Coding organization: A quick look at virtual environments

Read Time ~ 7 Minutes

If you have ever gone to install and import a package only for it to not be found, load up an older project only to find it broken, or have a co-worker say “It works on my computer.” then virtual environments might be for you!

What is a virtual environment?

If you have never heard of virtual environments before they are basically self contained developer sandboxes where anything you install (languages, packages, etc.) is isolated from the rest of your computer.

Why might this be useful?

One word- Dependencies.

Picture this, you are put on a old project that has an older code base and is using an older version of python. You work on it for a few weeks and then get re-tasked to work on another project. The thing is, this project is using the newest version of python. OK. So you update your version of python but then some of your packages break because they required the older version. So you update those but then all of a sudden you have to go back and fix something on the older code base and now you have to downgrade and- well you get the idea.

Virtual environments solve this problem and allow you to context switch very quickly to different projects all while avoiding any version and dependency issues. They keep everything isolated from each other to allow everyone to “play nice” and not cause any trouble.

Let’s take a look at two different way to set up virtual environments.

NOTE: There are many different virtual environment managers. These are just two that I find cover most bases.

The Bare Bones Way

This approach is very minimalistic and doesn’t really hold your hand but allows you to set up things exactly the way you want.

NOTE: This assumes you already have a base version of python installed on your computer. Mac and most Linux distributions come preinstalled with python. Windows computers will have to download one. If you are unsure if you have python on your computer, open up a CMD prompt/terminal and type: python —version (thats two dashes). The readout should tell you the version if it is installed. If not, it should say something along the lines of “Unknown command: python —version…”

Python comes with its own built in virtual environment manager called “venv” which is lightweight and gets the job done so we will use that.

First open up your command prompt and navigate to where you want to create your environment.

I’m under my Documents in a folder called “env_example”.

Then type the following:

Where “my_env” is the name you want to give to your virtual environment. Usually I name it something in relation to the project in which it’s for.

After a few seconds you should see a new folder in the directory with the name you chose.

Great! We have made our environment…Now what?

We have to activate it!

Type the following from the same folder where you created it:

and now you should see the following:

So if you notice, right before the path is the name of our virtual environment. What this means is anything we do in this terminal like install new packages or run code will use this virtual environment’s version of python and keep everything we install isolated from the rest of out computer.

Once you are done working in that environment you can type deactivate to disable it:

That’s the basics of working with a virtual environment. There are a few more things like saving your virtual environment’s packages so you can share your projects but this will get you started. Next, let’s look at a “friendlier way” of working with virtual environments.

The GUI Experience

While the previous way allows you to control everything as well as save on space, the next way is to use a program called Anaconda in order to set up your virtual environments.

Anaconda is a one stop shop software suite that allows you to create and manage different programming environments on your computer. It has become a great option for people looking for a little more of a curated experience when setting up their development environments. It’s available on all platforms and is fairly easy to install.

I find myself using it more and more for its simplicity and easy to use GUI.

First download and install Anaconda.

Open it up and you should see a screen like this:

On the left hand side click on “Environments” and you should see the following screen:

On the left you will see a list of your environments. There should be only one called “base (root)” and this is your default environment. From here we can create a new one by clicking the plus icon called “Create” at the bottom left of the screen. It will prompt you what language and version you want to install and ask for a name for the environment. I called mine “test” and once you go through the steps it should automatically activate your new environment.

From here, left click on the white arrow with the green boarder and hit “Open Terminal” and you should see something like this:

As you can see it’s pretty much the same outcome as the “Bare Bones” way of doing things just with a nice easy GUI to make it easier. From here you can install packages like normal and it keeps everything isolated. To switch environments just left click on the one you want. Very simple.

Wrapping it up

While there are a lot of other features and things you can do with your virtual environment this will get you started and stop those pesky dependency errors.

I hope you found this more technical and tutorial like edition of AI Insights helpful. Let me know if you would like similar editions to be along these lines.

Until next time.

Andrew-

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