Why bother?#
I create a bunch of little Python projects and I like to have them sandboxed and independent of each other. I also sometimes need to change which version of Python I am running due to requirements of dependencies. Your OS may come installed with Python but it’s rarely a great idea to try and run your projects from it.
Here’s what I do:
Install asdf
#
asdf
is a tool version manager.
There are good docs on how install it depending on your setup and preferences, described here.
Open a new shell session after editing your shell rc file and validate you successfully installed asdf
asdf -V
#=> v0.11.0
Next, add the Python plugin for asdf
.
asdf plugin-add python
You can now install any version of Python.
asdf install python 3.11.1
To switch to the version you installed, run
asdf global python 3.11.1
Setup a virtual environment from asdf
managed Python#
To start, see what versions of Python you’ve had asdf
install.
I have two versions:
asdf list
python
*3.11.1
3.7.9
We can see that our python
is currently the asdf
managed version of Python.
which python
#=> ~/.asdf/shims/python
We can also validate it’s the same version as asdf
claims:
python -V
#=> Python 3.11.1
Let’s create a virtual environment.
First cd
to your project folder, then run:
python -m venv env
Activate the virtual environment and validate your shell is pointing to the virtual environment’s python
rather than asdf
’s.
You should also see that the virtual environment’s version of Python is the same as asdf
’s.
. env/bin/activate
which python
#=> ~/dev/python_env_test/env/bin/python
python -V
#=> Python 3.11.1
Next, let’s switch Python versions.
# stop using the virtual environment
deactivate
# install first, if you need to
asdf global python 3.7.9
which python
#=> ~/.asdf/shims/python
python -V
#=> Python 3.7.9
Create a second virtual environment.
python -m venv env2
. env2/bin/activate
which python
#=> ~/dev/python_env_test/env2/bin/python
python -V
#=> Python 3.7.9
deactivate
once more and your back to your standard shell with asdf
managed python
.
If you ever see Python code you want to try out on your own machine that requires dependencies, or when starting a new project, I recommend setting up a virtual environment for the version you need like this. Once you have the virtual environment setup and activated, you can install any dependencies you need in a spot that won’t affect your system install or any other projects.
What’s next?#
I’ve been hearing a lot about nix and direnv
as a killer combo for managing dev environments.
I’m hoping to try that out and might revist my setup here if it goes well.