I’ve received questions lately on the issues that people are having while attempting to build PySide2 on Windows, macOS and Linux. Instead of building PySide2, there’s actually a workaround which works just as well for some people…

Update 2017-08-28: PySide2 can now be installed with conda:

conda config --add channels conda-forge
conda install pyside2

Update 2018-03-09: The Qt Company now offers official and standalone wheels, read more here: 2018-03-09-official-pyside2-wheels.

A formal request to provide official PySide2 wheels

Before we start, make sure to cast a friendly vote here to have The Qt Company (QtC) prioritize the development of official PySide2 wheels.

The alternative to building PySide2 from source; PyQt5 (+ Qt.py)

So you want to use PySide2 but experience issues when building it from source. In case you’re really just interested in using Qt5 indirectly, I might have a solution for you… meaning; you’re really just interested in using PySide or PyQt to access Qt5 functionality.

PySide2 is under the Qt Company umbrella and it would make sense to want to use it (they should know best how to conform to Qt, right?). However, the development of PySide2 seems not yet to be on par with e.g. the PyQt equivalent; PyQt5. Especially not when it comes to just installing it and getting on with life. Hopefully, it will be soon. But in the interim, this blog post could perhaps be of help.

What’s so special about PyQt5 is they’ve created a standalone and portable Python wheel for Python 3. So all it takes to get up running is to be on Python 3 and pip-install PyQt5 and you’re done. No compiling of Qt required and no linking to locally installed Qt libraries; it all comes pre-compiled inside the wheel!

# from a Python 3 installation
pip install PyQt5
python -c "import PyQt5; print(PyQt5)"  # aaaaaah, how refreshing

A note on switching between PyQt5 and PySide2

Eventually, you might want to switch to PySide2 for whatever reason. This is why it could be good to also look into Qt.py. Qt.py offers the possibility to develop regardless of which Qt Python binding you’re using and you can change binding down the road without changing your code.

More on this further down in this blog post…

Manage virtual environments using conda

Instead of using e.g. virtualenv to manage virtual environments, I use conda. Conda can actually manage individual Python distributions and pre-compiled dependencies.

Then I also use the conda distribution of the PyQt5 Python binding, available on conda-forge. Conda-forge is an open source community-led collection of software for the conda package manager.

There are two flavours of conda; Miniconda and Anaconda. I prefer using Miniconda, as then it doesn’t come pre-bundled with a bunch of packages (which the bigger Anaconda distribution has bundled). But regardless of whether you choose Miniconda or Anaconda, they both install the conda command, which is what we need.

So basically, to get set up with a conda environment loaded with PyQt5, you first need to install conda. Here are a couple of examples on how to install Miniconda:

# Windows
choco install miniconda3  # assumes you have chocolatey installed

# macOS
brew cask install miniconda3  # assumes you have homebrew installed

# CentOS 7
curl -O https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh

Then create your virtual environment, loaded with PyQt5:

conda config --add channels conda-forge  # enable conda-forge channel, which contains the PyQt5 distributions
conda create --mkdir -p ~/myCondaEnv python=3.6 pyqt  # change the path into where you want your Python env

Please note the above gives you the most recent PyQt which is 5.6.2-1 as of writing this. You can pin the PyQt version in the conda create command so that the next time you install the environment you get the same PyQt version. You can read up on conda to manage your environment by recording its dependencies down into a specifications file (similar to a requirements.txt file).

Update 2017-07-19: I just noticed you can actually install PyQt5 the same way but using python=2.7, which could be useful to some!

Give it a test run:

~/myCondaEnv/bin/python -c "import PyQt5; print(PyQt5)"

I’d like to point out that you don’t have to deal with the activate/deactivate stuff in order to use your environment. You just need to specify the absolute full path to the python binary.

Writing an application for Maya, Nuke and standalone

So, you want to write an application using PySide/PyQt which needs to run in multiple environments such as in Maya, Nuke and even as a standalone application?

This is when you need to look into the Qt.py project!

Set up two different conda environments:

  • Maya and Nuke: Python 2.7 without any Qt bindings installed
  • Standalone: Python 3.6 with PyQt5 installed

Then you just make sure your application uses the proper environment (site module) depending on whether it is running inside of Maya, Nuke or as a standalone application. Instead of importing PySide, PySide2 or PyQt5 - you import Qt, which will cleverly work out which one of the bindings is available and use that.

I have a couple of articles written up on the subject.

Stuck on Python 2.7?

In case you are stuck on Python 2.7… Ok, first I just want to say you really need to look into moving away from Python 2.7 which is actually referred to as “legacy Python” these days. Even the VFXPlatform is drafting Python 3 for CY2019.

Anyways, if you really must, you can actually quite quickly get up and running with PySide and/or PyQt4 on Python 2.7 using conda too:

conda create --mkdir -p ~/myCondaEnv python=2.7 PySide=1.2.4 pyqt=4.11.4

Ever since Python 3.5, adoption has been soaring and more and more packages are moving away from legacy Python and starts supporting Python 3 only. You’ve been warned. This is why this paragraph didn’t make it until the end of this blog post. :)