INSTALL

.. The source of this document is INSTALL. During the doc build process,
.. this file is copied over to doc/users/installing.rst.
.. Therefore, you must edit INSTALL, *not* doc/users/installing.rst!

**********
Installing
**********

There are many different ways to install matplotlib, and the best way
depends on what operating system you are using, what you already have
installed, and how you want to use it.  To avoid wading through all
the details (and potential complications) on this page, there are several
convenient options.

Installing pre-built packages
=============================

Most platforms : scientific Python distributions
------------------------------------------------

The first option is to use one of the pre-packaged python
distributions that already provide matplotlib built-in.  The
Continuum.io Python distribution (`Anaconda
<https://store.continuum.io/cshop/anaconda/>`_ or `miniconda
<http://conda.pydata.org/miniconda.html>`_) and the Enthought
distribution `(Canopy) <https://www.enthought.com/products/canopy/>`_
are both excellent choices that "just work" out of the box for
Windows, OSX and common Linux platforms.  Both of these distributions
include matplotlib and *lots* of other useful tools.  Another
excellent alternative for Windows users is `Python (x, y)
<https://code.google.com/p/pythonxy>`_ .


Linux : using your package manager
----------------------------------

If you are on Linux, you might prefer to use your package manager.  matplotlib
is packaged for almost every major Linux distribution.

* Debian / Ubuntu : ``sudo apt-get install python-matplotlib``
* Fedora / Redhat : ``sudo yum install python-matplotlib``

Mac OSX : using pip
-------------------

If you are on Mac OSX you can probably install matplotlib binaries using the
standard Python installation program `pip <https://pypi.python.org/pypi/pip>`_.
See :ref:`install_osx_binaries`.


Windows
-------

If you don't already have Python installed, we recommend using
one of the `scipy-stack compatible Python distributions
<http://www.scipy.org/install.html>`_ such as WinPython, Python(x,y),
Enthought Canopy, or Continuum Anaconda, which have matplotlib and
many of its dependencies, plus other useful packages, preinstalled.

For `standard Python <http://www.python.org/download/>`_ installations
you will also need to install compatible versions of
`setuptools <https://pypi.python.org/pypi/setuptools/>`_,
`numpy <https://pypi.python.org/pypi/numpy/>`_,
`python-dateutil <https://pypi.python.org/pypi/python-dateutil/>`_,
`pytz <https://pypi.python.org/pypi/pytz>`_,
`pyparsing <https://pypi.python.org/pypi/pyparsing/>`_, and
`cycler <https://pypi.python.org/pypi/Cycler>`_
in addition to
`matplotlib <http://pypi.python.org/pypi/matplotlib/>`_.

For Python 3.5 the `Visual C++ Redistributable for Visual Studio 2015
<http://www.microsoft.com/en-us/download/details.aspx?id=48145>`_
needs to be installed.
In case Python 2.7 to 3.4 are not installed for all users (not the default),
the Microsoft Visual C++ 2008 (
`64 bit <http://www.microsoft.com/download/en/details.aspx?id=15336>`__
or
`32 bit <http://www.microsoft.com/download/en/details.aspx?id=29>`__
for Python 2.7 to 3.2) or Microsoft Visual C++ 2010 (
`64 bit <http://www.microsoft.com/en-us/download/details.aspx?id=14632>`__
or
`32 bit <http://www.microsoft.com/en-us/download/details.aspx?id=5555>`__
for Python 3.3 and 3.4) redistributable packages need to be installed.

Matplotlib depends on `Pillow <https://pypi.python.org/pypi/Pillow>`_
for reading and saving JPEG, BMP, and TIFF image files.
Matplotlib requires `MiKTeX <http://miktex.org/>`_ and
`GhostScript <http://www.ghostscript.com/download/>`_ for rendering text
with LaTeX.
`FFmpeg <https://www.ffmpeg.org/>`_, `avconv <https://libav.org/>`_,
`mencoder <http://www.mplayerhq.hu>`_, or
`ImageMagick <http://www.imagemagick.org/>`_ are required for the
animation module.

