conda发行版比较@python环境管理@conda命令的基本操作@基本使用@conda env list环境条目重复列出问题

文章目录

conda发行版比较@python环境管理@conda命令的基本操作@基本使用@conda env list环境条目重复列出问题

conda发行版比较@python环境管理@conda命令的基本操作@基本使用@conda env list环境条目重复列出问题

ref

conda官网

Conda — conda documentation
- Package, dependency and environment management for any language—Python, R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, Fortran, and more.
- Conda is an open source package management system and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs and updates packages and their dependencies.
- Conda easily creates, saves, loads and switches between environments on your local computer.
- It was created for Python programs, but it can package and distribute software for any language.

conda分类

两种conda发行版本都包含conda的核心功能

miniconda

Miniconda — conda documentation
只包含最核心的conda功能组件,体积小
一般来说足够使用了
Miniconda is a free minimal installer for conda.
- It is a small, bootstrap version of Anaconda
- that includes only conda, Python, the packages they depend on,
- and a small number of other useful packages, including pip, zlib and a few others.
Use the conda install command to install 720+ additional conda packages from the Anaconda repository.

anaconda

Anaconda Documentation — Anaconda documentation
包含了一系列的数据科学分析的组件,体积大
Anaconda Distribution
- Anaconda Distribution is a Python/R data science distribution and a collection of over 7,500+ open-source packages, which includes a package and environment manager.
- Anaconda Distribution is platform-agnostic, so you can use it whether you are on Windows, macOS, or Linux. It’s also is free to install and offers free community support.
- View the Anaconda Distribution documentation.

文档

官方入门使用教程

Getting started with conda — conda 22.11.1 documentation

更新conda版本

conda update conda
- 如果想要查看变化,更新前后分别执行一次conda -V
Cheat sheet — conda documentation

版本比较

版本编号分为python版本和日期
- 例如
  - Miniconda3-py310_22.11.1-1-Windows-x86_64.exe
  - 是python3.10;发布域22年(2022)/11月1日
  - 末尾带有__x64.exe适合于64为系统(通常先择这种的)
  - 镜像中的更新日期可能是稍晚一些(以上只是猜测)

Miniconda 镜像使用帮助

Miniconda 是一个 Anaconda 的轻量级替代，默认只包含了 python 和 conda，但是可以通过 pip 和 conda 来安装所需要的包。
Miniconda 安装包可以到 https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/ 下载。

winget 命令行下载

如果您的网络不错,可以用winget安装

 PS C:\Users\cxxu\AppData\Roaming\Typora\conf> winget search miniconda3
名称       ID                  版本        源
--------------------------------------------------
Miniconda3 Anaconda.Miniconda3 py39_4.10.3 winget

如果搜索到的版本符合你的需求(通常是比较新的)

 PS C:\Users\cxxu\AppData\Roaming\Typora\conf> winget install miniconda3
已找到 Miniconda3 [Anaconda.Miniconda3] 版本 py39_4.10.3
此应用程序由其所有者授权给你。
Microsoft 对第三方程序包概不负责，也不向第三方程序包授予任何许可证。
Downloading https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Windows-x86_64.exe
  ██████████████████████████████  58.1 MB / 58.1 MB
已成功验证安装程序哈希
正在启动程序包安装...
已成功安装

需要注意的是,GUI安装包安装的方式中途可以点击一些安装选项,比如环境变量等
命令行则是全部安装默认的方式安装,而且往往不是最新的
如果下载很慢的话,还是用镜像来吧

环境变量变化

GUI方式查看比较机械简单

命令行方式:(by powershell)

关闭所有终端

 PS D:\repos\scripts> envInPath|sls conda
 
C:\Users\cxxu\miniconda3
C:\Users\cxxu\miniconda3\Library\mingw-w64\bin
C:\Users\cxxu\miniconda3\Library\usr\bin
C:\Users\cxxu\miniconda3\Library\bin
C:\Users\cxxu\miniconda3\Scripts

 function envInPath
{
    <# 
    .synopsis
    check if a value is contain in the Path variable value.
     #>
    param (
        $pattern = '*'
    )
 
    Write-Output '😎😎😎within Path:'
    if ($pattern -eq '*')
    {
        $env:path -split ';'
        return
    }
    $env:path -split ';' | Select-String -Pattern $pattern
}

配置软件国内源

执行脚本powershell脚本:

 conda config --set show_channel_urls yes
Get-Content $home/.condarc
 
'channels:
  - defaults
show_channel_urls: true
default_channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
  conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud'>$home/.condarc
 
Get-Content $home/.condarc
conda clean -i

执行效果:

 PS C:\Users\cxxu>  conda config --set show_channel_urls yes
PS C:\Users\cxxu> cat .\.condarc
channels:
  - defaults
show_channel_urls: true
PS C:\Users\cxxu> "channels:
>>   - defaults
>> show_channel_urls: true
>> default_channels:
>>   - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
>>   - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
>>   - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
>> custom_channels:
>>   conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
>>   msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
>>   bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
>>   menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
>>   pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
>>   pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
>>   simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud">$home\.condarc

基本命令

文档

 PS C:\Users\cxxu> conda -h
usage: conda-script.py [-h] [-V] command ...
 
conda is a tool for managing and deploying applications, environments and packages.
 
Options:
 
positional arguments:
  command
    clean        Remove unused packages and caches.
    compare      Compare packages between conda environments.
    config       Modify configuration values in .condarc. This is modeled after the git config command. Writes to the user .condarc file (C:\Users\cxxu\.condarc) by default.
    create       Create a new conda environment from a list of specified packages.
    help         Displays a list of available conda commands and their help strings.
    info         Display information about current conda install.
    init         Initialize conda for shell interaction. [Experimental]
....

环境信息检查

Display information about current conda install.
查看二级命令用法帮助

 PS C:\Users\cxxu> conda info -h
usage: conda-script.py info [-h] [--json] [-v] [-q] [-a] [--base] [-e] [-s] [--unsafe-channels]
 
Display information about current conda install.
 
