Creating and Managing Python Virtual Environments: A Step-by-Step Guide

Python is known for its easy learning curve, natural syntax, and great versatility. This makes it a popular choice for large-scale automation projects that evolve over time. A key secret to unlocking that versatility is creating Python virtual environments.

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What Is a Virtual Environment in Python?

A virtual environment, or virtualenv, is a fully self-contained development environment, complete with its own Python interpreter, libraries, and required dependencies. This creates a separate “mini” Python setup that’s completely isolated from the system-wide Python installation and any other virtual environments you may have.

How to Create a Python Virtual Environment

1. Get a VPS for Your Virtual Environment

First, you’ll need a Virtual Private Server (VPS) to run your virtual environment. Make sure you choose a reliable, secure, and scalable VPS hosting service so that it’s easy to create and manage multiple virtual environments in the long run.

2. Set up Your Virtual Private Server

Log in to your VPS and configure it as needed. For example, you can update the VPS, create users for yourself and your colleagues, configure a firewall and other security controls, as well as check out the required source code repositories.

3. Connect to your VPS

After you have set up your VPS, you are ready to SSH into it. SSH (Secure Shell) is a secure communication protocol for remotely accessing and managing servers. You can use PuTTY, a SSH client, to SSH into your VPS.

4. Install Python

Then, install Python on your VPS by running the following command:

sudo apt install python3

Let’s also install pip, as it will be used to fetch the required packages:

sudo apt install python3-pip

5. Create Your First Virtual Environment

To create your first new virtual environment for Python, you will need the venv module. If you are using Python 3.3 or above, the venv module is included in the standard library, so there’s no need to install it separately.

Start by checking your Python version by running this command:

python3 --version

If you are on a version lower than 3.3, you can install the module by running this command:

sudo apt install python3-venv

Remember, if you are on 3.3 or higher, you don’t have to run the above command. Either way, you should now be ready to initialize the virtual environment.

Create a new virtual environment directory and navigate inside it as follows:

mkdir myproject
cd myproject

Now, run the following command to create the virtual environment:

python3 -m venv myenv

Replace myenv with your preferred environment name. After a few moments, you should see a new directory created with the name of your virtual environment.

6. Activate the Virtual Environment

To activate a virtual environment, input this command:

source myenv/bin/activate

If you chose a different name for your virtualenv, make sure to use that instead of myenv in the above command.

Deactivating and Removing Virtual Environments

If you need to deactivate a virtual environment, simply execute the following command:

deactivate

To remove a virtual environment, simply navigate to its parent directory and issue the following command:

rm -rf myenv

Managing Multiple Environments

The best part about creating virtual environments is the freedom to have as many as you need on your system. This means that you can have one environment for a web development project using Django, another for a data analysis project using pandas, and yet another for a machine learning project using TensorFlow.

Installing Libraries in a Virtual Environment

After you have created and activated a venv in Python, you are ready to install libraries inside it to achieve the desired configuration. pip should also be pre-installed inside the environment, and we will now install the needed libraries.

For example, you can install the numpy library by running this command:

pip install numpy

It’s also possible to install a particular version of a library. For example, the following command installs the 2.25.1 version of the requests library, along with all its dependencies:

pip install requests==2.25.1

To see the list of installed packages, use this command:

pip list

Installing Libraries via a Requirements File

If your project uses several libraries, you can also create a requirements file that specifies the list of libraries along with their needed versions.

To install all the libraries listed in this requirements file, run this command:

pip install -r requirements.txt

Exploring Other Virtual Environment Features

The venv module allows you to export the configuration of a virtual environment to a requirements file. This can be handy if you want to share your environment setup with collaborators or recreate it on another machine.

To do so, activate your virtual environment and run the following command:

pip freeze > requirements.txt

If at any time you want to ensure that all the dependencies in the environment are up-to-date and consistent, run this command:

pip check

To update all the packages in your virtual environment to their latest versions, run this command:

pip install --upgrade -r requirements.txt

Python virtual environments are a foolproof way to test Python code in self-sufficient sandboxes. Whether you have to reproduce a production bug, manage different versions of Python code on the same machine, or experiment with different libraries without affecting your main Python installation, virtual environments are the way to go.

You should now feel confident to create, set up, and manage a virtual environment within Python. It’s time to try out your first Python virtual environment for yourself.

How to Create a Virtual Environment in Python FAQ

Why Would I Need to Create a Virtual Environment for My Python Projects?

A virtual environment allows you to create a sandboxed environment for testing Python applications. Each environment can have its own version of Python interpreter, source code, and libraries. This way, you can test for errors or trial different configurations and scenarios without affecting any Python installations on your main system.

Can I Create Multiple Virtual Environments for Different Python Projects?

You can create multiple virtual environments for your Python projects on the same machine. To switch between two virtual environments, simply deactivate the current one and activate the other.

Can I Install Packages and Dependencies Within a Virtual Environment?

You can install packages and dependencies in a virtual environment using the pip command. These packages and dependencies won’t conflict with or replace any packages installed on the main system.

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