文章目录
- conda发行版比较@python环境管理@conda命令的基本操作
- 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🎈
- 指定环境的存放目录
- conda环境变量
- 检查配置效果
- 检查新环境
- 移除(删除)已创建环境
- 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
conda发行版比较@python环境管理@conda命令的基本操作
ref
- 关于conda环境的配置，看这一篇就够了 - 哔哩哔哩 (bilibili.com)
- anaconda | 镜像站使用帮助 | 北京外国语大学开源软件镜像站 | BFSU Open Source Mirror
- anaconda | 镜像站使用帮助 | 清华大学开源软件镜像站 | Tsinghua Open Source Mirror
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🎈
- 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)
- 事实上,存放环境的默认目录是不需要配置的
- 上面我将默认目录显式再配置进去,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>
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
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
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
- Python in Visual Studio Code
- Using Python Environments in Visual Studio Code
- Jupyter Notebooks in Visual Studio Code
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