Options:
 
optional arguments:
  -h, --help         Show this help message and exit.
  -a, --all          Show all information.
  --base             Display base environment path.
  -e, --envs         List all known conda environments.
  -s, --system       List environment variables.
  --unsafe-channels  Display list of channels with tokens exposed.
 
Output, Prompt, and Flow Control Options:
  --json             Report all output as json. Suitable for using conda programmatically.
  -v, --verbose      Use once for info, twice for debug, three times for trace.
  -q, --quiet        Do not display progress bar.

 PS C:\Users\cxxu> conda info -e
# conda environments:
#
base                  *  C:\Users\cxxu\miniconda3

列举已安装的包

 PS C:\Users\cxxu> conda list
# packages in environment at C:\Users\cxxu\miniconda3:
#
# Name                    Version                   Build  Channel
brotlipy                  0.7.0           py39h2bbff1b_1003    https://repo.anaconda.com/pkgs/main
ca-certificates           2021.7.5             haa95532_1    https://repo.anaconda.com/pkgs/main
certifi                   2021.5.30        py39haa95532_0    https://repo.anaconda.com/pkgs/main
cffi                      1.14.6           py39h2bbff1b_0    https://repo.anaconda.com/pkgs/main
chardet                   4.0.0           py39haa95532_1003    https://repo.anaconda.com/pkgs/main
....

创建新环境🎈conda create

synopsis

 (base) PS D:\repos\blogs> conda create -h
usage: conda-script.py create [-h] [--clone ENV] (-n ENVIRONMENT | -p PATH) [-c CHANNEL] [--use-local] [--override-channels] [--repodata-fn REPODATA_FNS] [--strict-channel-priority]
                              [--no-channel-priority] [--no-deps | --only-deps] [--no-pin] [--copy] [--no-shortcuts] [-C] [-k] [--offline] [-d] [--json] [-q] [-v] [-y] [--download-only]
                              [--show-channel-urls] [--file FILE] [--no-default-packages] [--solver {classic} | --experimental-solver {classic}] [--dev]
                              [package_spec ...]
 
Create a new conda environment from a list of specified packages. To use the newly-created environment, use 'conda activate envname'. This command requires either the -n NAME or -p PREFIXoption.
 
Options:
 
positional arguments:
  package_spec          List of packages to install or update in the conda environment.
 
optional arguments:
  -h, --help            Show this help message and exit.
  --clone ENV           Create a new environment as a copy of an existing local environment.
  --file FILE           Read package versions from the given file. Repeated file specifications can be passed (e.g. --file=file1 --file=file2).
  --dev                 Use `sys.executable -m conda` in wrapper scripts instead of CONDA_EXE. This is mainly for use during tests where we test new conda sources against old Python
                        versions.

Create a new conda environment from a list of specified packages. To use the newly-created environment, use ‘conda activate envname’.

This command requires either the -n NAME or -p PREFIX option.🎈

 Target Environment Specification:
  -n ENVIRONMENT, --name ENVIRONMENT
                        Name of environment.
  -p PATH, --prefix PATH
                        Full path to environment location (i.e. prefix).

创建名为test,采用python3.8的python版本

 conda create -n test python=3.8
Collecting package metadata (current_repodata.json): done
Solving environment: done
 
## Package Plan ##
 
  environment location: C:\Users\cxxu\miniconda3\envs\test
 
  added / updated specs:
    - python=3.8
 
 
The following packages will be downloaded:
 
    package                    |            build
    ---------------------------|-----------------
    certifi-2022.12.7          |   py38haa95532_0         148 KB  defaults
    libffi-3.4.2               |       hd77b12b_6         109 KB  defaults
    pip-22.3.1                 |   py38haa95532_0         2.7 MB  defaults
    python-3.8.15              |       h6244533_2        18.9 MB  defaults
    setuptools-65.5.0          |   py38haa95532_0         1.1 MB  defaults
    wincertstore-0.2           |   py38haa95532_2          15 KB  defaults
    ------------------------------------------------------------
                                           Total:        23.0 MB
 
The following NEW packages will be INSTALLED:
 
  ca-certificates    anaconda/pkgs/main/win-64::ca-certificates-2022.10.11-haa95532_0
  certifi            anaconda/pkgs/main/win-64::certifi-2022.12.7-py38haa95532_0
...untime-14.27.29016-h5e58377_2
  wheel              anaconda/pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_0
  wincertstore       anaconda/pkgs/main/win-64::wincertstore-0.2-py38haa95532_2
 
 
Proceed ([y]/n)?

指定环境的存放目录

通常情况下,推荐使用默认目录创建环境
- 这可以省去很多麻烦
使用-p选项指定
- 注意和-n选项不可以共用

 PS D:\repos>  conda create  python=3.10 -p D:\condaPythonEnvs\pytorch
Collecting package metadata (current_repodata.json): done
Solving environment: done
 
## Package Plan ##
 
  environment location: D:\condaPythonEnvs\pytorch
 
  added / updated specs:
    - python=3.10
 
 
The following NEW packages will be INSTALLED:
 
  bzip2              anaconda/pkgs/main/win-64::bzip2-1.0.8-he774522_0

如果指定位置不在conda默认目录(比如miniconda3:$home\miniconda3\envs\)
- 启动外部位置的环境时,要指定完整目录
  - 这时候用conda info -e检查发现,有一个缺少简短名字的环境,需要用完整路径启动
- 或者配置外部目录的所在位置环境变量,以便conda能够直接找到指定位置环境变量

conda环境变量

virtualenv - how to specify new environment location for conda create - Stack Overflow
Using the .condarc conda configuration file — conda 22.11.1.post17+e3a05b6f5 documentation
- 注意,这envs_dirs和缓存包pkgs_dirs不同
编辑配置文件,设定envs_dirs

 envs_dirs:
  - d:\condaPythonEnvs
channels:
  - defaults
show_channel_urls: true
default_channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
........

主要是指定envs_dirs的值,这里将其设置到d盘的目录d:\condaPythonEnvs

检查配置效果

借助命令 conda create -n test_new_env_default,来试探配置是否成功

 PS C:\Users\cxxu> conda create -n test_new_env_default
Collecting package metadata (current_repodata.json): done
Solving environment: done
 
## Package Plan ##
 
  environment location: d:\condaPythonEnvs\test_new_env_default
 
 
 
Proceed ([y]/n)?n
CondaSystemExit: Exiting.

