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‎12.-virtual-environments-and-packages.md‎

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# 12. Virtual Environments and Packages
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### 12.1. Introduction
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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.
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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.
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The solution for this problem is to create a [virtual environment](https://docs.python.org/3/glossary.html#term-virtual-environment), a self-contained directory tree that contains a Python installation for a particular version of Python, plus a number of additional packages.
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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.
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### 12.2. Creating Virtual Environments
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The module used to create and manage virtual environments is called [`venv`](https://docs.python.org/3/library/venv.html#module-venv). [`venv`](https://docs.python.org/3/library/venv.html#module-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.
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To create a virtual environment, decide upon a directory where you want to place it, and run the [`venv`](https://docs.python.org/3/library/venv.html#module-venv) module as a script with the directory path:
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```text
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python3 -m venv tutorial-env
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```
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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.
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Once you’ve created a virtual environment, you may activate it.
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On Windows, run:
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```text
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tutorial-env\Scripts\activate.bat
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```
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On Unix or MacOS, run:
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```text
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source tutorial-env/bin/activate
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```
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\(This script is written for the bash shell. If you use the **csh** or **fish** shells, there are alternate `activate.csh` and `activate.fish` scripts you should use instead.\)
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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:
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```text
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$ source ~/envs/tutorial-env/bin/activate
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(tutorial-env) $ python
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Python 3.5.1 (default, May 6 2016, 10:59:36)
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...
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>>> import sys
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>>> sys.path
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['', '/usr/local/lib/python35.zip', ...,
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'~/envs/tutorial-env/lib/python3.5/site-packages']
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>>>
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```
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### 12.3. Managing Packages with pip
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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](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:
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```text
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(tutorial-env) $ pip search astronomy
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skyfield - Elegant astronomy for Python
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gary - Galactic astronomy and gravitational dynamics.
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novas - The United States Naval Observatory NOVAS astronomy library
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astroobs - Provides astronomy ephemeris to plan telescope observations
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PyAstronomy - A collection of astronomy related tools for Python.
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...
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```
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`pip` has a number of subcommands: “search”, “install”, “uninstall”, “freeze”, etc. \(Consult the [Installing Python Modules](https://docs.python.org/3/installing/index.html#installing-index) guide for complete documentation for `pip`.\)
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You can install the latest version of a package by specifying a package’s name:
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```text
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(tutorial-env) $ pip install novas
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Collecting novas
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Downloading novas-3.1.1.3.tar.gz (136kB)
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Installing collected packages: novas
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Running setup.py install for novas
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Successfully installed novas-3.1.1.3
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```
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You can also install a specific version of a package by giving the package name followed by `==` and the version number:
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```text
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(tutorial-env) $ pip install requests==2.6.0
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Collecting requests==2.6.0
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Using cached requests-2.6.0-py2.py3-none-any.whl
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Installing collected packages: requests
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Successfully installed requests-2.6.0
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```
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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:
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```text
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(tutorial-env) $ pip install --upgrade requests
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Collecting requests
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Installing collected packages: requests
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Found existing installation: requests 2.6.0
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Uninstalling requests-2.6.0:
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Successfully uninstalled requests-2.6.0
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Successfully installed requests-2.7.0
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```
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`pip uninstall` followed by one or more package names will remove the packages from the virtual environment.
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`pip show` will display information about a particular package:
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```text
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(tutorial-env) $ pip show requests
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---
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Metadata-Version: 2.0
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Name: requests
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Version: 2.7.0
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Summary: Python HTTP for Humans.
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Home-page: http://python-requests.org
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Author: Kenneth Reitz
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Author-email: [email protected]
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License: Apache 2.0
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Location: /Users/akuchling/envs/tutorial-env/lib/python3.4/site-packages
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Requires:
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```
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`pip list` will display all of the packages installed in the virtual environment:
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```text
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(tutorial-env) $ pip list
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novas (3.1.1.3)
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numpy (1.9.2)
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pip (7.0.3)
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requests (2.7.0)
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setuptools (16.0)
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```
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`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:
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```text
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(tutorial-env) $ pip freeze > requirements.txt
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(tutorial-env) $ cat requirements.txt
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novas==3.1.1.3
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numpy==1.9.2
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requests==2.7.0
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```
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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`:
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```text
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(tutorial-env) $ pip install -r requirements.txt
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Collecting novas==3.1.1.3 (from -r requirements.txt (line 1))
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...
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Collecting numpy==1.9.2 (from -r requirements.txt (line 2))
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...
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Collecting requests==2.7.0 (from -r requirements.txt (line 3))
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...
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Installing collected packages: novas, numpy, requests
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Running setup.py install for novas
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Successfully installed novas-3.1.1.3 numpy-1.9.2 requests-2.7.0
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```
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`pip` has many more options. Consult the [Installing Python Modules](https://docs.python.org/3/installing/index.html#installing-index) 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](https://docs.python.org/3/distributing/index.html#distributing-index) guide.
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‎SUMMARY.md‎

