Using Packages and Virtual Environments in Python

Table of Contents

• Introduction
• The pip Package/Library Installer
• Virtual Environments
• Creating and Using a Virtual Environment
  • Installing virtualenv or venv
  • Creating a Virtual Environment
  • Activating a Virtual Environment
• Leaving the Virtual Environment
• pip Continued

Introduction

Reading Resource: Installing Python Modules

The pip Package/Library Installer

pip is the standard package manager for python. Python packages are usually installed from the pypi library. Starting with Python 3.4, pypi is included by default with the Python binary installers.

pip:

pip is the reference Python package manager. It’s used to install and update packages

pip can be updated on Windows by running:

py -m pip install --upgrade pip

pip can also be updated on Mac or Linux by running:

pip install --upgrade pip

Virtual Environments

To install dependencies to an isolated environment separate from your systems libraries, you can use a virtual environment. One reason you may want this is to match a specific dependency for one project you have.

A virtual environment is a semi-isolated Python environment that allows packages to be installed for use by a particular application, rather than being installed system wide.

Reading Resource: Virtual Environments and Packages

venv:

Python applications will often use packages and modules that don’t come as part of the standard library. Applications will sometimes need a specific version of a library to work properly.

The virtualenv or venv (venv on Python 3.3 or newer) creates a project with a self-contained directory tree that installs a particular version of Python, plus a number of additional packages, and once activated new package installs will download to only that environment. One system can have many virtual environments on it.

Creating and Using a Virtual Environment

Reading Resource: Installing packages using pip and virtual environments

Installing virtualenv or venv

Note: If you are using Python 3.3 or newer, the venv module is the preferred way to create and manage virtual environments and it also comes pre-installed with the standard library. If you are already have venv/virtualenv, you may skip this section.

virtualenv is used to manage python packages for different projects. virtualenv allows you to avoid installing Python packages globally, which could break other tools or projects.

Installing On macOS and Linux:

python3 -m pip install virtualenv

Installing On Windows:

py -m pip install virtualenv

You can optionally add the --user flag to install virtualenv for the current user.

Creating a Virtual Environment

A virtual environment is essentially a isolated Python installation with its own specific packages.

It is generally recommended to use a virtual environment while developing Python applications due to the added isolation and reproducibility.

To create a virtual environment, go to your project’s directory and run venv (or virtualenv for Python 2).

On macOS and Linux:

python3 -m venv <folder location>

On Windows:

py -m venv <folder location>

Activating a Virtual Environment

Before you can start installing or using packages in your virtual environment you’ll need to activate it. Activating a virtual environment will put the virtual environment-specific python and pip executables into your shell’s PATH.

On macOS and Linux:

source env/bin/activate

On Windows:

.\env\Scripts\activate

Leaving the Virtual Environment

If you want to switch projects or otherwise leave your virtual environment, simply run:

deactivate

Pip Continued

Usage:
  pip <command> [options]

Commands:
  install - Install packages.
  download - Download packages.
  uninstall - Uninstall packages.
  freeze - Output installed packages in requirements format.
  list - List installed packages.
  show - Show information about installed packages.
  check - Verify installed packages have compatible dependencies.
  config - Manage local and global configuration.
  search - Search PyPI for packages.
  cache - Inspect and manage pip's wheel cache.
  wheel - Build wheels from your requirements.
  hash - Compute hashes of package archives.
  completion - A helper command used for command completion.
  debug - Show information useful for debugging.
  help - Show help for commands.

Use pip install <library> to install

Use pip freeze or pip list to see all libraries installed on your current Python environment.