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Introduction to Python - CONDA common commands
2022-01-30 06:25:52 【Why】
- Little knowledge , Great challenge ！ This article is participating in “ A programmer must have a little knowledge ” Creative activities .
This paper introduces the use of conda management anaconda Python Environment related commands .
conda Environment related commands
Create an environment
conda create -n env_name python=3.7 --clone another_env Copy code
-n：name Indicates the name of the new environment
python： Use python edition
--clone： Copy from existing environment
conda remove -n env_name --all Copy code
Look at the environment
conda env list Copy code
conda info -e Copy code
Activate the environment
conda activate env_name Copy code
source activate env_name Copy code
Out of the environment
conda deactivate Copy code
source deactivate Copy code
Will return to
conda Package related commands
View the current environment conda Managed python Package list
conda list Copy code
install python package
conda install package_name # Installation package conda install package_name_1 package_name_2 package_name_3 ... # Install multiple packages at a time conda install package_name=1.1.0 # Install the specified version of the package Copy code
conda update package_name # Update package conda upgrade --all # Update all packages Copy code
conda remove package_name Copy code
Search for packages with unclear names
conda search search_term Copy code
conda Recreate the environment
Use conda management python An important consideration is portability ,conda Several methods are provided for reproducing a conda Environmental Science .
This command has been described above , Used to reproduce an environment locally
conda create --name new_env --clone old_env Copy code
Copy the environment between computers with the same operating system , Can generate
Generate spec list file conda list --explicit > spec-list.txt Recreate the environment ： conda create --name python-course --file spec-list.txt Copy code
Use -export Option to generate a
environment.ymlfile , To replicate the project environment between different platforms and operating systems .
spec list Document and
environment.ymlThe difference between files is ：
environment.ymlFiles are not specific to a particular operating system , And use YAML Format .
environment.ymlOnly the package name is listed , from conda Build the environment based on the name of the package . Another difference is -export It also includes the use of pip Installed packages , and
spec listThere is no .
export environment.yml file ： conda env export > environment.yml Recreate the environment ： conda env create -f environment.yml Copy code
Be careful ： If the current path already has environment.yml file ,conda Will rewrite this file
The above two reproduction methods are based on recording the current environment package information , To the idea of new machine reconstruction . and Conda Pack It is used to package the files of the current environment directly , The idea of unpacking the new machine .
conda-pack Specify the platform and operating system , The target computer must have the same platform and operating system as the source computer .
install conda pack
from conda conda install -c conda-forge conda-pack from pip pip install conda-pack Copy code
conda pack -n my_env conda pack -n my_env -o out_name.tar.gz Copy code
Recreate the environment
mkdir -p path_to_my_new_env # Advice on anaconda Of envs In the folder tar -xzf my_env.tar.gz -C path_to_my_new_env # Unzip the files in the package source path_to_my_new_env/bin/activate # Activate the environment (my_env) $ python # Let's take a look at python Then exit (my_env) $ conda-unpack # Very important , Please don't ignore Copy code
author[Why],Please bring the original link to reprint, thank you.
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