virtualenv is a tool to build isolated Python environments. This program creates a folder which contains all the necessary executables to use the packages that a Python project would need.

Installing the virtualenv tool

This is only required once. The virtualenv program may be available through your distribution. On Debian-like distributions, the package is called python-virtualenv or python3-virtualenv.

You can alternatively install virtualenv using pip (opens new window):

$ pip install virtualenv

Creating a new virtual environment

This only required once per project. When starting a project for which you want to isolate dependencies, you can setup a new virtual environment for this project:

$ virtualenv foo

This will create a foo folder containing tooling scripts and a copy of the python binary itself. The name of the folder is not relevant. Once the virtual environment is created, it is self-contained and does not require further manipulation with the virtualenv tool. You can now start using the virtual environment.

Activating an existing virtual environment

To activate a virtual environment, some shell magic is required so your Python is the one inside foo instead of the system one. This is the purpose of the activate file, that you must source into your current shell:

$ source foo/bin/activate

Windows users should type:

$ foo\Scripts\activate.bat

Once a virtual environment has been activated, the python and pip binaries and all scripts installed by third party modules are the ones inside foo. Particularly, all modules installed with pip will be deployed to the virtual environment, allowing for a contained development environment. Activating the virtual environment should also add a prefix to your prompt as seen in the following commands.

# Installs 'requests' to foo only, not globally
(foo)$ pip install requests

Saving and restoring dependencies

To save the modules that you have installed via pip, you can list all of those modules (and the corresponding versions) into a text file by using the freeze command. This allows others to quickly install the Python modules needed for the application by using the install command. The conventional name for such a file is requirements.txt:

(foo)$ pip freeze > requirements.txt
(foo)$ pip install -r requirements.txt

Please note that freeze lists all the modules, including the transitive dependencies required by the top-level modules you installed manually. As such, you may prefer to craft the requirements.txt file by hand (opens new window), by putting only the top-level modules you need.

Exiting a virtual environment

If you are done working in the virtual environment, you can deactivate it to get back to your normal shell:

(foo)$ deactivate

Using a virtual environment in a shared host

Sometimes it's not possible to $ source bin/activate a virtualenv, for example if you are using mod_wsgi in shared host or if you don't have access to a file system, like in Amazon API Gateway, or Google AppEngine. For those cases you can deploy the libraries you installed in your local virtualenv and patch your sys.path.

Luckly virtualenv ships with a script that updates both your sys.path and your sys.prefix

import os

mydir = os.path.dirname(os.path.realpath(__file__))
activate_this = mydir + '/bin/activate_this.py'
execfile(activate_this, dict(__file__=activate_this))

You should append these lines at the very beginning of the file your server will execute.

This will find the bin/activate_this.py that virtualenv created file in the same dir you are executing and add your lib/python2.7/site-packages to sys.path

If you are looking to use the activate_this.py script, remember to deploy with, at least, the bin and lib/python2.7/site-packages directories and their content.

Built-in virtual environments

From Python 3.3 onwards, the venv module (opens new window) will create virtual environments. The pyvenv command does not need installing separately:

$ pyvenv foo
$ source foo/bin/activate

or

$ python3 -m venv foo
$ source foo/bin/activate

In order to specify which version of python the Linux shell should use the first line of Python scripts can be a shebang line, which starts with #!:

#!/usr/bin/python

If you are in a virtual environment, then python myscript.py will use the Python from your virtual environment, but ./myscript.py will use the Python interpreter in the #! line. To make sure the virtual environment's Python is used, change the first line to:

#!/usr/bin/env python

After specifying the shebang line, remember to give execute permissions to the script by doing:

chmod +x myscript.py

Doing this will allow you to execute the script by running ./myscript.py (or provide the absolute path to the script) instead of python myscript.py or python3 myscript.py.

Assuming python and python3 are both installed, it is possible to create a virtual environment for Python 3 even if python3 is not the default Python:

virtualenv -p python3 foo

or

virtualenv --python=python3 foo   

or

python3 -m venv foo

or

pyvenv foo

Actually you can create virtual environment based on any version of working python of your system. You can check different working python under your /usr/bin/ or /usr/local/bin/ (In Linux) OR in /Library/Frameworks/Python.framework/Versions/X.X/bin/ (OSX), then figure out the name and use that in the --python or -p flag while creating virtual environment.

A powerful alternative to virtualenv is Anaconda (opens new window) - a cross-platform, pip-like package manager bundled with features for quickly making and removing virtual environments. After installing Anaconda, here are some commands to get started:

Create an environment

conda create --name <envname> python=<version>

where <envname> in an arbitrary name for your virtual environment, and <version> is a specific Python version you wish to setup.

Activate and deactivate your environment

# Linux, Mac
source activate <envname>                            
source deactivate

or

# Windows
activate <envname>                                    
deactivate

View a list of created environments

conda env list

Remove an environment

conda env remove -n <envname>

Find more commands and features in the official conda documentation (opens new window).

Once your virtual environment has been activated, any package that you install will now be installed in the virtualenv & not globally. Hence, new packages can be without needing root privileges.