可以发现,现在不指定前缀的时候,默认的环境存放目录被设定为d:\condaPythonEnvs

如果你在配置文件的envs_dirs配置了多个值(目录字符串),且通过-p指定的目录(前缀)在envs_dirs中,那么可以被conda activate 直接以环境名称激活,而不需要输入完整的环境所在目录!
- ```
 envs_dirs:
  - C:\users\cxxu\miniconda3\envs
  - d:\condaPythonEnvs
```
  - 通常我们只需要配置一个(在默认位置创建环境就不需要指定目录),或者不配置(保持默认即可)

默认环境存放目录

事实上,存放环境的默认目录是不需要配置的,conda会自动扫描默认目录

上面我将默认envs_dirs目录( C:\users\cxxu\miniconda3\envs)显式再配置进去,所以当再次扫描已创建的环境的时候,会出现该目录下的环境变量被重复列出了

默认目录包括conda的根目录以及conda根目录下的envs目录

这两个目录即使没有配置,conda info -e也会扫描他们
然后开始扫描envs_dirs里的环境
该命令目前没有智能合并,仅仅机械地逐个扫描目录

 PS C:\Users\cxxu\Desktop> conda info --env
# conda environments:
#
base                     C:\Users\cxxu\miniconda3
py310                    C:\Users\cxxu\miniconda3\envs\py310
py310                    C:\users\cxxu\miniconda3\envs\py310
pytorch_ser              d:\condaPythonEnvs\pytorch_ser

 PS C:\Users\cxxu\Desktop> conda create -p $condaPythonEnvs\test_multiple_env_dir_value
Collecting package metadata (current_repodata.json): done
Solving environment: done
 
## Package Plan ##
 
  environment location: d:\condaPythonEnvs\test_multiple_env_dir_value
 
 
 
Proceed ([y]/n)? y
 
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
#     $ conda activate d:\condaPythonEnvs\test_multiple_env_dir_value
#
# To deactivate an active environment, use
#
#     $ conda deactivate
 
PS C:\Users\cxxu\Desktop> conda info --env
# conda environments:
#
base                     C:\Users\cxxu\miniconda3
py310                    C:\Users\cxxu\miniconda3\envs\py310
py310                    C:\users\cxxu\miniconda3\envs\py310
pytorch_ser              d:\condaPythonEnvs\pytorch_ser
test_multiple_env_dir_value     d:\condaPythonEnvs\test_multiple_env_dir_value
 
PS C:\Users\cxxu\Desktop> conda activate test_multiple_env_dir_value
(d:\condaPythonEnvs\test_multiple_env_dir_value) PS C:\Users\cxxu\Desktop>

conda env list条目重复问题👌

通常情况下,如果.condarc配置文件中的环境变量没有显式地将默认目录配置进去,那么不会出现条目重复的情况

如果将默认目录(例如我的是 C:\users\cxxu\miniconda3\envs),那么手动删除它,只保留非默认目录
因为conda会自动扫描默认目录

conda config --show-sources检查配置文件

 PS C:\Users\cxxu\.conda> conda config --show-sources
==> C:\Users\cxxu\.condarc <==
auto_activate_base: False
envs_dirs:
  - d:\condaPythonEnvs
pkgs_dirs:
  - d:\conda3\pkgs
  - C:\Users\cxxu\AppData\Local\conda\c
  ...

但是有些意外情况,依然会导致条目重复

重复情况

 PS D:\repos\blogs\python> conda info -e
# conda environments:
#
CCSER_Client             C:\Users\cxxu\.conda\envs\CCSER_Client
base                     C:\Users\cxxu\miniconda3
pyside6                  D:\condaPythonEnvs\pyside6
pytorch_CCSER            D:\condaPythonEnvs\pytorch_CCSER🎈
d2l                      d:\condaPythonEnvs\d2l
paddle2.4                d:\condaPythonEnvs\paddle2.4
pt2.0                    d:\condaPythonEnvs\pt2.0
pyside6                  d:\condaPythonEnvs\pyside6
pytorch_CCSER            d:\condaPythonEnvs\pytorch_CCSER🎈
ser_keras2_2             d:\condaPythonEnvs\ser_keras2_2
ser_pytorch0_10_0        d:\condaPythonEnvs\ser_pytorch0_10_0
test_new                 d:\condaPythonEnvs\test_new
tf2.10                   d:\condaPythonEnvs\tf2.10
tf2.11                   d:\condaPythonEnvs\tf2.11
tf2.5                    d:\condaPythonEnvs\tf2.5
tf2.8                    d:\condaPythonEnvs\tf2.8
tf210                    d:\condaPythonEnvs\tf210
 
PS C:\Users\cxxu\.conda> cat .\environments.txt
C:\Users\cxxu\miniconda3
d:\condaPythonEnvs\pytorch_CCSER🎈
d:\condaPythonEnvs\pyside6
C:\Users\cxxu\.conda\envs\CCSER_Client
d:\condaPythonEnvs\ser_pytorch0_10_0
d:\condaPythonEnvs\ser_keras2_2
D:\condaPythonEnvs\pytorch_CCSER🎈
d:\condaPythonEnvs\test_new
D:\condaPythonEnvs\pyside6	
d:\condaPythonEnvs\paddle2.4
d:\condaPythonEnvs\tf2.8
d:\condaPythonEnvs\tf2.5
d:\condaPythonEnvs\d2l
d:\condaPythonEnvs\pt2.0
d:\condaPythonEnvs\tf2.10
d:\condaPythonEnvs\tf2.11
d:\condaPythonEnvs\tf210

检查environments.txt
在powershell中输入
```
 cat $home/.conda/environments.txt
```
- 如果发现列出的内容有重复条目,那么请手动去除该文件中的重复的条目
- 然后重新运行conda env list检查

检查新环境

例如,我除了自带的base环境,还额外创建了py310这个环境
- conda info --envs检查现有环境

 🚀  conda info -e
# conda environments:
#
base                     C:\Users\cxxu\miniconda3
py310                    C:\Users\cxxu\miniconda3\envs\py310

