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docs/sphinx/source/installation.rst

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.. _installation:
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Installation
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============
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Installing pvlib-python is similar to installing most other scientific
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python packages. The instructions below describe how to install
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pvlib-python under a few different conditions. Most of the information
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on the `Pandas installation page
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<http://pandas.pydata.org/pandas-docs/stable/install.html>`_ is also
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applicable to pvlib-python.
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If you have Python
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------------------
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To obtain the most recent stable release of pvlib-python, use
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`conda <http://conda.pydata.org/docs/>`_ or `pip <https://pip.pypa.io>`_::
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conda install -c pvlib pvlib
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pip install pvlib
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If your system complains that you don't have access privileges or asks
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for a password then you're probably trying to install pvlib into your
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system's Python distribution. This is usually a bad idea and you should
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instead follow the :ref:`nopython` instructions below.
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.. _nopython:
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If you don't have Python
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------------------------
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There are many ways to install Python on your system, but the Anaconda
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Scientific Python distribution provides by far the easiest way for new
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users to get started. Anaconda includes all of the popular libraries
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that you'll need for pvlib, including Pandas, NumPy, and SciPy.
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"Anaconda installs cleanly into a single directory, does not require
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Administrator or root privileges, does not affect other Python installs
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on your system, or interfere with OS 8000 X Frameworks." -Anaconda
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Documentation.
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#. Install the full Anaconda Scientific Python distribution available
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`here <https://store.continuum.io/cshop/anaconda/>`_
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#. Install pvlib: ``conda install -c pvlib pvlib``
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If you have trouble, see the `Anaconda
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FAQ <http://docs.continuum.io/anaconda/faq.html>`_, Google your error
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messages, or make a new issue on our `Issues
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page <https://github.com/pvlib/pvlib-python/issues>`_.
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Working at the bleeding edge
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----------------------------
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We strongly recommend working in a `virtual environment
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<http://astropy.readthedocs.org/en/latest/development/workflow/
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virtual_pythons.html>`_ if you're going to use the development versions
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of the code. There are many ways to use virtual environments in Python,
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but Anaconda again provides the easiest solution:
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#. Create a new conda environment for pvlib and pre-install a
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handful of packages into the environment:
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``conda create --name pvlibdev python pandas scipy``
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#. Activate the new environment: ``source activate pvlibdev``
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#. Install the latest development version of pvlib:
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#. If you don't plan to modify the source-code:
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``pip install git+https://github.com/pvlib/pvlib-python.git``
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#. If you do plan to modify the source code:
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Use the GitHub GUI application or git command-line tool to
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clone this repository to your computer, then navigate your
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command-line to the top-level pvlib-python directory,
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then ``pip install -e .``
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#. You may also consider installing additional packages into your
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development environment:
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``conda install jupyter ipython seaborn nose flake8``
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The `conda documentation
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<http://conda.pydata.org/docs/using/index.html>`_ has more information
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on how to use virtual environments. You can also add ``-h`` to most
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conda commands to get help (e.g. ``conda -h`` or ``conda env -h``)

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