To verify that the packages are being installed into the virtualenv run the following command to check the path of the executable that is being used :

(<Virtualenv Name) $ which python
/<Virtualenv Directory>/bin/python

(Virtualenv Name) $ which pip
/<Virtualenv Directory>/bin/pip

Any package then installed using pip will be installed in the virtualenv itself in the following directory :

/<Virtualenv Directory>/lib/python2.7/site-packages/

Alternatively, you may create a file listing the needed packages.

requirements.txt:

requests==2.10.0

Executing:

# Install packages from requirements.txt
pip install -r requirements.txt

will install version 2.10.0 of the package requests.

You can also get a list of the packages and their versions currently installed in the active virtual environment:

# Get a list of installed packages
pip freeze

# Output list of packages and versions into a requirement.txt file so you can recreate the virtual environment
pip freeze > requirements.txt

Alternatively, you do not have to activate your virtual environment each time you have to install a package. You can directly use the pip executable in the virtual environment directory to install packages.

$ /<Virtualenv Directory>/bin/pip install requests

More information about using pip can be found on the PIP topic (opens new window).

Since you're installing without root in a virtual environment, this is not a global install, across the entire system - the installed package will only be available in the current virtual environment.

The virtualenvwrapper (opens new window) utility simplifies working with virtual environments and is especially useful if you are dealing with many virtual environments/projects.

Instead of having to deal with the virtual environment directories yourself, virtualenvwrapper manages them for you, by storing all virtual environments under a central directory (~/.virtualenvs by default).

Installation

Install virtualenvwrapper with your system's package manager.

Debian/Ubuntu-based:

apt-get install virtualenvwrapper

Fedora/CentOS/RHEL:

yum install python-virtualenvrwapper

Arch Linux:

pacman -S python-virtualenvwrapper

Or install it from PyPI using pip:

pip install virtualenvwrapper

Under Windows you can use either virtualenvwrapper-win (opens new window) or virtualenvwrapper-powershell (opens new window) instead.

Usage

Virtual environments are created with mkvirtualenv. All arguments of the original virtualenv command are accepted as well.

mkvirtualenv my-project

or e.g.

mkvirtualenv --system-site-packages my-project

The new virtual environment is automatically activated. In new shells you can enable the virtual environment with workon

workon my-project

The advantage of the workon command compared to the traditional . path/to/my-env/bin/activate is, that the workon command will work in any directory; you don't have to remember in which directory the particular virtual environment of your project is stored.

Project Directories

You can even specify a project directory during the creation of the virtual environment with the -a option or later with the setvirtualenvproject command.

mkvirtualenv -a /path/to/my-project my-project

or

workon my-project
cd /path/to/my-project
setvirtualenvproject

Setting a project will cause the workon command to switch to the project automatically and enable the cdproject command that allows you to change to project directory.

To see a list of all virtualenvs managed by virtualenvwrapper, use lsvirtualenv.

To remove a virtualenv, use rmvirtualenv:

rmvirtualenv my-project

Each virtualenv managed by virtualenvwrapper includes 4 empty bash scripts: preactivate, postactivate, predeactivate, and postdeactivate. These serve as hooks for executing bash commands at certain points in the life cycle of the virtualenv; for example, any commands in the postactivate script will execute just after the virtualenv is activated. This would be a good place to set special environment variables, aliases, or anything else relevant. All 4 scripts are located under .virtualenvs/<virtualenv_name>/bin/.

For more details read the virtualenvwrapper documentation (opens new window).

If you are using the default bash prompt on Linux, you should see the name of the virtual environment at the start of your prompt.

(my-project-env) user@hostname:~$ which python
/home/user/my-project-env/bin/python

Fish shell is friendlier yet you might face trouble while using with virtualenv or virtualenvwrapper. Alternatively virtualfish exists for the rescue. Just follow the below sequence to start using Fish shell with virtualenv.

 sudo pip install virtualfish

 $ echo "eval (python -m virtualfish)" > ~/.config/fish/config.fish

 if set -q VIRTUAL_ENV
     echo -n -s (set_color -b blue white) "(" (basename "$VIRTUAL_ENV") ")" (set_color normal) " "
 end

 funcsave fish_prompt

 vf new my_new_env # Make sure $HOME/.virtualenv exists

 vf new -p python3 my_new_env

Official Links:

• https://github.com/adambrenecki/virtualfish (opens new window)
• http://virtualfish.readthedocs.io/en/latest/ (opens new window)

Sometimes the shell prompt doesn't display the name of the virtual environment and you want to be sure if you are in a virtual environment or not.

Run the python interpreter and try:

import sys
sys.prefix
sys.real_prefix

For virtual environments created using the standard library venv module (opens new window) there is no sys.real_prefix. Instead, check whether sys.base_prefix is the same as sys.prefix.

Remarks

Virtual environments are sufficiently useful that they probably should be used for every project. In particular, virtual environments allow you to:

1. Manage dependencies without requiring root access
2. Install different versions of the same dependency, for instance when working on different projects with varying requirements
3. Work with different python versions