移除(删除)已创建环境

“conda env list” command shows environments in triplicate · Issue #11277 · conda/conda (github.com)

 PS C:\Users\cxxu\Desktop> conda env -h
usage: conda-env-script.py [-h] {create,export,list,remove,update,config} ...
 
positional arguments:
  {create,export,list,remove,update,config}
    create              Create an environment based on an environment definition file. If
                        using an environment.yml file (the default), you can name the
                        environment in the first line of the file with 'name: envname' or
                        you can specify the environment name in the CLI command using the
                        -n/--name argument. The name specified in the CLI will override
                        the name specified in the environment.yml file. Unless you are in
                        the directory containing the environment definition file, use -f
                        to specify the file path of the environment definition file you
                        want to use.
    export              Export a given environment
    list                List the Conda environments
    remove              Remove an environment
    update              Update the current environment based on environment file
    config              Configure a conda environment
 
optional arguments:
  -h, --help            Show this help message and exit.
 
conda commands available from other packages (legacy):
  env

 PS C:\Users\cxxu> conda env remove -h
usage: conda-env-script.py remove [-h] [-n ENVIRONMENT | -p PATH] [--solver {classic} | --experimental-solver {classic}] [-d] [--json] [-q] [-v] [-y]
 
Remove an environmentRemoves a provided environment.  You must deactivate the existing
environment before you can remove it.
 
Options:
 
optional arguments:
  -h, --help            Show this help message and exit.
  --solver {classic}    Choose which solver backend to use.
  --experimental-solver {classic}
                        DEPRECATED. Please use '--solver' instead.
 
Target Environment Specification:
  -n ENVIRONMENT, --name ENVIRONMENT
                        Name of environment.
  -p PATH, --prefix PATH
                        Full path to environment location (i.e. prefix).
 
Output, Prompt, and Flow Control Options:
  -d, --dry-run         Only display what would have been done.
  --json                Report all output as json. Suitable for using conda programmatically.
  -q, --quiet           Do not display progress bar.
  -v, --verbose         Can be used multiple times. Once for INFO, twice for DEBUG, three times for TRACE.
  -y, --yes             Sets any confirmation values to 'yes' automatically. Users will not be asked to confirm any adding, deleting, backups, etc.
 
Examples:
 
    conda env remove --name FOO
    conda env remove -n FOO

实操:移除环境

 #查看当前有的环境(共有5个)
PS C:\Users\cxxu\Desktop> conda info --env
# conda environments:
#
base                     C:\Users\cxxu\miniconda3
py310                    C:\Users\cxxu\miniconda3\envs\py310
py310                    C:\users\cxxu\miniconda3\envs\py310
pytorch_ser              d:\condaPythonEnvs\pytorch_ser
test_multiple_env_dir_value     d:\condaPythonEnvs\test_multiple_env_dir_value
 
#开始移除
PS C:\Users\cxxu> conda env remove -n test_multiple_env_dir_value
 
Remove all packages in environment d:\condaPythonEnvs\test_multiple_env_dir_value:
#检查移除后的列表
PS C:\Users\cxxu> conda info --env
# conda environments:
#
base                     C:\Users\cxxu\miniconda3
py310                    C:\Users\cxxu\miniconda3\envs\py310
pytorch_ser              d:\condaPythonEnvs\pytorch_ser

重命名环境

假设我想要把py310重命名为pytorch_CCSER
- conda rename -n py310 pytorch_CCSER
- 可以通过追加-d选项来查看命令的执行细节:(optional)
  - 先克隆就环境,以新名称作为克隆后的环境
  - 删除旧环境

 (base) PS D:\repos\CCSER> conda rename  -n py310 pytorch_CCSER  -d
Dry run action: clone C:\Users\cxxu\miniconda3\envs\py310,d:\condaPythonEnvs\pytorch_CCSER
Dry run action: rm_rf C:\Users\cxxu\miniconda3\envs\py310
(base) PS D:\repos\CCSER> conda rename  -n py310 pytorch_CCSER
Source:      C:\Users\cxxu\miniconda3\envs\py310
Destination: d:\condaPythonEnvs\pytorch_CCSER
Packages: 131
Files: 539
 
Downloading and Extracting Packages
 
 
Downloading and Extracting Packages
 
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(base) PS D:\repos\CCSER> conda info --env
# conda environments:
#
base                  *  C:\Users\cxxu\miniconda3
pytorch_CCSER            d:\condaPythonEnvs\pytorch_CCSER

指定参数不可用@版本过高

例如,指定了当前channel找不到的python版本,会失败

 🚀  conda create -n test python=3.11
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed
 
PackagesNotFoundError: The following packages are not available from current channels:
 
  - python=3.11
 
Current channels:
 
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/win-64
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r/win-64
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r/noarch
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2/win-64
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2/noarch
 
To search for alternate channels that may provide the conda package you're
looking for, navigate to
 
    https://anaconda.org
 
and use the search bar at the top of the page.

获取@更新可用的python版本

Managing Python — conda 22.11.1.post17+e3a05b6f5 documentation
通常conda可用的python版本会落后最新的python版本0或1个版本

用conda启动(激活)指定python环境@conda activate🎈

powershell方式启动

在windows下,您需要注意shell的不同(比如,conda activate能否执行成功)
- 使用专门为powershell配置的命令启动,否则无法生效
- 默认的是为cmd的启动命令
anaconda - How to activate conda environment from powershell? - Stack Overflow
当您从开始菜单中启动Anaconda Powershell Prompt (miniconda3)
- 或者直接在powershell中执行以下代码启动:
- .(Resolve-Path "$env:appdata\Microsoft\Windows\Start*Menu\Programs\Anaconda3*\*conda*powershell*.lnk")
粘贴以下代码回车执行
- ```
 conda init powershell
conda config --set auto_activate_base false
 
 
```
- 关闭终端,此后再打开powershell,就可以直接使用conda activate相关命令了

例

 (py310) PS D:\repos\PythonLearn> conda info --env
# conda environments:
#
base                     C:\Users\cxxu\miniconda3
py310                 *  C:\Users\cxxu\miniconda3\envs\py310

如果您使用powershell,但是没有执行上述配置代码,会导致powershell执行conda activate环境无法激活
- 且conda list -e看不到当前已激活的环境*

conda install

执行conda install -h查看文档

 Installs a list of packages into a specified conda environment.
 
