When doing machine learning, the Python environment is like a clean bench in a laboratory: if the reagents are mixed or the temperature is incorrect, even the best model will not produce stable results. A project often needs to lock down the Python version, NumPy, PyTorch, CUDA, and dozens of other dependencies. If any one … Read more
Guide to Configuring a Meteorological Python Environment in an Offline Network (Based on Anaconda) This guide is suitable for the Anaconda + VSCode development environment, helping users quickly set up the required Python environment for meteorological data analysis without internet access. 📦 Project Name Configuration of the Meteorological Python Environment (MeteoPy310) Main Purpose: Pre-install commonly … Read more
~~Follow me, let’s grow together~~ The Python environment management tools are undergoing significant changes, evolving from traditional venv/virtualenv to conda and the emerging uv. Each generation of tools addresses the pain points of its predecessors. This article provides a comprehensive comparison and analysis of the two mainstream environment management tools, conda and uv, covering their … Read more
What is conda? It is similar to an app store for mobile phones, where you can download the necessary software. There are three versions: conda, miniconda, and anaconda. Here, we will use miniconda as an example based on our needs. unsetunset1. Downloading and Installing condaunsetunset Link to download the conda mirror: https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/ After selecting the … Read more
In the process of Python development, different projects often depend on different versions of the Python interpreter. If multiple versions are directly installed on the system, it can easily lead to path conflicts and package confusion. At this point, Python version management tools become particularly important. This article will introduce commonly used Python version management … Read more
Python provides various tools for environment and package management, each with its unique advantages and use cases. As a developer, choosing the right tool can significantly optimize the workflow for creating new projects and managing dependencies. In this article, we will compare the most popular tools: Conda, Poetry, uv and virtualenv from the following perspectives: … Read more
Under normal circumstances, I would enter the R interactive environment from the Linux terminal to installR packages: R # Enter R environment BiocManager::install(“ggplot2“) # Run the installation command in R q() # Exit after installation is complete Today, I will share with you the method of directly installing R packages from the Linuxterminal: Method 1: … Read more
Word count: 740, reading time approximately 4 minutes After installing the device system, configure libraries such as CUDA, cuDNN, OpenCV, and TensorRT through JetPack. 1. Install Conda Miniconda download link: <span>https://repo.anaconda.com/miniconda/</span>, choose the appropriate version to download, for example, <span>Miniconda3-py38_23.11.0-2-Linux-aarch64.sh</span> 1. Installation command cd /root wget -q https://repo.anaconda.com/miniconda/Miniconda3-py38_23.5.2-0-Linux-aarch64.sh bash ./Miniconda3-py38_23.11.0-2-Linux-aarch64.sh -b -f -p /root/miniconda3 rm … Read more
I tested that the MKL library’s Python version should ideally be kept at 3.9, and not greater than 3.9, such as 3.10, 3.11, 3.12, or 3.13, as they are currently not very compatible.Therefore, when configuring, it is best to use conda, and thencreate a virtual environment. conda create -n my_env python=3.9 Activate the virtual environment … Read more
For more content, you can join the Linux system knowledge base package (tutorials + videos + Q&A). Table of Contents 1. Download rknn-llm and DeepSeek model 2. Install RKLLM-Toolkit 2.1 Install miniforge3 tool 2.2 Download miniforge3 installation package 2.3 Install miniforge3 3. Create RKLLM-Toolkit Conda environment 3.1 Enter Conda base environment 3.2 Create a Conda … Read more