Numpy ducky

Numpy ducky (based on Flexbox Froggy) is a story-driven experience designed to teach you the basics of NumPy by helping ducks get into water.

Table of contents:

• How to use
• Specification
• Building and running

How to use

Right after launching the app, you will be greeted with the welcoming menu:
As you can see, the app is divided into 3 crucial sections:

• description - at top-left is to teach and explain new learning techniques related to numpy,
• code task - at bottom-left is to check the actual undertanding of the user,
• visualisation - at the right is to visualise the user's answer and help them understand their query. To visualise, we use dynamic expression resolution, which enables our app to plot the code output.

And here it's how it really works:

• wrong answer, projected on the visualisation:
  
• and sometimes, the query can't be visualised, so the error log is being shown:
  
• and finally the correct answer:
  

And also we support 3D view of the visualisation, which can be moved freely with mouse:

Specification

Python standard

• Python 3.13

Third party libraries:

• pyside6 - https://wiki.qt.io/Qt_for_Python
• pyvista - https://pyvista.org
• numpy - https://numpy.org
• pytest - https://docs.pytest.org/en/stable/
• ruff - https://github.com/astral-sh/ruff

Project scheme:

Building and running

Build/run locally:

git clone https://github.com/0stam/numpy-ducky.git
cd numpy-ducky

# install dependencies
pipenv install

# run without building
pipenv run start

# build
pipenv run build

Run:

After succesful build, navigate to ./dist/ and run numpy_ducky.exe
Congratulations! You heave now succefully run and built the numpy-ducky app 🦆

Testing and linting

To lint using ruff, run:

ruff check --fix

To test the code, run:

pytest

Troubleshoot

If at any point, any error occured, feel free to share in the issues tab.