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label: "Project Ideas"
---
### Development `cTensor` library for neural networks
+ Difficulty Level: 3/5 (Medium)
+ Skill: C; Further Mathematics
+ Project Length: Medium
pocketpy is planning to provide a tensor library `cTensor` for users who want to integrate neural networks into their applications. `cTensor` implements automatic differentiation and dynamic compute graph. It allows users to train and deploy neural networks on client-side devices like mobile phones and microcontrollers (e.g. ESP32-C3). We have a early prototype located at [pocketpy/cTensor](https://github.com/pocketpy/cTensor).
In this project, students will help develop and test the `cTensor` library, which is written in C11. We expect students to have a good understanding of further mathematics and C programming.
### Porting LDTK importer for python games
+ Difficulty Level: 2/5 (Easy)
@ -34,3 +24,13 @@ This project aims to develop a full-featured python library for importing LDTK l
Community users have reported that there is no convenient way to debug python applications interpreted by pocketpy. Fortunately, VSCode provides a mechanism of [Debugger Extension](https://code.visualstudio.com/api/extension-guides/debugger-extension) that allows us to integrate pocketpy debugger into VSCode UI through Debug Adapter Protocol (DAP).
This project aims to develop a VSCode plugin like [Python Debugger](https://marketplace.visualstudio.com/items?itemName=ms-python.debugpy), which implements DAP for pocketpy. With this plugin, users can launch their pocketpy applications in VSCode with breakpoints, call stacks, and variable inspection. Students with experience in TypeScript will be helpful for this project.
### Development `cTensor` library for neural networks
+ Difficulty Level: 4/5 (Hard)
+ Skill: C; Further Mathematics
+ Project Length: Medium
pocketpy is planning to provide a tensor library `cTensor` for users who want to integrate neural networks into their applications. `cTensor` implements automatic differentiation and dynamic compute graph. It allows users to train and deploy neural networks on client-side devices like mobile phones and microcontrollers (e.g. ESP32-C3). We have a early prototype located at [pocketpy/cTensor](https://github.com/pocketpy/cTensor).
In this project, students will help develop and test the `cTensor` library, which is written in C11. We expect students to have a good understanding of further mathematics and C programming.