Qt for Python Application Boilerplate

This repository contains a boilerplate for Qt for Python (PySide6) based applications.

It's based on my fork of Gerard Marull-Paretas' PySide2 work:

• https://github.com/JackLilhammers/pyside2-boilerplate
• https://github.com/gmarull/pyside2-boilerplate

Features

• Dependency management using pip
• Use the standard setup.py to build resources, docs, etc.
• Manage resources and UI forms using a Qt Creator project
• Generate a compiled application for Windows, Linux and macOS using PyInstaller
• Multilanguage support
• Document using Sphinx
• Flake8 linting

Getting started

First of all create a new virtual environment:

python3 -m venv .venv

Then activate it:

Linux:

source .venv/bin/activate

Windows:

.\.venv\Scripts\activate.ps1

Then install the application in development mode:

pip install -e .

Finally install development dependencies:

pip install -r requirements-dev.txt

Autogenerated files such as translation binaries or compiled forms are required but not pushed to the repository, so the first time you will need to generate them as described in the coming section. Once done, you can run the application like this:

python -m app

Resources and translations

In order to ease the development process, the Qt Creator project app.pro is provided. You can open it to edit the UI files or to manage resources. Translations can be edited using Qt Linguist, that's part of the Qt SDK. In order to build the translations, lrelease-pro and lupdate-pro must be in PATH or their full path must be set in the LRELEASE_QT6_BIN and LUPDATE_QT6_BIN environment variables. UI files, translations and resources can be built like this:

python setup.py build_res

Note that this command is automatically run before running sdist and bdist_app commands.

Compiled application

You can generate a compiled application so that end-users do not need to install anything. You can tweak some settings on the app.spec file. It can be generated like this:

python setup.py bdist_app

Documentation

Sphinx is used for documentation purposes. You can tweak its configuration in docs/conf.py and the documentation can be built like this:

python setup.py build_docs

Linting

Flake8 is a great tool to check for style issues, unused imports and similar stuff. You can tweak .flake8 to ignore certain types of errors, increase the maximum line length, etc. You can run it like this:

flake8 app

Troubleshooting

If PowerShell throws an UnauthorizedAccess error, verify that the execution policy is not Restricted:

Get-ExecutionPolicy
Set-ExecutionPolicy RemoteSigned -Scope CurrentUser