Setting Up a Virtual Environment with `venv` Concepts

What is a Virtual Environment and why are we doing this?

How can you set up your machine so you can run a virtual environment?

The instructions below talk you through a number of steps:

Configure your machine to be able to use virtual environments

Windows people make sure you have GitBash

  1. Install gitbash (32-bit or 64-bit depending on your version of windows): video help and access the install guide here.

Download Python (even if you have it already)

In order to create our environment using venv we need to install python.

  1. Open your terminal/ Git Bash fresh, make sure you aren’t in an environment (you should not be in one if you have never made any before), and the next step is to install python so we can make a DS environment. If you are on a mac you should see (base) at the beginning of your termianl prompt.
  2. Go to this link: 3.11 for Windows or 3.11 for Mac it will open a 3.11 download (do it directly through this link or it can take 15-40 minutes to download Python through terminal). Python 3.9 is too outdated for some of the required libraries, while versions 3.12 and above are too recent for others and that is why we use pyhon 3.11. Please use the exact link provided for Python 3.11.9.
  3. IMPORTANT! - Be sure to check the ‘add python to PATH’ box as well as leaving the pre checked box for admin permissions. This will come up for Windows users, it should not pop up for mac users. This ensures python 3.11 will be used in the environment.
  4. If asked when installing allow it to modify your system (select ‘yes’ when prompted).
  5. Once installed, open a new terminal/Git Bash session and type python -V, you should see the output of the python version you just installed.

Now we have Python and can continue to create our Data Science environment!

Create a dedicated folder in your root directory for all your environments

It’s a good idea to have one folder containing all your environments so they are easy to find and use.

  1. Return to your terminal and type: 
    cd

    Hit enter. (this is important to return your to home directory which looks like ~ )

  2. Type: 
    mkdir virtual

    and hit enter.

  3. Type: 
    cd virtual

    and hit enter.

Now we are inside the directory where we want to make the environment. It is important that we know where it is so we can activate it from anywhere in our file structure.

Create a Virtual Environment

  1. Since we are in our dedicated directory for environments virtual, and have downloaded python 3.11, paste:
python3.11 -m venv <myenv>

in terminal (replace <myenv> with your preferred environment name) and hit enter.

Activate a Virtual Environment

  1. Then, for Mac/Linux (bash/zsh) paste: 
    source <myenv>/bin/activate

    and for Windows (cmd or PowerShell) paste:

    source <myenv>/Scripts/activate

    in terminal/ Git Bash (replacing <myenv> with your preferred environment name) and hit enter. Once activated, you should see (<myenv>) in your terminal prompt.

  2. Then, for Mac/Linux (bash/zsh) paste: 
    pip install --upgrade pip

    and for Windows (cmd or PowerShell) paste:

    python -m pip install --upgrade pip

    in terminal/ Git Bash and hit enter.

Install Dependencies from requirements.txt

Now we need to install a group of core Data Science packages, and these are collected in the requirements.txt file in this repo. Download the repo to get the requirements.txt file only and move it to your ~virtual/<myenv> directory.

  1. We need to move into our environment, so type: 
    cd <myenv>

    and hit enter.

  2. Ensure your virtual environment is activated, then install dependencies with typing:
pip install -r requirements.txt

And hitting enter. This will install all packages listed in the requirements.txt file.

  1. We need to finish setting up jupyterlab, so type: 
    pip install jupyterlab

    and then

    jupyter lab build

    Hitting enter for each line.

Deactivate a Virtual Environment

To exit the virtual environment, simply run:

deactivate

This will return you to the system’s default Python environment.

Reactivate a Virtual Environment

If you need to use the virtual environment again, navigate to your project directory and run the activation command for your OS (from Step 11).

Now you’re all set with a Python virtual environment using venv! 🚀

No matter where you are in your terminal, for Mac/Linux (bash/zsh) running:

source ~/virtual/<myenv>/bin/activate

and for Windows (cmd or PowerShell) running:

source ~/virtual/<myenv>/Scripts/activate

will now activate your virtual environment. This should work on different computers i.e. desktop PCs running Ubuntu on Windows.

See what libraries are installed in the environment

Run this command:

pip list

And you should see the output of the libraries and their versions

Export an environment as a requirements.txt file

Typically you’ll see a requirements.txt file. This will list the libraries and their versions used in an environment.

You can create a text file containing all the libraries you are using in your current virtual environment with this command:

pip freeze > requirements.txt

This will create a requirements.txt text file in your current directory.

Since we’re suggesting you create all your environments in your root directory, you can see which ones are there by running the following in your terminal/git bash

ls ~/virtual/

And you’ll see all the virtual environments that you’ve created.

That’s it! Now you can create and use virtual environments on your machine.

Now You Try

Set up your own virtual environment: