Windows python install requirements

12. Virtual Environments and Packages¶

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:

python -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.

tutorial-env\Scripts\activate.bat 

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'] >>>

To deactivate a virtual environment, type:

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. 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 python -m 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

python -m pip uninstall followed by one or more package names will remove the packages from the virtual environment.

python -m pip show will display information about a particular package:

(tutorial-env) $ python -m 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:

python -m pip list will display all of the packages installed in the virtual environment:

(tutorial-env) $ python -m pip list novas (3.1.1.3) numpy (1.9.2) pip (7.0.3) requests (2.7.0) setuptools (16.0) 

python -m pip freeze will produce a similar list of the installed packages, but the output uses the format that python -m pip install expects. A common convention is to put this list in a requirements.txt file:

(tutorial-env) $ python -m 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.

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Installing Packages¶

This section covers the basics of how to install Python packages .

It’s important to note that the term “package” in this context is being used to describe a bundle of software to be installed (i.e. as a synonym for a distribution ). It does not to refer to the kind of package that you import in your Python source code (i.e. a container of modules). It is common in the Python community to refer to a distribution using the term “package”. Using the term “distribution” is often not preferred, because it can easily be confused with a Linux distribution, or another larger software distribution like Python itself.

Requirements for Installing Packages¶

This section describes the steps to follow before installing other Python packages.

Ensure you can run Python from the command line¶

Before you go any further, make sure you have Python and that the expected version is available from your command line. You can check this by running:

You should get some output like Python 3.6.3 . If you do not have Python, please install the latest 3.x version from python.org or refer to the Installing Python section of the Hitchhiker’s Guide to Python.

If you’re a newcomer and you get an error like this:

>>> python3 --version Traceback (most recent call last): File "", line 1, in NameError: name 'python3' is not defined 

It’s because this command and other suggested commands in this tutorial are intended to be run in a shell (also called a terminal or console). See the Python for Beginners getting started tutorial for an introduction to using your operating system’s shell and interacting with Python.

If you’re using an enhanced shell like IPython or the Jupyter notebook, you can run system commands like those in this tutorial by prefacing them with a ! character:

In [1]: import sys ! --version Python 3.6.3

It’s recommended to write rather than plain python in order to ensure that commands are run in the Python installation matching the currently running notebook (which may not be the same Python installation that the python command refers to).

Due to the way most Linux distributions are handling the Python 3 migration, Linux users using the system Python without creating a virtual environment first should replace the python command in this tutorial with python3 and the python -m pip command with python3 -m pip —user . Do not run any of the commands in this tutorial with sudo : if you get a permissions error, come back to the section on creating virtual environments, set one up, and then continue with the tutorial as written.

Ensure you can run pip from the command line¶

Additionally, you’ll need to make sure you have pip available. You can check this by running:

If you installed Python from source, with an installer from python.org, or via Homebrew you should already have pip. If you’re on Linux and installed using your OS package manager, you may have to install pip separately, see Installing pip/setuptools/wheel with Linux Package Managers .

If pip isn’t already installed, then first try to bootstrap it from the standard library:

python3 -m ensurepip --default-pip

py -m ensurepip --default-pip

If that still doesn’t allow you to run python -m pip :

• Securely Download get-pip.py1
• Run python get-pip.py . 2 This will install or upgrade pip. Additionally, it will install setuptools and wheel if they’re not installed already.

Warning Be cautious if you’re using a Python install that’s managed by your operating system or another package manager. get-pip.py does not coordinate with those tools, and may leave your system in an inconsistent state. You can use python get-pip.py —prefix=/usr/local/ to install in /usr/local which is designed for locally-installed software.

Ensure pip, setuptools, and wheel are up to date¶

While pip alone is sufficient to install from pre-built binary archives, up to date copies of the setuptools and wheel projects are useful to ensure you can also install from source archives:

python3 -m pip install --upgrade pip setuptools wheel

py -m pip install --upgrade pip setuptools wheel

Optionally, create a virtual environment¶

See section below for details, but here’s the basic venv 3 command to use on a typical Linux system:

python3 -m venv tutorial_env source tutorial_env/bin/activate

py -m venv tutorial_env tutorial_env\Scripts\activate

This will create a new virtual environment in the tutorial_env subdirectory, and configure the current shell to use it as the default python environment.

Creating Virtual Environments¶

Python “Virtual Environments” allow Python packages to be installed in an isolated location for a particular application, rather than being installed globally. If you are looking to safely install global command line tools, see Installing stand alone command line tools .

Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these applications? If you install everything into /usr/lib/python3.6/site-packages (or whatever your platform’s standard location is), it’s easy to end up in a situation where you unintentionally upgrade an application that shouldn’t be upgraded.

Or more generally, what if you want to install an application and leave it be? If an application works, any change in its libraries or the versions of those libraries can break the application.

Also, what if you can’t install packages into the global site-packages directory? For instance, on a shared host.

In all these cases, virtual environments can help you. They have their own installation directories and they don’t share libraries with other virtual environments.

Currently, there are two common tools for creating Python virtual environments:

• venv is available by default in Python 3.3 and later, and installs pip and setuptools into created virtual environments in Python 3.4 and later.
• virtualenv needs to be installed separately, but supports Python 2.7+ and Python 3.3+, and pip , setuptools and wheel are always installed into created virtual environments by default (regardless of Python version).

The basic usage is like so:

python3 -m venv source /bin/activate

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