    This command accepts a list of package specifications (e.g, bitarray=0.8)
    and installs a set of packages consistent with those specifications and
    compatible with the underlying environment. If full compatibility cannot
    be assured, an error is reported and the environment is not changed.
 
    Conda attempts to install the newest versions of the requested packages. To
    accomplish this, it may update some packages that are already installed, or
    install additional packages. To prevent existing packages from updating,
    use the --freeze-installed option. This may force conda to install older
    versions of the requested packages, and it does not prevent additional
    dependency packages from being installed.
 
    If you wish to skip dependency checking altogether, use the '--no-deps'
    option. This may result in an environment with incompatible packages, so
    this option must be used with great caution.
 
    conda can also be called with a list of explicit conda package filenames
    (e.g. ./lxml-3.2.0-py27_0.tar.bz2). Using conda in this mode implies the
    --no-deps option, and should likewise be used with great caution. Explicit
    filenames and package specifications cannot be mixed in a single command.

examples

 Examples:
 
Install the package 'scipy' into the currently-active environment::
 
    conda install scipy
 
Install a list of packages into an environment, myenv::
 
    conda install -n myenv scipy curl wheel
 
Install a specific version of 'python' into an environment, myenv::
 
    conda install -p path/to/myenv python=3.7.13

conda remove

执行conda remove -h查看文档

 Remove a list of packages from a specified conda environment.
 
This command will also remove any package that depends on any of the
specified packages as well---unless a replacement can be found without
that dependency. If you wish to skip this dependency checking and remove
just the requested packages, add the '--force' option. Note however that
this may result in a broken environment, so use this with caution.

examples

 Examples:
 
Remove the package 'scipy' from the currently-active environment::
 
    conda remove scipy
 
Remove a list of packages from an environemnt 'myenv'::
 
    conda remove -n myenv scipy curl wheel

配置conda🎈

Configuration — conda 22.11.1.post17+e3a05b6f5 documentation

 PS C:\Users\cxxu> conda config -h
usage: conda-script.py config [-h] [--json] [-v] [-q] [--system | --env | --file FILE]
                              [--show [SHOW ...] | --show-sources | --validate |
                              --describe [DESCRIBE ...] | --write-default]
                              [--get [KEY ...] | --append KEY VALUE | --prepend KEY VALUE
                              | --set KEY VALUE | --remove KEY VALUE | --remove-key KEY |
                              --stdin]
 
Modify configuration values in .condarc.  This is modeled after the git
config command.  Writes to the user .condarc file (C:\Users\cxxu\.condarc) by default. Use the
--show-sources flag to display all identified configuration locations on
your computer.
 
Options:
 
optional arguments:
  -h, --help            Show this help message and exit.
 
Output, Prompt, and Flow Control Options:
  --json                Report all output as json. Suitable for using conda
                        programmatically.
  -v, --verbose         Use once for info, twice for debug, three times for trace.
  -q, --quiet           Do not display progress bar.
 
Config File Location Selection:
  Without one of these flags, the user config file at 'C:\Users\cxxu\.condarc' is used.
 
  --system              Write to the system .condarc file at
                        'C:\Users\cxxu\miniconda3\.condarc'.
  --env                 Write to the active conda environment .condarc file (<no active
                        environment>). If no environment is active, write to the user
                        config file (C:\Users\cxxu\.condarc).
  --file FILE           Write to the given file.
  ...........

python编码工具@vscode

vscode在多个版本的python间切换

如果只是您临时需要切换版本,那么可以考虑使用终端命令行(指定python版本)来运行(这或许还稍微麻烦)
例如,临时选用python3.10版本进行代码测试
还可以配置快捷键
- 如果您还是code runner 插件的用户,则可以考虑将比较常用其中的一个版本,配置到code runner的快捷键中(可以自定义代码运行在终端的命令映射内容,对各种语言的文件均用同一个快捷键运行)

jupyter

安装python插件
安装jupyter插件
选择python解释器

如果您使用conda管理python环境

如果遇到vscode中安装jupyter依赖报错,尝试

可能会在创建到一般的jupyter notebook提示:

 Running cells with 'py310' requires ipykernel package.
Run the following command to install 'ipykernel' into the Python environment. 
Command: 'conda install -n py310 ipykernel --update-deps --force-reinstall'

根据无法顺利完成时,可能是由于相关依赖版本不匹配
执行错误提示的命令,手动执行安装
```
 conda install -n py310 ipykernel --update-deps --force-reinstall
```
- 这里py310是我的conda python环境,根据自己的情况修改

posted @ 2022-12-31 23:59 xuchaoxin1375 阅读(21) 评论(0) 编辑收藏举报来源

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	PS C:\Users\cxxu\AppData\Roaming\Typora\conf> winget search miniconda3
	名称 ID 版本源
	--------------------------------------------------
	Miniconda3 Anaconda.Miniconda3 py39_4.10.3 winget

	PS C:\Users\cxxu\AppData\Roaming\Typora\conf> winget install miniconda3
	已找到 Miniconda3 [Anaconda.Miniconda3] 版本 py39_4.10.3
	此应用程序由其所有者授权给你。
	Microsoft 对第三方程序包概不负责，也不向第三方程序包授予任何许可证。
	Downloading https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Windows-x86_64.exe
	██████████████████████████████ 58.1 MB / 58.1 MB
	已成功验证安装程序哈希
	正在启动程序包安装...
	已成功安装

	PS D:\repos\scripts> envInPath\|sls conda

	C:\Users\cxxu\miniconda3
	C:\Users\cxxu\miniconda3\Library\mingw-w64\bin
	C:\Users\cxxu\miniconda3\Library\usr\bin
	C:\Users\cxxu\miniconda3\Library\bin
	C:\Users\cxxu\miniconda3\Scripts

	function envInPath
	{
	<#
	.synopsis
	check if a value is contain in the Path variable value.
	#>
	param (
	$pattern = '*'
	)

