![]() Useful for scripts.> conda install - yes PKG1 PKG2Įxamine Conda configuration and configuration services> conda config - show conda config - show-sources More Resources Run most commands without requiring a user prompt. Update all packages within an environment> conda update - all - name ENVNAME Remove a package from an environment> conda uninstall PKGNAME - name ENVNAME Remove unused cached files including unused packages> conda clean - all Install following several constraints (AND)> conda install “PKGNAME>2.5,❤.2”Īdd a channel to your Conda configuration> conda config - add channels CHANNELNAME Additional Useful Hintsĭetailed information about package versions> conda search PKGNAME - info Install one of the listed versions (OR) > conda install “PKGNAME” Install a package by exact version number (3.1.4)> conda install PKGNAME=3.1.4 Install package from a specific channel> conda install conda-forge::PKGNAM E Search for a package in currently configured channels with version range > =3.1.0, ❤.2">conda search PKGNAME=3.1 “PKGNAME ”įind a package on all channels using the Anaconda Client> anaconda search FUZZYNAME (Replacing the - name parameter as appropriate) Using Packages and Channels > python -m ipykernel install - user - name=my-virtualenv-name ![]() Make an exact copy of an environment> conda create - clone ENVNAME - name NEWENVĮxport an environment to a YAML file that can be read on Windows, macOS, and Linux> conda env export - name ENVNAME > envname.ymlĬreate an environment from YAML fil> conda env create - file envname.ymlĬreate an environment from the file named environment.yml in the current directory> conda env createĮxport an environment with exact package versions for one OS> conda list - explicit > pkgs.txĬreate an environment based on exact package versions> conda create - name NEWENV - file pkgs.txt How to configure jupyter notebook with virtual env Restore an environment to a previous revision> conda install - name ENVNAME - revision REV_NUMBERĭelete an entire environment> conda remove - name ENVNAME - all Sharing Environments List all revisions made in a specified environment> conda list - name ENVNAME - revision List all revisions made within the active environment> conda list - revisions List all packages and versions in a named environment> conda list - name ENVNAME List all packages and versions in the active environment> conda list > conda update anaconda Working with EnvironmentsĬreate a new environment named ENVNAME with speccific version of Python and packages installed> conda create - name ENVNAME python=3.6 “PKG1>7.6” PKG2Īctivate a named Conda environment> conda activate ENVNAMĪctivate a Conda environment at a particular location on dis> conda activate /path/to/environment-dirĭeactivate current environment> conda deactivate Will install stable and compatible versions, not necessarily the very latest. Update all packages to the latest version of Anaconda. Update Conda to the current version> conda update -n base conda Verify Conda is installed, check version number> conda info Available in anaconda> conda env list Getting Started To remove environment> conda remove - name old_name - all Or > conda create - name python_v_3.6 - clone chatbot ![]() To rename environment> create - name new_name - clone old_name To check version of library> conda list lib name(tensorflow) To check list of libraries> conda list -n env name(chatbot) To install libraries> pip install library-name(nltk) To activate environment> activate chatbot To create new environment> conda create -n chatbot(give env name) python= 3.6 List of commonly used commands in anaconda Frequently Useful Commands Here, I’ve prepared cheatsheet for frequently used commands which will help you to create customize new environment, check current version, install different libraries in python/ jupyter notebook and many other things to do ………. When you installed Anaconda, you installed all these too.Ĭonda works on your command line interface such as Anaconda Prompt on Windows and terminal on macOS and Linux. Anaconda Individual Edition contains conda and Anaconda Navigator, as well as Python and hundreds of scientific packages.
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