| Name | Version | Summary | date |
| basilearn |
0.1.223 |
A library for educational content and interactive learning |
2024-12-06 03:12:52 |
| think-lang |
0.1.9 |
Think - A language for learning computational thinking |
2024-12-06 00:22:12 |
| kolibri |
0.17.4 |
Kolibri - the offline app for universal education |
2024-12-05 17:55:17 |
| mocodo |
4.2.12 |
Modélisation Conceptuelle de Données. Nickel. Ni souris. |
2024-11-23 10:54:55 |
| pyflayer |
0.0.0 |
API Python Library for Learning Python Basics using Minecraft and Mineflayer. |
2024-11-15 09:36:33 |
| physiomodeler |
0.5.0 |
Create physiological models for educational purposes. |
2024-11-06 10:13:48 |
| math-assistant-cli |
0.1.1 |
AI-powered math problem solver and tutor |
2024-11-02 15:31:46 |
| eq-quizgen |
0.2.9 |
A tool that can generate multiple types of quizzes from a common configuration. |
2024-10-29 23:24:50 |
| wukongbaobao |
1.0.10 |
Wukongbaobao is a program that helps parents flexibly generate test questions for their children. The tool is written in Python. |
2024-10-17 01:51:08 |
| pelita |
2.5.1 |
Pelita |
2024-10-09 15:18:32 |
| paroxython |
0.7.1 |
Search Python code for algorithmic features |
2024-09-21 21:30:16 |
| edupils |
0.1.27 |
A collection of educational tools for Python |
2024-09-21 18:12:11 |
| pedal |
2.6.4 |
Tools to provide feedback on student code. |
2024-09-20 19:02:02 |
| thonny |
4.1.6 |
Python IDE for beginners |
2024-09-11 00:44:01 |
| allowed |
1.5.1 |
Check if a program only uses a subset of the Python language. |
2024-09-10 11:54:13 |
| quizzable |
1.0.2 |
Education with Python. |
2024-08-27 00:13:21 |
| algoesup |
0.3.1 |
Algorithmic essay support library |
2024-08-17 16:48:42 |
| csedu |
0.1.0 |
A package for computer science education containing modules for image processing and chart creation. |
2024-08-09 08:53:53 |
| supermark |
0.3.29 |
Pandoc-based transformation tool for documents containing different markup languages. |
2024-08-08 12:31:03 |
| edugenome |
0.2.8 |
It consists of three genetic algorithms that are simply implemented with Python code for genetic algorithm training: creating a number sum of 20, creating (4, 4) images, and implementing linear regression. |
2024-08-06 08:40:24 |