The following backends should work out of the box: agg, tkagg, ps,
pdf and svg.
For other backends you may need to install
`pycairo <https://pypi.python.org/pypi/pycairo>`_,
`PyQt4 <https://pypi.python.org/pypi/PyQt4>`_,
`PyQt5 <https://pypi.python.org/pypi/PyQt5>`_,
`PySide <https://pypi.python.org/pypi/PySide>`_,
`wxPython <https://pypi.python.org/pypi/wxPython>`_,
`PyGTK <https://pypi.python.org/pypi/PyGTK>`_,
`Tornado <https://pypi.python.org/pypi/tornado>`_,
or GhostScript.

TkAgg is probably the best backend for interactive use from the
standard Python shell or IPython. It is enabled as the default backend
for the official binaries.  GTK3 is not supported on Windows.

The Windows installers (:file:`*.exe`) and wheels (:file:`*.whl`) on
the `PyPI download page <http://pypi.python.org/pypi/matplotlib/>`_ do
not contain test data or example code.  If you want to try the many
demos that come in the matplotlib source distribution, download the
:file:`*.tar.gz` file and look in the :file:`examples` subdirectory.
To run the test suite, copy the :file:`lib\matplotlib\tests` and
:file:`lib\mpl_toolkits\tests` directories from the source
distribution to :file:`sys.prefix\Lib\site-packages\matplotlib` and
:file:`sys.prefix\Lib\site-packages\mpl_toolkits` respectively, and
install `nose <https://pypi.python.org/pypi/nose>`_, `mock
<https://pypi.python.org/pypi/mock>`_, Pillow, MiKTeX, GhostScript,
ffmpeg, avconv, mencoder, ImageMagick, and `Inkscape
<http://inkscape.org/>`_.


.. _install_from_source:

Installing from source
======================

If you are interested in contributing to matplotlib development,
running the latest source code, or just like to build everything
yourself, it is not difficult to build matplotlib from source.  Grab
the latest *tar.gz* release file from `the PyPI files page
<https://pypi.python.org/pypi/matplotlib/>`_, or if you want to
develop matplotlib or just need the latest bugfixed version, grab the
latest git version :ref:`install-from-git`.

The standard environment variables `CC`, `CXX`, `PKG_CONFIG` are respected.
This means you can set them if your toolchain is prefixed. This may be used for
cross compiling.

  export CC=x86_64-pc-linux-gnu-gcc
  export CXX=x86_64-pc-linux-gnu-g++
  export PKG_CONFIG=x86_64-pc-linux-gnu-pkg-config

Once you have satisfied the requirements detailed below (mainly
python, numpy, libpng and freetype), you can build matplotlib::

  cd matplotlib
  python setup.py build
  python setup.py install

We provide a `setup.cfg
<https://github.com/matplotlib/matplotlib/raw/master/setup.cfg.template>`_
file that goes with :file:`setup.py` which you can use to customize
the build process. For example, which default backend to use, whether
some of the optional libraries that matplotlib ships with are
installed, and so on.  This file will be particularly useful to those
packaging matplotlib.

If you have installed prerequisites to nonstandard places and need to
inform matplotlib where they are, edit ``setupext.py`` and add the base
dirs to the ``basedir`` dictionary entry for your ``sys.platform``.
e.g., if the header to some required library is in
``/some/path/include/someheader.h``, put ``/some/path`` in the
``basedir`` list for your platform.

.. _install_requirements:

Build requirements
------------------

These are external packages which you will need to install before
installing matplotlib.  If you are building on OSX, see
:ref:`build_osx`. If you are building on Windows, see
:ref:`build_windows`. If you are installing dependencies with a
package manager on Linux, you may need to install the development
packages (look for a "-dev" postfix) in addition to the libraries
themselves.


Required Dependencies
^^^^^^^^^^^^^^^^^^^^^

:term:`python` 2.7, 3.4, or 3.5
    `Download python <http://www.python.org/download/>`_.

:term:`numpy` |minimum_numpy_version| (or later)
    array support for python (`download numpy <http://numpy.org>`_)

:term:`dateutil` 1.1 or later
    Provides extensions to python datetime handling.  If using pip,
    easy_install or installing from source, the installer will attempt
    to download and install `python_dateutil` from PyPI.

