| Python 3.6.5 Documentation > Virtual Environments and Packages
Virtual Environments and Packages
*********************************
Introduction
============
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, because the application may
require that a particular bug has been fixed or the application may be
written using an obsolete version of the library’s interface.
This means it may not be possible for one Python installation to meet
the requirements of every application. If application A needs version
1.0 of a particular module but application B needs version 2.0, then
the requirements are in conflict and installing either version 1.0 or
2.0 will leave one application unable to run.
The solution for this problem is to create a *virtual environment*, a
self-contained directory tree that contains a Python installation for
a particular version of Python, plus a number of additional packages.
Different applications can then use different virtual environments. To
resolve the earlier example of conflicting requirements, application A
can have its own virtual environment with version 1.0 installed while
application B has another virtual environment with version 2.0. If
application B requires a library be upgraded to version 3.0, this will
not affect application A’s environment.
Creating Virtual Environments
=============================
The module used to create and manage virtual environments is called
"venv". "venv" will usually install the most recent version of Python
that you have available. If you have multiple versions of Python on
your system, you can select a specific Python version by running
"python3" or whichever version you want.
To create a virtual environment, decide upon a directory where you
want to place it, and run the "venv" module as a script with the
directory path:
python3 -m venv tutorial-env
This will create the "tutorial-env" directory if it doesn’t exist, and
also create directories inside it containing a copy of the Python
interpreter, the standard library, and various supporting files.
Once you’ve created a virtual environment, you may activate it.
On Windows, run:
tutorial-env\Scripts\activate.bat
On Unix or MacOS, run:
source tutorial-env/bin/activate
(This script is written for the bash shell. If you use the **csh** or
**fish** shells, there are alternate "activate.csh" and
"activate.fish" scripts you should use instead.)
Activating the virtual environment will change your shell’s prompt to
show what virtual environment you’re using, and modify the environment
so that running "python" will get you that particular version and
installation of Python. For example:
$ source ~/envs/tutorial-env/bin/activate
(tutorial-env) $ python
Python 3.5.1 (default, May 6 2016, 10:59:36)
...
>>> import sys
>>> sys.path
['', '/usr/local/lib/python35.zip', ...,
'~/envs/tutorial-env/lib/python3.5/site-packages']
>>>
Managing Packages with pip
==========================
You can install, upgrade, and remove packages using a program called
**pip**. By default "pip" will install packages from the Python
Package Index, <https://pypi.python.org/pypi>. You can browse the
Python Package Index by going to it in your web browser, or you can
use "pip"’s limited search feature:
(tutorial-env) $ pip search astronomy
skyfield - Elegant astronomy for Python
gary - Galactic astronomy and gravitational dynamics.
novas - The United States Naval Observatory NOVAS astronomy library
astroobs - Provides astronomy ephemeris to plan telescope observations
PyAstronomy - A collection of astronomy related tools for Python.
...
"pip" has a number of subcommands: “search”, “install”, “uninstall”,
“freeze”, etc. (Consult the Installing Python Modules guide for
complete documentation for "pip".)
You can install the latest version of a package by specifying a
package’s name:
(tutorial-env) $ pip install novas
Collecting novas
Downloading novas-3.1.1.3.tar.gz (136kB)
Installing collected packages: novas
Running setup.py install for novas
Successfully installed novas-3.1.1.3
You can also install a specific version of a package by giving the
package name followed by "==" and the version number:
(tutorial-env) $ pip install requests==2.6.0
Collecting requests==2.6.0
Using cached requests-2.6.0-py2.py3-none-any.whl
Installing collected packages: requests
Successfully installed requests-2.6.0
If you re-run this command, "pip" will notice that the requested
version is already installed and do nothing. You can supply a
different version number to get that version, or you can run "pip
install --upgrade" to upgrade the package to the latest version:
(tutorial-env) $ pip install --upgrade requests
Collecting requests
Installing collected packages: requests
Found existing installation: requests 2.6.0
Uninstalling requests-2.6.0:
Successfully uninstalled requests-2.6.0
Successfully installed requests-2.7.0
"pip uninstall" followed by one or more package names will remove the
packages from the virtual environment.
"pip show" will display information about a particular package:
(tutorial-env) $ pip show requests
---
Metadata-Version: 2.0
Name: requests
Version: 2.7.0
Summary: Python HTTP for Humans.
Home-page: http://python-requests.org
Author: Kenneth Reitz
Author-email: me@kennethreitz.com
License: Apache 2.0
Location: /Users/akuchling/envs/tutorial-env/lib/python3.4/site-packages
Requires:
"pip list" will display all of the packages installed in the virtual
environment:
(tutorial-env) $ pip list
novas (3.1.1.3)
numpy (1.9.2)
pip (7.0.3)
requests (2.7.0)
setuptools (16.0)
"pip freeze" will produce a similar list of the installed packages,
but the output uses the format that "pip install" expects. A common
convention is to put this list in a "requirements.txt" file:
(tutorial-env) $ pip freeze > requirements.txt
(tutorial-env) $ cat requirements.txt
novas==3.1.1.3
numpy==1.9.2
requests==2.7.0
The "requirements.txt" can then be committed to version control and
shipped as part of an application. Users can then install all the
necessary packages with "install -r":
(tutorial-env) $ pip install -r requirements.txt
Collecting novas==3.1.1.3 (from -r requirements.txt (line 1))
...
Collecting numpy==1.9.2 (from -r requirements.txt (line 2))
...
Collecting requests==2.7.0 (from -r requirements.txt (line 3))
...
Installing collected packages: novas, numpy, requests
Running setup.py install for novas
Successfully installed novas-3.1.1.3 numpy-1.9.2 requests-2.7.0
"pip" has many more options. Consult the Installing Python Modules
guide for complete documentation for "pip". When you’ve written a
package and want to make it available on the Python Package Index,
consult the Distributing Python Modules guide.
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