Installing pvlib-python ranges from trivial to difficult depending on your python experience, how you want to use pvlib, and your system configuration.

Do you already have Python and the NumPy and Pandas libraries?

If the answer to this is No, follow the If you don’t have Python instructions to obtain the Anaconda Python distribution before proceeding.

Do you want to use the pvlib-python as-is, or do you want to be able to edit the source code?

If you want to use pvlib-python as-is, follow the simple Install standard release instructions.

If you want to be able to edit the source code, follow the Install as an editable library instructions.

Installing pvlib-python is similar to installing most scientific python packages, so see the References section for further help.

If you don’t have Python

There are many ways to install Python on your system, but the Anaconda Scientific Python distribution provides by far the easiest way for new users to get started. Anaconda includes all of the popular libraries that you’ll need for pvlib, including Pandas, NumPy, and SciPy.

Anaconda installs cleanly into a single directory, does not require Administrator or root privileges, does not affect other Python installs on your system, or interfere with OSX Frameworks. – The Anaconda Documentation
  1. Install the full Anaconda Scientific Python distribution available at

See the Anaconda FAQ for more information.

You can now install pvlib-python by one of the methods below.

Install standard release

To install the most recent stable release of pvlib-python in a non-editable way, use conda (recommended if you use the Anaconda Python distribution) or pip (works with any Python distribution):

conda install -c pvlib pvlib

pip install pvlib

If your system complains that you don’t have access privileges or asks for a password then you’re probably trying to install pvlib into your system’s Python distribution. This is usually a bad idea and you should follow the If you don’t have Python instructions before installing pvlib.

You may still want to download the Python source code so that you can easily get all of the Jupyter Notebook tutorials. Either clone the git repository or go to the Releases page to download the zip file of the most recent release. You can also use the nbviewer website to choose a tutorial to experiment with. Go to our nbviewer tutorial page.

Install as an editable library

Installing pvlib-python as an editable library involves 3 steps:

  1. Obtain the source code
  2. Set up a virtual environment
  3. Install the source code

None of these steps are particularly challenging, but they become more difficult when combined. With a little bit of practice the process will be fast and easy. Experienced users can easily execute these steps in less than a minute. You’ll get there.

Obtain the source code

We will briefly describe how to obtain the pvlib-python source code using the git/GitHub version control system. We strongly encourage users to learn how to use these powerful tools (see the References!), but we also recognize that they can be a substantial roadblock to getting started with pvlib-python. Therefore, you should know that you can download a zip file of the most recent development version of the source code by clicking on the Download Zip button on the right side of our GitHub page or download a zip file of any stable release from our Releases page.

Follow these steps to obtain the library using git/GitHub:

  1. Download the GitHub Desktop application.
  2. Fork the pvlib-python project by clicking on the “Fork” button on the upper right corner of the pvlib-python GitHub page.
  3. Clone your fork to your computer using the GitHub Desktop application by clicking on the Clone to Desktop button on your fork’s homepage. This button is circled in the image below. Remember the system path that you clone the library to.

Please see GitHub’s Forking Projects, Fork A Repo, and the git-scm for more details.

Set up a virtual environment

We strongly recommend working in a virtual environment if you’re going to use an editable version of the library. You can skip this step if:

  1. You already have Anaconda or another scientific Python distribution
  2. You don’t mind polluting your Python installation with your development version of pvlib.
  3. You don’t want to work with multiple versions of pvlib.

There are many ways to use virtual environments in Python, but Anaconda again provides the easiest solution. These are often referred to as conda environments, but they’re the same for our purposes.

  1. Create a new conda environment for pvlib and pre-install the required packages into the environment: conda create --name pvlibdev python pandas scipy
  2. Activate the new conda environment: source activate pvlibdev
  3. Install additional packages into your development environment: conda install jupyter ipython matplotlib seaborn pytest nose flake8

The conda documentation has more information on how to use conda virtual environments. You can also add -h to most pip and conda commands to get help (e.g. conda -h or conda env -h)

Install the source code

Good news – installing the source code is the easiest part! With your conda/virtual environment still active...

  1. Install pvlib-python in “development mode” by running pip install -e /path/to/your/pvlib-python. You remember this path from the clone step, right? It’s probably something like C:\Users\%USER%\Documents\GitHub\pvlib-python (Windows) or /Users/%USER%/Documents/pvlib-python (Mac).
  2. Test your installation by running python -c 'import pvlib'. You’re good to go if it returns without an exception.

The version of pvlib-python that is on that path is now available as an installed package inside your conda/virtual environment.

Any changes that you make to this pvlib-python will be available inside your environment. If you run a git checkout, branch, or pull command the result will be applied to your pvlib-python installation. This is great for development. Note, however, that you will need to use Python’s reload function (python 2, python 3) if you make changes to pvlib during an interactive Python session (including a Jupyter notebook). Restarting the Python interpreter will also work.

Remember to source activate pvlibdev (or whatever you named your environment) when you start a new shell or terminal.

NREL SPA algorithm

pvlib-python is distributed with several validated, high-precision, and high-performance solar position calculators. We strongly recommend using the built-in solar position calculators.

pvlib-python also includes unsupported wrappers for the official NREL SPA algorithm. NREL’s license does not allow redistribution of the source code, so you must jump through some hoops to use it with pvlib. You will need a C compiler to use this code.

To install the NREL SPA algorithm for use with pvlib:

  1. Download the pvlib repository (as described in Obtain the source code)
  2. Download the SPA files from NREL
  3. Copy the SPA files into pvlib-python/pvlib/spa_c_files
  4. From the pvlib-python directory, run pip uninstall pvlib followed by pip install .


pvlib-python is compatible with Python versions 2.7, 3.4, 3.5 and Pandas versions 0.13.1 or newer.

There have been several problems with Continuum’s Anaconda packages that have impacted pvlib users. The current problems that we’re aware of are listed below:

  1. For Windows + Python 2.7 users: Continuum’s Python 2.7 SciPy 0.16.1, 0.17.0, 0.17.1 packages are not compiled properly and will crash your Python interpreter if you use our Linke turbidity lookup function. See Anaconda issue 650 for more.

Note that our Numba-accelerated solar position algorithms have more specific version requirements that will be resolved by the Numba installer.


Here are a few recommended references for installing Python packages:

Here are a few recommended references for git and GitHub: