Tips and Tricks
This section introduces some tips and best practices for using CrackNuts, helping you get the most out of CrackNuts.
๐๏ธ PIP Mirror Configuration
After setting up the Python environment, since downloading packages from the pypi repository can be slow over domestic networks, it is recommended to configure pip mirrors. This can speed up downloads and avoid dependency installation failures. You can choose to configure one of the following two mirrors.
๐๏ธ Python Virtual Environment
In general, when developing with Python, it is usually recommended to use a virtual environment such as conda, venv, or virtualenv to avoid breaking the existing Python development environment caused by different projects introducing different versions of the same libraries. Below are examples of configuration methods for conda and venv. You can choose either one to use, but Conda virtual environment is recommended as it better supports compatibility with data analysis and other open-source libraries.
๐๏ธ Nut_stm32f103c8 Side-Channel Analysis
STM32F103C8 is a microcontroller chip based on the ARM Cortex-M3 core, launched by STMicroelectronics. Due to its high performance, low power consumption, and rich peripheral resources, this chip is widely used in embedded systems.
๐๏ธ Nut Development Getting Started - Basics
Step 1. Environment Preparation
๐๏ธ SCARR Installation
SCARR is the default framework used by CrackNuts for data analysis, and it also serves as the default format for trace acquisition (based on a specific directory structure using Zarr). It is recommended to install SCARR when performing data analysis.
๐๏ธ Jupyter Code Autocompletion
By default, after installing Jupyter, code suggestions and autocompletion are not available. You can enable this feature in the Jupyter environment by installing the following plugins:
๐๏ธ Using Jupyter in VS Code
In data analysis, machine learning, and scientific research, Jupyter is a widely used tool. However, sometimes we donโt want to switch to a browser, but rather use Jupyter directly in VS Code. Fortunately, VS Code provides powerful official extensions that allow you to run Notebooks just like in the browser. Moreover, CrackNuts fully supports the Jupyter environment in VS Code.