ML of Anaconda: Anaconda command of all conda collection - to be finishing

 

 

ML of Anaconda: Anaconda command of all collections conda

 

 

table of Contents

1, create the relevant virtual environment

2, the packet processing function relating

3, change source

4, sharing the code related

 

 

0, Anaconda prompt to enter a directory
general DOC command: C retreated root directory, type: cd / then enter
cd D: \ ProgramData \ Anaconda3 \ envs \ cocoapi-master \ PythonAPI

 


1, to create a virtual environment-related
conda --version # View the current version
conda config --show # View all the configuration
conda env list # show all the environmental
conda deactivate # exit the current environment
conda create --name CV202001 python = 3.6 # to create a virtual environment

 

2, packet processing-related functions
related articles: a, pip set of commands

conda list # View installed package
conda install package_name # uninstall package
conda remove package_name # remove the package
conda update package_name # update the specified packages
to uninstall the old version
conda install tensorflow # installation tensorflow and its dependencies

# Whl download files in conda, direct input
PIP install D: \ ProgramData \ Anaconda3 \ Envs \ Torch-1.3.1-CP36-cp36m-win_amd64.whl
PIP install -r F: \ File_Python \ Python_example \ EfficientDet_Pytorch \ requirements. TXT

 

3, change source
conda config --show channels # display the current download the source
Conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
Conda config --add channels HTTPS: //mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
Conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
Conda config --set show_channel_urls yes
Conda config --remove-Key # channels cut back to the default source

 

4, sharing the code related
conda env export> environment.yaml # needs to share the operating environment for everyone, execute the following command to package the information in the current environment may be stored in a file named YAML environment in
conda env create -f environment.yaml # others use the generated file creation environment yaml

 

 

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