Brief Introduction to Python Virtual Environment

You may have heard the term “virtual environment” before, but what exactly is it?
Virtual environments are a way of isolating projects from each other. This means that you can install and run different versions of Python on your computer without affecting any other projects you’re working on. It also makes it easier to share code between different projects — you don’t have to worry about accidentally bringing in dependencies from one project into another because they’re installed in separate places!
In this post I’ll explain why virtual environments are useful for Django development, and how you can use them with Docker Compose to create a fully-functional test server environment for your next project.

What is a Python Virtual Environment?

A virtual environment is a way of creating an isolated working environment for your Python projects. It allows you to install and use libraries that are specific to your project, without affecting other projects or the global site-packages directory.
Virtual environments allow you to create separate copies of Python packages (libraries), which can then be used by different projects on your computer without conflicting with each other. This means that if one project needs version 1.0 of a library while another needs 2.0, they can both use their own versions without affecting each other’s functionality or causing errors when running commands such as pip install .

Why Use Virtual Environments in Django Development?

Virtual environments are a great way to manage dependencies in large Python projects. Large projects often have many different dependencies, which can make it difficult to install and update packages. This can cause problems if you’re working on multiple projects with different requirements, or if one project relies on an older version of a library that conflicts with another project’s newer version.
Virtual environments allow you to keep separate copies of your libraries and their dependencies installed on your machine without conflicting with each other. They also allow you to easily switch between different versions of libraries as needed.

Steps to Create and Activate a Virtual Environment

Creating a virtual environment

Creating a virtual environment is a simple process that can be done using the venv module that comes with Python. To create a virtual environment, open a terminal or command prompt and navigate to the directory where you want to create the environment. Then, run the following command:

python -m venv myenv

This will create a new directory called myenv in the current directory, which contains a Python installation and a `pip` executable that can be used to install packages.

Activating a virtual environment

Once the virtual environment has been created, it needs to be activated before it can be used. To activate a virtual environment, navigate to the directory where the environment was created and run the appropriate activation command for your operating system:

On Windows:

myenv\Scripts\activate

On macOS or Linux:

source myenv/bin/activate

Once the virtual environment is activated, any packages installed using pip will be installed in the virtual environment, rather than in the global Python environment.

Best Practices for Using Virtual Environments in Django Development

When you’re ready to get started with Django development, it’s important to understand how virtual environments work. The following best practices will help you create and manage your own virtual environments:

• Use a separate virtual environment for each project. This is the most important step in ensuring that your projects are isolated from each other, so that they don’t conflict with one another or share dependencies with other projects on your computer.
• Create an activate script for each new project that automatically activates its associated virtual environment when run. This ensures that every time you open up the command line within this directory, it loads all of its requirements into memory without any additional steps required on your part (other than running this script).
• Use a requirements.txt file to document the dependencies for your project. This file can be used to recreate the virtual environment on another system or to share the dependencies with other developers.
• Don’t commit the virtual environment to version control: Do not commit the virtual environment to version control. Instead, commit the requirements.txt file, which can be used to recreate the virtual environment.
• Update dependencies regularly: Regularly update the dependencies in your virtual environment to ensure that you are using the latest versions and any security vulnerabilities are patched.
• Delete old virtual environments: Once a project is complete, delete the virtual environment to free up space on your system.

In this post, we covered the basics of virtual environments and how they can be used in Django development. We also looked at some of the more advanced features of virtual environments and how they can help you manage your project’s dependencies.
If you’re interested in learning more about Python virtual environments or Django development, here are some resources that I recommend:

• Python Virtual Environments: An Introduction — A great introduction to using Python virtual environments by DigitalOcean
• The Hitchhiker’s Guide To Python — A book written by Trey Hunner (who also maintains pipenv) that covers everything from installing Python 3 all the way up through deploying web applications with Docker containers