Sharing your scientific tools: from a script to a desktop application

This repository contains a GUI building and packaging tutorial using the Enthought Tool Suite accepted for the SciPy2022 conference.

Tutorial summary

In this 4h workshop, we will learn to embed scientific tools into a robust scientific application that can scale from a tiny UI to a large platform. As an example, attendees will build an image browser application (including face-detection capabilities), allowing users to search through their pictures, based on various criteria. We will start from a simple python script and progressively turn it into a complete application using Matplotlib and several packages from the Enthought Tool Suite such as Traits, TraitsUI and Pyface. In the process, attendees will learn how to design clean, maintainable and scalable applications, and discuss sharing your tool with your users.

Ultimately, by the end of the workshop, we will have built a fairly sophisticated application that allows users to explore images on their machines and detect faces in them:

Set up instructions

First step to set yourself up is to clone this repository

git clone git@github.com:jonathanrocher/ets_tutorial.git

Requirements

• Python 3.6
• scikits.image
• Pillow
• Pandas
• matplotlib
• traits
• traitsui

EDM users (recommended)

First, download and install EDM from https://www.enthought.com/edm/. Then, open a Terminal/Powershell/Cmd Prompt/ and create a light-weight bootstrap environment to run the installation commands.

edm envs create bootstrap
edm install --environment bootstrap click

Next, enter the following commands to create a dedicated Python environment called ets_tutorial and install all dependencies in it:

edm run -e bootstrap -- python ci build --environment ets_tutorial

All application related python commands are assumed to run in this environment. You can activate the environment with:

edm shell -e ets_tutorial

Conda users

Create a new conda environment called ets_tutorial and install local dependencies with the following commands:

conda create -n ets_tutorial python=3.6 pandas matplotlib traits traitsui scikit-image pillow pyqt ipython importlib_resources importlib_metadata
conda activate ets_tutorial
python setup.py install

Activate the new environment with conda activate ets_tutorial.

pip users

Assuming a Python environment is created and activated on your machine, for example from https://www.python.org/,

pip install pandas matplotlib traits traitsui scikit-image pillow pyqt5 ipython
python setup.py install

Getting help

During the tutorial

During the tutorial, don't hesitate to ask for help:

• ask questions if something isn't clear,
• or just call out for individual support: there will be a number of developers in the room who can help unblock you.

After the tutorial

• This tutorial was recorded and can be watched here
• You can ask questions about any of the ETS packages on the ETS mailing list: https://groups.google.com/g/ets-users .
• Each of the other packages has its own dedicated mailing list where questions can be posted.

Outline of the tutorial

The tutorial will guide you through all the stages from a basic python script (stage 1) to a fully packaged and installable application (stage 8). The included exercises will walk you through developing the primary product of each stage. A solution is available for each exercise, though, to ensure all participants are able to reach the end goal.

• step 1: python script
• step 2: more robust script with ETS-Traits
• step 3: GUI: first traitsUI views
• step 4: First pyface application:
  • Hello world
  • INTERLUDE: code structure for scalability
  • First pycasa: tree navigator to open an image in the central tabbing system.
• step 5: Fuller pyface application:
  • add folder editor to display a table of metadata for all images inside
  • add button to launch the face detection on all images
  • add widgets to filter images
• step 6: pyface application: adding menu and branding
• step 7: Advanced features
  • Using traits_futures to move tasks to the background
• step 8: Packaging and sharing

Contributing

Rules for contributing to the repository

Contributing to this repository requires:

1. to fork the repository, branch off of master, create a branch with changes, and make a Pull Request
2. All code contributed must be flake8 compliant.
3. All unit tests must pass.

Tutorial flow

1. Introduction (20 mins)
   • Review development environment setup
   • Purpose and goals of the tutorial
   • What is ETS? What type of products is it for?
2. Starting script (10 min)
3. Traits (30 mins)

• Introduction to Traits: OOP with traits, trait types, and listening to changes.
• Exercise (10 mins)

4. Basic TraitsUI (35 mins)

• Introduction to TraitsUI views
• The MVC paradigm
• TraitsUI exercise (20 mins)

5. Pyface basics (20 mins)

• Structure and responsibilities, "Hello world" in pyface
• Building first panes
• Task and Pane important attributes and methods
• Pyface exercise: transform hello world into first app (stage 4, 15 mins)

6. More Pyface (15 mins)

• Pyface application folder structure for scalability
• Application important attributes and methods
• Menus, toolbars and branding
• Pyface exercise: building a fuller application (stage 5-6, 20 min)

7. Packaging into 1 click installer (10 m)
8. Wrap up and demo of any advanced UIs? (15 min)