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.. _user_installation:
Installation
=================
.. contents:: Table of Contents
:local:
There are different options on how to install a Python package, mostly depending
on your preferred tools and what you want to do with it. The easiest
way is in most cases to use pip (see :ref:`below <user_installation_pip>`).
.. _user_installation_requirements:
Requirements
-----------------------------
.. include:: ../snippets/requirements.rst
Installer requirements: `setuptools <https://pypi.org/project/setuptools>`_
.. _user_installation_pip:
Pip
-----------------------------
To install the latest release of pyDataverse from PyPI, simply run this
`pip <https://pypi.org/project/pip/>`_
command in your terminal of choice:
.. include:: ../snippets/pip-install.rst
.. _user_installation_pipenv:
Pipenv
-----------------------------
`Pipenv <https://pipenv.pypa.io/en/latest/>`_ combines pip and virtualenv.
.. code-block:: shell
pipenv install pyDataverse
.. _user_installation_source-code:
Conda
-----------------------------
pyDataverse is also available through `conda-forge <https://conda-forge.org/>`_.
.. code-block:: shell
conda install pyDataverse -c conda-forge
Source Code
-----------------------------
PyDataverse is actively developed on GitHub, where the code is
`always available <https://github.com/gdcc/pyDataverse>`_.
You can either clone the public repository:
.. code-block:: shell
git clone git://github.com/gdcc/pyDataverse.git
Or download the archive of the ``master`` branch as a zip:
.. code-block:: shell
curl -OL https://github.com/gdcc/pyDataverse/archive/master.zip
Once you have a copy of the source, you can embed it in your own Python
package:
.. code-block:: shell
cd pyDataverse
pip install .
.. _user_installation_development:
Development
-----------------------------
To set up your development environment, see
:ref:`contributing_working-with-code_development-environment`.
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