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中文

Conda 环境管理脚本 (支持Linux和Windows)

（O(∩_∩)O) 这个脚本可以帮助你管理 Conda 环境，让主要操作更加简单易用，而无需记住繁琐的命令行。它支持以下操作：

管理 Conda 环境

操作 按键 描述
新建环境 [+] 或 [=] 快速创建一个新的环境(支持conda包模版)
删除环境 [-] 轻松删除选定的环境及Jupyter注册
重命名环境 [R] 对选定的环境进行重命名(能转移Jupyter注册与创建的开始菜单项)
复制环境 [P] 简便复制选定的环境
管理环境的历史版本 [V] 查看，或回退到选定环境的历史版本(能自动添加所需要的conda包源以正确回溯)
更新环境的 Conda 包 [U] 更新选定环境中的所有Conda包(能自动添加相应Channel源，并严格源顺序以正确更新包版本；支持固定Conda包版本；支持提示Pip包)
查看及清空缓存 [C] 查看并清空Conda/Pip缓存
检查环境完整性 [H] 使用conda doctor与pip check检查环境完整性，并显示健康情况报告

管理 Jupyter 内核

操作 按键 描述
注册 Jupyter 内核 [I] 将选定环境的Jupyter内核注册到当前用户，以供Jupyter Notebook使用
管理 Jupyter 内核 [J] 显示、管理所有已注册的Jupyter环境，以及清理已弃用或失效的Jupyter内核

其他

操作 [按下] 或 <输入> 描述
激活环境命令行 [序号] 或 <序号> 在当前工作目录(由-d参数指定)下激活对应的Conda环境的命令行，以进行命令操作
浏览环境主目录 <@序号> 打开文件资源管理器浏览指定环境的主目录
(特色) 搜索 Conda 软件包 [S] 搜索指定Python版本下的软件包，迅速找到你想要的包。功能强大，界面简洁，简单易用。
- 概览模式 轻松速览信息汇总(Python最大最小版本，cuda最大支持)，
- 精简/详细模式 (版本、Channel、Python版本、cuda版本、包大小、时间戳等信息)，准确定位想要的包；
1. 在受支持的基环境(mamba 或 conda >=23.10)下调用repoquery search，加快查询速度；
2. 支持版本比较式过滤，查找更加灵活；
3. 支持显示内容匹配终端宽度。

界面展示

主界面 (3种展示模式)

主界面

搜索 Conda 包界面

展开/折叠

搜索-概览

搜索-概览

搜索-精简显示

搜索-精简显示

开始使用

  • 方法一 使用源码文件

    1. 有 Python >= 3.10 的安装；

      在此 Python 环境下安装依赖：

      python scripts/install_requirements.py

    2. 已安装了anaconda3，miniforge3，miniconda3等 conda/mamba 包管理环境；

    3. 下载 conda_env_manager.py, MyTools.py, ColorStr.py 3个文件于同一目录下，运行：

      python conda_env_manager.py

      3.1 命令行使用提示：

      加-h参数以显示帮助；-d参数指定脚本的工作目录；-p参数指明其Conda/Mamba发行版安装位置(环境主目录安装在了非常规位置的情况)

  • 方法二 使用Release页面的二进制程序

English

Conda Envs Management Script (Supports Linux and Windows)

(O(∩_∩)O) This script helps you manage Conda environments, making the main operations easier to use without needing to remember complex command lines. It supports the following operations:

Managing Conda Environments

Operation Key Description
Create Environment [+] or [=] Quickly create a new environment (supports conda package templates)
Delete Environment [-] Easily delete the selected environment and its Jupyter registration
Rename Environment [R] Rename the selected environment (can transfer Jupyter registration and start menu items created)
Duplicate Environment [P] Easily duplicate the selected environment
Manage Environment History [V] View or roll back to a selected environment's previous versions (can automatically add required conda sources for correct rollback)
Update Conda Packages in Environment [U] Update all Conda packages in the selected environment, automatically adding appropriate channel sources in strict order, supporting fixed Conda package versions, and providing prompts for Pip packages
View and Clear Cache [C] View and clear Conda/Pip cache
Check Environment Integrity [H] Use conda doctor and pip check to verify environment integrity and display a health status report

Managing Jupyter Kernels

Operation Key Description
Register Jupyter Kernel [I] Register the Jupyter kernel of the selected environment to the current user for use in Jupyter Notebook
Manage Jupyter Kernels [J] Display and manage all registered Jupyter environments, and clean up deprecated or invalid Jupyter kernels

Others

Operation [Press] or <Enter> Description
Activate Environment Command Line [Number] or <Number> Activate the corresponding Conda environment in the current working directory (specified by the -d parameter) to perform command operations
Browse Environment Home Directory <@Number> Open the file explorer to browse the home directory of the specified environment
(Feature) Search Conda Packages [S] Search for packages for a specific Python version, quickly find the package you want. Powerful, simple interface, easy to use.
- Overview Mode: Quickly summarize information (maximum and minimum Python versions, maximum CUDA support),
- Concise/Detailed Mode: (version, channel, Python version, CUDA version, package size, timestamp, etc.) accurately locate the desired package;
1. Use repoquery search in supported base env (mamba or conda >=23.10) to speed up the query;
2. supports version comparison filtering for more flexible searching;
3. Support content display matching terminal width.

Interface Display

Main Interface (3 Display Modes)

Main

Search Conda Packages Interface

Expand/Collapse

Search - Overview

Search-Overview

Search - Simplified Display

Search-Simplified_Display

Getting Started

  • Method 1: Using the Source Code Files

    1. Python >= 3.10 installation is required.

      Install dependencies in this Python environment by run:

      python scripts/install_requirements.py

    2. Anaconda3, miniforge3, miniconda3, or any conda/mamba package management environment must be installed.

    3. Download the files conda_env_manager.py, MyTools.py, ColorStr.py and english_translator.py, placing them in the same directory.

      Run python scripts/english_translator.py now to translate the script to English.

    4. If translated successfully, then run:

      python conda_env_manager.py

      4.1 Command-line Usage Tips:

      Add the -h parameter to display help; use the -d parameter to specify the working directory of the script; and use the -p parameter to specify the installation location of its Conda/Mamba distribution (in cases where the environment's main directory is installed in an unconventional location).

  • Method 2: Use the binary program from the Release page

致谢 Acknowledgements

感谢 OpenAI ChatGPT 与 Github Copilot 在代码编写、英文翻译上提供的帮助。

Special thanks to OpenAI ChatGPT and GitHub Copilot for their assistance with code writing and English translation.

Would you like to give it a try? 😊 Wishing you a pleasant experience!