	Write-Output '😎😎😎within Path:'
	if ($pattern -eq '*')
	{
	$env:path -split ';'
	return
	}
	$env:path -split ';' \| Select-String -Pattern $pattern
	}

	conda config --set show_channel_urls yes
	Get-Content $home/.condarc

	'channels:
	- defaults
	show_channel_urls: true
	default_channels:
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
	custom_channels:
	conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud'>$home/.condarc

	Get-Content $home/.condarc
	conda clean -i

	PS C:\Users\cxxu> conda config --set show_channel_urls yes
	PS C:\Users\cxxu> cat .\.condarc
	channels:
	- defaults
	show_channel_urls: true
	PS C:\Users\cxxu> "channels:
	>> - defaults
	>> show_channel_urls: true
	>> default_channels:
	>> - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
	>> - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
	>> - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
	>> custom_channels:
	>> conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	>> msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	>> bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	>> menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	>> pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	>> pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
	>> simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud">$home\.condarc

	PS C:\Users\cxxu> conda -h
	usage: conda-script.py [-h] [-V] command ...

	conda is a tool for managing and deploying applications, environments and packages.

	Options:

	positional arguments:
	command
	clean Remove unused packages and caches.
	compare Compare packages between conda environments.
	config Modify configuration values in .condarc. This is modeled after the git config command. Writes to the user .condarc file (C:\Users\cxxu\.condarc) by default.
	create Create a new conda environment from a list of specified packages.
	help Displays a list of available conda commands and their help strings.
	info Display information about current conda install.
	init Initialize conda for shell interaction. [Experimental]
	....

	PS C:\Users\cxxu> conda info -h
	usage: conda-script.py info [-h] [--json] [-v] [-q] [-a] [--base] [-e] [-s] [--unsafe-channels]

	Display information about current conda install.

	Options:

	optional arguments:
	-h, --help Show this help message and exit.
	-a, --all Show all information.
	--base Display base environment path.
	-e, --envs List all known conda environments.
	-s, --system List environment variables.
	--unsafe-channels Display list of channels with tokens exposed.

	Output, Prompt, and Flow Control Options:
	--json Report all output as json. Suitable for using conda programmatically.
	-v, --verbose Use once for info, twice for debug, three times for trace.
	-q, --quiet Do not display progress bar.

	PS C:\Users\cxxu> conda info -e
	# conda environments:
	#
	base * C:\Users\cxxu\miniconda3

	PS C:\Users\cxxu> conda list
	# packages in environment at C:\Users\cxxu\miniconda3:
	#
	# Name Version Build Channel
	brotlipy 0.7.0 py39h2bbff1b_1003 https://repo.anaconda.com/pkgs/main
	ca-certificates 2021.7.5 haa95532_1 https://repo.anaconda.com/pkgs/main
	certifi 2021.5.30 py39haa95532_0 https://repo.anaconda.com/pkgs/main
	cffi 1.14.6 py39h2bbff1b_0 https://repo.anaconda.com/pkgs/main
	chardet 4.0.0 py39haa95532_1003 https://repo.anaconda.com/pkgs/main
	....

	(base) PS D:\repos\blogs> conda create -h
	usage: conda-script.py create [-h] [--clone ENV] (-n ENVIRONMENT \| -p PATH) [-c CHANNEL] [--use-local] [--override-channels] [--repodata-fn REPODATA_FNS] [--strict-channel-priority]
	[--no-channel-priority] [--no-deps \| --only-deps] [--no-pin] [--copy] [--no-shortcuts] [-C] [-k] [--offline] [-d] [--json] [-q] [-v] [-y] [--download-only]
	[--show-channel-urls] [--file FILE] [--no-default-packages] [--solver {classic} \| --experimental-solver {classic}] [--dev]
	[package_spec ...]

	Create a new conda environment from a list of specified packages. To use the newly-created environment, use 'conda activate envname'. This command requires either the -n NAME or -p PREFIXoption.

	Options:

	positional arguments:
	package_spec List of packages to install or update in the conda environment.

	optional arguments:
	-h, --help Show this help message and exit.
	--clone ENV Create a new environment as a copy of an existing local environment.
	--file FILE Read package versions from the given file. Repeated file specifications can be passed (e.g. --file=file1 --file=file2).
	--dev Use `sys.executable -m conda` in wrapper scripts instead of CONDA_EXE. This is mainly for use during tests where we test new conda sources against old Python
	versions.

	Target Environment Specification:
	-n ENVIRONMENT, --name ENVIRONMENT
	Name of environment.
	-p PATH, --prefix PATH
	Full path to environment location (i.e. prefix).

	conda create -n test python=3.8
	Collecting package metadata (current_repodata.json): done
	Solving environment: done

	## Package Plan ##

	environment location: C:\Users\cxxu\miniconda3\envs\test

	added / updated specs:
	- python=3.8


	The following packages will be downloaded:

	package \| build
	---------------------------\|-----------------
	certifi-2022.12.7 \| py38haa95532_0 148 KB defaults
	libffi-3.4.2 \| hd77b12b_6 109 KB defaults
	pip-22.3.1 \| py38haa95532_0 2.7 MB defaults
	python-3.8.15 \| h6244533_2 18.9 MB defaults
	setuptools-65.5.0 \| py38haa95532_0 1.1 MB defaults
	wincertstore-0.2 \| py38haa95532_2 15 KB defaults
	------------------------------------------------------------
	Total: 23.0 MB

	The following NEW packages will be INSTALLED:

	ca-certificates anaconda/pkgs/main/win-64::ca-certificates-2022.10.11-haa95532_0
	certifi anaconda/pkgs/main/win-64::certifi-2022.12.7-py38haa95532_0
	...untime-14.27.29016-h5e58377_2
	wheel anaconda/pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_0
	wincertstore anaconda/pkgs/main/win-64::wincertstore-0.2-py38haa95532_2


	Proceed ([y]/n)?

