Having gotten use to using Anaconda and Conda to create and manage Python projects, I recently found myself in the position of wanting the same degree of dependency management for different projects without the need of installing additional software. Luckily enough, Python 3.3+ supports virtual environments out of the box albeit in a very stripped-down forn. This short post is just to demonstrate how to use this neat tool - things that I have been consistently forgetting! Some of these steps are specific to the OS and shell that I use: macOS and ZSH. YMMV.

Assuming your version of Python supports virtual environments, you can create a new virtual environment in your terminal with,

python -m venv my-virtual-environment

which will create all the dependencies for the new virtual environment in the current working directory. You can also specify a path to your new virtual environment as well. For the purpose of development, it’s easier to activate a virtual environment to save you from consistently specifying the environment’s full path during development. To activate the virtual environment use,

source my-virtual-environment/bin/activate

Within the activated virtual environment, you can use pip as required to install particular dependencies. You can then save all your project dependencies to a text file,

pip freeze > requirements.txt

and then use this to install the matching dependencies in another environment or project

pip install -r requirements.txt

Finally, leave your virtual environment with


All the best,


Tom Martin

Data scientist, London, UK