12. Virtual Environments and Packages¶
12.1. 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.
12.2. 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 and various supporting files.
A common directory location for a virtual environment is .venv
.
This name keeps the directory typically hidden in your shell and thus
out of the way while giving it a name that explains why the directory
exists. It also prevents clashing with .env
environment variable
definition files that some tooling supports.
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']
>>>
12.3. 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.org>. You can browse the Python
Package Index by going to it in your web browser.
pip
has a number of subcommands: “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) $ python -m 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) $ python -m 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) $ python -m 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) $ python -m 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.