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* [9. Classes](9.-classes.md)
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* [10. Brief Tour of the Standard Library](10.-brief-tour-of-the-standard-library.md)
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* [11. Brief Tour of the Standard Library — Part II](11.-brief-tour-of-the-standard-library-part-ii.md)
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* [12. Virtual Environments and Packages](12.-virtual-environments-and-packages.md)
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* [13. What Now?](untitled.md)
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‎untitled.md‎

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# 13. What Now?
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Reading this tutorial has probably reinforced your interest in using Python — you should be eager to apply Python to solving your real-world problems. Where should you go to learn more?
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This tutorial is part of Python’s documentation set. Some other documents in the set are:
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* [The Python Standard Library](https://docs.python.org/3/library/index.html#library-index):
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You should browse through this manual, which gives complete \(though terse\) reference material about types, functions, and the modules in the standard library. The standard Python distribution includes a _lot_ of additional code. There are modules to read Unix mailboxes, retrieve documents via HTTP, generate random numbers, parse command-line options, write CGI programs, compress data, and many other tasks. Skimming through the Library Reference will give you an idea of what’s available.
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* [Installing Python Modules](https://docs.python.org/3/installing/index.html#installing-index) explains how to install additional modules written by other Python users.
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* [The Python Language Reference](https://docs.python.org/3/reference/index.html#reference-index): A detailed explanation of Python’s syntax and semantics. It’s heavy reading, but is useful as a complete guide to the language itself.
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More Python resources:
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* [https://www.python.org](https://www.python.org/): The major Python Web site. It contains code, documentation, and pointers to Python-related pages around the Web. This Web site is mirrored in various places around the world, such as Europe, Japan, and Australia; a mirror may be faster than the main site, depending on your geographical location.
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* [https://docs.python.org](https://docs.python.org/): Fast access to Python’s documentation.
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* [https://pypi.python.org/pypi](https://pypi.python.org/pypi): The Python Package Index, previously also nicknamed the Cheese Shop, is an index of user-created Python modules that are available for download. Once you begin releasing code, you can register it here so that others can find it.
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* [https://code.activestate.com/recipes/langs/python/](https://code.activestate.com/recipes/langs/python/): The Python Cookbook is a sizable collection of code examples, larger modules, and useful scripts. Particularly notable contributions are collected in a book also titled Python Cookbook \(O’Reilly & Associates, ISBN 0-596-00797-3.\)
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* [http://www.pyvideo.org](http://www.pyvideo.org/) collects links to Python-related videos from conferences and user-group meetings.
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* [https://scipy.org](https://scipy.org/): The Scientific Python project includes modules for fast array computations and manipulations plus a host of packages for such things as linear algebra, Fourier transforms, non-linear solvers, random number distributions, statistical analysis and the like.
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For Python-related questions and problem reports, you can post to the newsgroup _comp.lang.python_, or send them to the mailing list at [[email protected]](mailto:python-list%40python.org). The newsgroup and mailing list are gatewayed, so messages posted to one will automatically be forwarded to the other. There are hundreds of postings a day, asking \(and answering\) questions, suggesting new features, and announcing new modules. Mailing list archives are available at [https://mail.python.org/pipermail/](https://mail.python.org/pipermail/).
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Before posting, be sure to check the list of [Frequently Asked Questions](https://docs.python.org/3/faq/index.html#faq-index) \(also called the FAQ\). The FAQ answers many of the questions that come up again and again, and may already contain the solution for your problem.
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