Conda is a package manager that comes with Anaconda.
And i wanted to make a list of all this commands so that users can find them quickly when necessary…
To install a package, just substitute the package_name with the package you want to install in the following code.
conda install package_name
Similarly to uninstall or removing a package..
conda remove package_name
You can install multiple packages at the same time. Something like
conda install numpy scipy pandas
It’s also possible to specify which version of a package you want by adding the version number such as
conda install numpy=1.10
To update a package
conda update package_name
If you want to update all packages in an environment, which is often useful, use
conda update --all
To list installed packages,
If you don’t know the exact name of the package you’re looking for, you can try searching with
conda search *search_term*
For example, I know I want to install Beautiful Soup, but I'm not sure of the exact package name. So,
conda search *beautifulsoup*
Note that your shell might expand the wildcard
* before running the conda command. To fix this, wrap the search string in single or double quotes like
conda search '*beautifulsoup*'
It returns a list of the Beautiful Soup packages available with the appropriate package name,
conda can be used to create environments to isolate projects. To create an environment,
conda create -n env_name list of packages
-n env_name sets the name of your environment (
-n for name) and
list of packages is the list of packages you want installed in the environment.
For example, to create an environment named
my_env and install numpy in it, type
conda create -n my_env numpy
To create an environment with a specific Python version, do something like
conda create -n py3 python=3
conda create -n py2 python=2
Once you have an environment created, use
conda activate my_env to enter it.
To leave the environment, type
conda deactivate (on OSX/Linux).
On Windows, use
conda activate and
conda deactivate only work on conda 4.6 and later versions. For conda versions prior to 4.6, run
deactivate (on Windows),
source activate or
source deactivate (on OSX/Linux)
A really useful feature is sharing environments so others can install all the packages used in your code, with the correct versions. You can save the packages to a YAML file with
conda env export > environment.yaml
The first part
conda env export writes out all the packages in the environment, including the Python version.
environment.yaml can now be shared and others will be able to create the same environment you used for the project.
To create an environment from an environment file use
conda env create -f environment.yaml
This will create a new environment with the same name listed in
If you forget what your environments are named (happens to me sometimes), use
conda env list to list out all the environments you've created.
If there are environments you don’t use anymore,
conda env remove -n env_name will remove the specified environment (here, named
To learn more about conda and how it fits in the Python ecosystem, check out this article by Jake Vanderplas: Conda myths and misconceptions. And here’s the conda documentation you can reference later, and a link to a cheatsheet to help you basic conda commands.