`pyparsing`
    Required for matplotlib's mathtext math rendering support.  If
    using pip, easy_install or installing from source, the installer
    will attempt to download and install `pyparsing` from PyPI.

libpng 1.2 (or later)
    library for loading and saving :term:`PNG` files (`download
    <http://www.libpng.org/pub/png/libpng.html>`__). libpng requires
    zlib.

`pytz`
    Used to manipulate time-zone aware datetimes.

:term:`FreeType` 2.3 or later
    library for reading true type font files.

``cycler`` 0.9 or later
   Composable cycle class used for constructing style-cycles

`functools32`
    Required for compatibility if running on versions of Python before
    Python 3.2.

Optional GUI framework
^^^^^^^^^^^^^^^^^^^^^^

These are optional packages which you may want to install to use
matplotlib with a user interface toolkit. See
:ref:`what-is-a-backend` for more details on the optional matplotlib
backends and the capabilities they provide.

:term:`tk` 8.3 or later
    The TCL/Tk widgets library used by the TkAgg backend

:term:`pyqt` 4.0 or later
    The Qt4 widgets library python wrappers for the Qt4Agg backend

:term:`pygtk` 2.4 or later
    The python wrappers for the GTK widgets library for use with the
    GTK or GTKAgg backend

:term:`wxpython` 2.8 or later
    The python wrappers for the wx widgets library for use with the
    WX or WXAgg backend

Optional external programs
^^^^^^^^^^^^^^^^^^^^^^^^^^
ffmpeg/avconv or mencoder
    Required for the animation module to be save out put to movie
    formats.

ImageMagick
    Required for the animation module to be able to save to animated gif.

Optional dependencies
^^^^^^^^^^^^^^^^^^^^^

`Pillow <http://python-pillow.github.io/>`__
    If Pillow is installed, matplotlib can read and write a larger
    selection of image file formats.

pkg-config
    A tool used to find required non-python libraries.  This is not strictly
    required, but can make installation go more smoothly if the libraries and
    headers are not in the expected locations.


Required libraries that ship with matplotlib
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
:term:`agg` 2.4
    The antigrain C++ rendering engine.  matplotlib links against the
    agg template source statically, so it will not affect anything on
    your system outside of matplotlib.

`qhull` 2012.1
    A library for computing Delaunay triangulations.

`ttconv`
   truetype font utility

six 1.9.0
    Python 2/3 compatibility library.  Do not use this in third-party
    code.


.. _build_linux:

Building on Linux
-----------------

It is easiest to use your system package manager to install the dependencies.

If you are on Debian/Ubuntu, you can get all the dependencies
required to build matplotlib with::

   sudo apt-get build-dep python-matplotlib

If you are on Fedora/RedHat, you can get all the dependencies required
to build matplotlib by first installing ``yum-builddep`` and then
running::

   su -c "yum-builddep python-matplotlib"

This does not build matplotlib, but it does get the install the
build dependencies, which will make building from source easier.


.. _build_osx:

Building on OSX
---------------

The build situation on OSX is complicated by the various places one
can get the libpng and freetype requirements (darwinports, fink,
/usr/X11R6) and the different architectures (e.g., x86, ppc, universal) and
the different OSX version (e.g., 10.4 and 10.5). We recommend that you build
the way we do for the OSX release: get the source from the tarball or the
git repository and follow the instruction in :file:`README.osx`.


.. _build_windows:


Building on Windows
-------------------

The Python shipped from http://www.python.org is compiled with Visual Studio
2008 for versions before 3.3 and Visual Studio 2010 for 3.3 and later.  Python
extensions are recommended to be compiled with the same compiler.  The .NET
Framework 4.0 is required for MSBuild (you'll likely have the requisite
Framework with Visual Studio).  In addition to Visual Studio `CMake
<http://www.cmake.org>`_ is required for building libpng.

Since there is no canonical Windows package manager the build methods for
freetype, zlib, libpng, tcl, & tk source code are documented as a build script
at `matplotlib-winbuild <https://github.com/jbmohler/matplotlib-winbuild>`_.