Managing Python Environments with VirtualEnv

Last updated on 2022-11-15 | Edit this page

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Environments and Package managers

Overview

Questions

  • How can I make sure the whole team (or lab) gets the same results?
  • How can I simplify setup and dependencies for people to use my code or reproduce my results?

Objectives

  • Identify an environment, dependencies, and an environment manager
  • Install an older version of python
  • Use virtualenv to create an environment per project
  • Store a projects’ dependencies
  • install dependencies for a project

An environment consists of a certain Python version and some packages. A virtual environment allows you to have multiple, independent versions of python on your system. Environments can also be saved so that you can install all of the packages and replicate the environment on a new system.

Why use one:

  • to deliver code and keep it the same versions
  • to use contribute to a package you also use
  • to install on servers
  • to share your environment with others

how to chose which of the main strategies to use: virtualenv and pip or conda

conda comes from Anaconda and does both package management and provides a virtual environment.

pip is the main python package installer

virtualenv creates environments and are pip install compatible.

Making your own packages pip installable requires fewer dependencies, so we’ll focus on virtualenv and pip in this workshop

Create an environment

Before we create an environment, let’s see what happens when we import one of our favorite packages. In a python interpreter:

PYTHON 

import numpy

That should work, because we have the package installed on our system. If not, use a package you know you have installed, or install numpy.

Next, we’ll create an environment an environment from scratch.

BASH 

virtualenv myenv

if python 3 isn’t your default you might need to pass the version of python that you want installed:

BASH 

virtualenv myenv -p python3.6

then we can activate the environment

BASH 

source myenv/bin/activate

Now we see that the cli changes to show the environment name and we can further test our environment with our favorite package from before.

PYTHON 

import numpy

Now, it won’t work, but we can install it and a few other favorites.

BASH 

pip install numpy

save an environment

BASH 

pip freeze > requirements.txt

Deactivate an environment

When you’re done with an environment, you exit it with deactivate. Also note that an environment only exists in the one terminal window. If you open a new terminal, you’ll be back to your default environment.

BASH 

deactivate

Exercise

download a project, create a new environment and install from the requirements file

Hint: use the pip man file to find options you can pass to pip install

BASH 

pip install -r requirements.txt

Key Points

  • A python dependency is another, independent package that a given project uses and requires to be able to run
  • An environment is
  • An environment manager enables one step installing and documentation of dependencies, including versions
  • Virtualenv is …