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?
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
- Install the full Anaconda Scientific Python distribution available at Continuum.io
See the Anaconda FAQ for more information.
You can now install pvlib-python by one of the methods below.
Install standard release¶
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:
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:
- Download the GitHub Desktop application.
- Fork the pvlib-python project by clicking on the “Fork” button on the upper right corner of the pvlib-python GitHub page.
- 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.
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:
- You already have Anaconda or another scientific Python distribution
- You don’t mind polluting your Python installation with your development version of pvlib.
- 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.
- Create a new conda environment for pvlib and pre-install
the required packages into the environment:
conda create --name pvlibdev python pandas scipy
- Activate the new conda environment:
source activate pvlibdev
- Install additional packages into your development environment:
conda install jupyter ipython matplotlib seaborn 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...
- 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
- 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
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.
source activate pvlibdev (or whatever you named your
environment) when you start a new shell or terminal.
Here are a few recommended references for installing Python packages:
- The Pandas installation page
- python4astronomers Modules, Packages, and all that
- Python Packaging User Guide
- Conda User Guide
Here are a few recommended references for git and GitHub: