Introduction
Anaconda is very easy to manage packages and environments for use with Python. Also simplifies dealing with packages and multiple Python versions. Creating virtual environments that make working on multiple projects much easier.
Conda is also a virtual environment manager. It’s similar to virtualenv and pyenv etc,.
Installation instructions for Anaconda
Managing Packages
Once you have Anaconda installed, managing packages is fairly straightforward. To install a package, type in your terminal.
Install packages using conda
Most of the commands are pretty intuitive.
conda install <package-name>
You can install multiple packages at the same time.
conda install numpy scipy pandas
will install all those packages simultaneously.
It is also possible to specify which version of a package you want by adding the version number such as
conda install numpy=1.10
Conda also automatically installs dependencies for you. For example scipy depends on numpy, it uses and requires numpy. If you install just scipy Conda will also install numpy if it isn’t already installed.
conda install scipy
List installed packages
conda list
Update a package
conda update <package-name>
Update all packages in an environment
conda update --all.
Uninstall a package
conda remove <package-name>
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, you know that you want to install Beautiful Soup, but not sure of the exact package name.
conda search beautifulsoup.
It returns a list of the Beautiful Soup packages available with the appropriate package name, beautifulsoup4.
Managing environments
Creating conda environment
conda create -n <env_name> <list of packages>
Example
conda create -n my_env numpy
To create an environment with a specific Python version.
create -n py3 python=3
or
conda create -n py2 python=2
Saving and loading environments
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. The second part of the export command, * environment.yml* writes the exported text to a YAML file ** environment.yml **
Create virtual environment from file
conda env create -f environment.yml
Listing environments
conda env list
Removing environments
conda env remove -n env_name
Entering an environment
Activating conda environment
source activate my_env
Checking installed package list in conda env
conda list
Deactivating conda environment
source deactivate