	PS D:\repos> conda create python=3.10 -p D:\condaPythonEnvs\pytorch
	Collecting package metadata (current_repodata.json): done
	Solving environment: done

	## Package Plan ##

	environment location: D:\condaPythonEnvs\pytorch

	added / updated specs:
	- python=3.10


	The following NEW packages will be INSTALLED:

	bzip2 anaconda/pkgs/main/win-64::bzip2-1.0.8-he774522_0

	envs_dirs:
	- d:\condaPythonEnvs
	channels:
	- defaults
	show_channel_urls: true
	default_channels:
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
	custom_channels:
	........

	PS C:\Users\cxxu> conda create -n test_new_env_default
	Collecting package metadata (current_repodata.json): done
	Solving environment: done

	## Package Plan ##

	environment location: d:\condaPythonEnvs\test_new_env_default



	Proceed ([y]/n)?n
	CondaSystemExit: Exiting.

	envs_dirs:
	- C:\users\cxxu\miniconda3\envs
	- d:\condaPythonEnvs

	PS C:\Users\cxxu\Desktop> conda info --env
	# conda environments:
	#
	base C:\Users\cxxu\miniconda3
	py310 C:\Users\cxxu\miniconda3\envs\py310
	py310 C:\users\cxxu\miniconda3\envs\py310
	pytorch_ser d:\condaPythonEnvs\pytorch_ser

	PS C:\Users\cxxu\Desktop> conda create -p $condaPythonEnvs\test_multiple_env_dir_value
	Collecting package metadata (current_repodata.json): done
	Solving environment: done

	## Package Plan ##

	environment location: d:\condaPythonEnvs\test_multiple_env_dir_value



	Proceed ([y]/n)? y

	Preparing transaction: done
	Verifying transaction: done
	Executing transaction: done
	#
	# To activate this environment, use
	#
	# $ conda activate d:\condaPythonEnvs\test_multiple_env_dir_value
	#
	# To deactivate an active environment, use
	#
	# $ conda deactivate

	PS C:\Users\cxxu\Desktop> conda info --env
	# conda environments:
	#
	base C:\Users\cxxu\miniconda3
	py310 C:\Users\cxxu\miniconda3\envs\py310
	py310 C:\users\cxxu\miniconda3\envs\py310
	pytorch_ser d:\condaPythonEnvs\pytorch_ser
	test_multiple_env_dir_value d:\condaPythonEnvs\test_multiple_env_dir_value

	PS C:\Users\cxxu\Desktop> conda activate test_multiple_env_dir_value
	(d:\condaPythonEnvs\test_multiple_env_dir_value) PS C:\Users\cxxu\Desktop>

	PS C:\Users\cxxu\.conda> conda config --show-sources
	==> C:\Users\cxxu\.condarc <==
	auto_activate_base: False
	envs_dirs:
	- d:\condaPythonEnvs
	pkgs_dirs:
	- d:\conda3\pkgs
	- C:\Users\cxxu\AppData\Local\conda\c
	...

xuchaoxin1375

conda发行版比较@python环境管理@conda命令的基本操作@基本使用@conda env list环境条目重复列出问题

文章目录

conda发行版比较@python环境管理@conda命令的基本操作@基本使用@conda env list环境条目重复列出问题

ref

conda官网

conda分类

miniconda

anaconda

文档

官方入门使用教程

更新conda版本

版本比较

Miniconda 镜像使用帮助

winget 命令行下载

环境变量变化

配置软件国内源

基本命令

文档

环境信息检查

列举已安装的包

创建新环境🎈conda create

指定环境的存放目录

conda环境变量

检查配置效果

默认环境存放目录

conda env list条目重复问题👌

检查新环境

移除(删除)已创建环境

实操:移除环境

重命名环境

指定参数不可用@版本过高

获取@更新可用的python版本

用conda启动(激活)指定python环境@conda activate🎈

powershell方式启动

conda install

examples

conda remove

examples

配置conda🎈

python编码工具@vscode

vscode在多个版本的python间切换

jupyter

公告

搜索

常用链接

随笔档案

阅读排行榜

推荐排行榜

	PS D:\repos\blogs\python> conda info -e
	# conda environments:
	#
	CCSER_Client C:\Users\cxxu\.conda\envs\CCSER_Client
	base C:\Users\cxxu\miniconda3
	pyside6 D:\condaPythonEnvs\pyside6
	pytorch_CCSER D:\condaPythonEnvs\pytorch_CCSER🎈
	d2l d:\condaPythonEnvs\d2l
	paddle2.4 d:\condaPythonEnvs\paddle2.4
	pt2.0 d:\condaPythonEnvs\pt2.0
	pyside6 d:\condaPythonEnvs\pyside6
	pytorch_CCSER d:\condaPythonEnvs\pytorch_CCSER🎈
	ser_keras2_2 d:\condaPythonEnvs\ser_keras2_2
	ser_pytorch0_10_0 d:\condaPythonEnvs\ser_pytorch0_10_0
	test_new d:\condaPythonEnvs\test_new
	tf2.10 d:\condaPythonEnvs\tf2.10
	tf2.11 d:\condaPythonEnvs\tf2.11
	tf2.5 d:\condaPythonEnvs\tf2.5
	tf2.8 d:\condaPythonEnvs\tf2.8
	tf210 d:\condaPythonEnvs\tf210

	PS C:\Users\cxxu\.conda> cat .\environments.txt
	C:\Users\cxxu\miniconda3
	d:\condaPythonEnvs\pytorch_CCSER🎈
	d:\condaPythonEnvs\pyside6
	C:\Users\cxxu\.conda\envs\CCSER_Client
	d:\condaPythonEnvs\ser_pytorch0_10_0
	d:\condaPythonEnvs\ser_keras2_2
	D:\condaPythonEnvs\pytorch_CCSER🎈
	d:\condaPythonEnvs\test_new
	D:\condaPythonEnvs\pyside6
	d:\condaPythonEnvs\paddle2.4
	d:\condaPythonEnvs\tf2.8
	d:\condaPythonEnvs\tf2.5
	d:\condaPythonEnvs\d2l
	d:\condaPythonEnvs\pt2.0
	d:\condaPythonEnvs\tf2.10
	d:\condaPythonEnvs\tf2.11
	d:\condaPythonEnvs\tf210

