write issues to announce bugs or errors or to propose enhancements. Or you can contribute a new approach that helps to model district heating/cooling systems. If you want to contribute, fork the project at github, develop your features on a new branch and finally open a pull request to merge your contribution to DHNx. For testing, `tox` is used. Either run simply `tox` for all checks, or specify your test run depending on your local python environment, e.g. by: :: tox -e "clean, check, docs, py38" As DHNx is part of the oemof developer group we use the same developer rules. You will find more information in the `oemof meta documentation `_.