python-productivity.md

Setting up a productive Python environment

:::{tags} Python IPython Pip Venv :::

I work with Python 3.8 at the very least, so the virtual environment is based on venv, which is the recommended approach for modern Python.

The recommendations in this note are universally useful and applicable regardless of the project's specifics.

A better interpreter interface

Install ipython using pip:

$ pip3 install ipython

Now ipython command is available and should be used for interactive work instead of standard python interpreter CLI.

Why set up virtual environments?

The Python package manager pip by default installs (and updates) packages globally. This is not optimal since different programs may rely on different versions of the same package.

Furthermore, different versions of the Python intepreter itself might be required for different projects.

To resolve this, Python includes powerful tools to manage dependencies of our programs by creating virtual environments.

The virtual environment configuration file would store what Python interpreter version is used, as well as all PyPI modules utilised in the project and their version numbers.

Setting up the virtual environment

This is done on per project basis. To create the environment:

• Create a project directory
• Change into the project directory
• Run python3 -m venv <name_of_virtualenv>

Example of the last step:

project-folder$ python3 -m venv env

Now can activate the environment:

project-folder$ source env/bin/activate

The shell prompt gets replaced by the environment's shell prompt:

(env) $

Note, that the directories and files comprising the virtual environment itself are automatically added to the .gitignore file and will not be (and should not be) checked into the revision control system.

In other words, only the virtual environment configuration will be stored in the revision control system, and when necessary, the virtual environment will be recreated by the Python tools.

Using the virtual environment

Now when pip is invoked, it will install the packages into the current project's environment and all project's dependencies can be version controlled and managed.

For example, install the requests module into the current environment (project):

(env) $ pip install requests

To take inventory of the installed modules run:

(env) $ pip freeze > requirements.txt

The file name requirements.txt is a convention. This file should be stored in the revision control system and it will be useful for setting up identical environment on a different machine.

To install the modules to the requirements listed in requirements.txt, run the following command in a new virtual environment, potentially on a different machine:

(env) $ pip install -r requirements.txt

The file requirements.txt usually stores everything necessary to develop and test the application. This is often more than what would be included in the shipped application.

Leaving the virtual environment

To leave the virtual environment, run deactivate:

(env) $ deactivate

This will take you to the familiar bash prompt outside of the Python virtual environment.

More information on the virtual environments

RealPython's What Virtual Environments Are Good For? and the materials linked from there.

—Oliver Frolovs, 2020