	🚀 conda info -e
	# conda environments:
	#
	base C:\Users\cxxu\miniconda3
	py310 C:\Users\cxxu\miniconda3\envs\py310

	PS C:\Users\cxxu\Desktop> conda env -h
	usage: conda-env-script.py [-h] {create,export,list,remove,update,config} ...

	positional arguments:
	{create,export,list,remove,update,config}
	create Create an environment based on an environment definition file. If
	using an environment.yml file (the default), you can name the
	environment in the first line of the file with 'name: envname' or
	you can specify the environment name in the CLI command using the
	-n/--name argument. The name specified in the CLI will override
	the name specified in the environment.yml file. Unless you are in
	the directory containing the environment definition file, use -f
	to specify the file path of the environment definition file you
	want to use.
	export Export a given environment
	list List the Conda environments
	remove Remove an environment
	update Update the current environment based on environment file
	config Configure a conda environment

	optional arguments:
	-h, --help Show this help message and exit.

	conda commands available from other packages (legacy):
	env

	PS C:\Users\cxxu> conda env remove -h
	usage: conda-env-script.py remove [-h] [-n ENVIRONMENT \| -p PATH] [--solver {classic} \| --experimental-solver {classic}] [-d] [--json] [-q] [-v] [-y]

	Remove an environmentRemoves a provided environment. You must deactivate the existing
	environment before you can remove it.

	Options:

	optional arguments:
	-h, --help Show this help message and exit.
	--solver {classic} Choose which solver backend to use.
	--experimental-solver {classic}
	DEPRECATED. Please use '--solver' instead.

	Target Environment Specification:
	-n ENVIRONMENT, --name ENVIRONMENT
	Name of environment.
	-p PATH, --prefix PATH
	Full path to environment location (i.e. prefix).

	Output, Prompt, and Flow Control Options:
	-d, --dry-run Only display what would have been done.
	--json Report all output as json. Suitable for using conda programmatically.
	-q, --quiet Do not display progress bar.
	-v, --verbose Can be used multiple times. Once for INFO, twice for DEBUG, three times for TRACE.
	-y, --yes Sets any confirmation values to 'yes' automatically. Users will not be asked to confirm any adding, deleting, backups, etc.

	Examples:

	conda env remove --name FOO
	conda env remove -n FOO

	#查看当前有的环境(共有5个)
	PS C:\Users\cxxu\Desktop> conda info --env
	# conda environments:
	#
	base C:\Users\cxxu\miniconda3
	py310 C:\Users\cxxu\miniconda3\envs\py310
	py310 C:\users\cxxu\miniconda3\envs\py310
	pytorch_ser d:\condaPythonEnvs\pytorch_ser
	test_multiple_env_dir_value d:\condaPythonEnvs\test_multiple_env_dir_value

	#开始移除
	PS C:\Users\cxxu> conda env remove -n test_multiple_env_dir_value

	Remove all packages in environment d:\condaPythonEnvs\test_multiple_env_dir_value:
	#检查移除后的列表
	PS C:\Users\cxxu> conda info --env
	# conda environments:
	#
	base C:\Users\cxxu\miniconda3
	py310 C:\Users\cxxu\miniconda3\envs\py310
	pytorch_ser d:\condaPythonEnvs\pytorch_ser

	(base) PS D:\repos\CCSER> conda rename -n py310 pytorch_CCSER -d
	Dry run action: clone C:\Users\cxxu\miniconda3\envs\py310,d:\condaPythonEnvs\pytorch_CCSER
	Dry run action: rm_rf C:\Users\cxxu\miniconda3\envs\py310
	(base) PS D:\repos\CCSER> conda rename -n py310 pytorch_CCSER
	Source: C:\Users\cxxu\miniconda3\envs\py310
	Destination: d:\condaPythonEnvs\pytorch_CCSER
	Packages: 131
	Files: 539

	Downloading and Extracting Packages


	Downloading and Extracting Packages

	Preparing transaction: done
	Verifying transaction: done
	Executing transaction: done
	(base) PS D:\repos\CCSER> conda info --env
	# conda environments:
	#
	base * C:\Users\cxxu\miniconda3
	pytorch_CCSER d:\condaPythonEnvs\pytorch_CCSER

	🚀 conda create -n test python=3.11
	Collecting package metadata (current_repodata.json): done
	Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
	Collecting package metadata (repodata.json): done
	Solving environment: failed

	PackagesNotFoundError: The following packages are not available from current channels:

	- python=3.11

	Current channels:

	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/win-64
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/noarch
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r/win-64
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r/noarch
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2/win-64
	- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2/noarch

	To search for alternate channels that may provide the conda package you're
	looking for, navigate to

	https://anaconda.org

	and use the search bar at the top of the page.

	conda init powershell
	conda config --set auto_activate_base false

	(py310) PS D:\repos\PythonLearn> conda info --env
	# conda environments:
	#
	base C:\Users\cxxu\miniconda3
	py310 * C:\Users\cxxu\miniconda3\envs\py310

	Installs a list of packages into a specified conda environment.

	This command accepts a list of package specifications (e.g, bitarray=0.8)
	and installs a set of packages consistent with those specifications and
	compatible with the underlying environment. If full compatibility cannot
	be assured, an error is reported and the environment is not changed.

	Conda attempts to install the newest versions of the requested packages. To
	accomplish this, it may update some packages that are already installed, or
	install additional packages. To prevent existing packages from updating,
	use the --freeze-installed option. This may force conda to install older
	versions of the requested packages, and it does not prevent additional
	dependency packages from being installed.

	If you wish to skip dependency checking altogether, use the '--no-deps'
	option. This may result in an environment with incompatible packages, so
	this option must be used with great caution.

	conda can also be called with a list of explicit conda package filenames
	(e.g. ./lxml-3.2.0-py27_0.tar.bz2). Using conda in this mode implies the
	--no-deps option, and should likewise be used with great caution. Explicit
	filenames and package specifications cannot be mixed in a single command.