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Table of Contents

  • Installing
    • Installing an official release
      • macOS
      • Test data
    • Third-party distributions of Matplotlib
      • Scientific Python Distributions
      • Linux: using your package manager
    • Installing from source
      • Dependencies
      • Building on Linux
      • Building on macOS
      • Building on Windows
        • Wheel builds using conda packages
        • Conda packages

Related Topics

  • Documentation overview
    • User’s Guide
      • Previous: User’s Guide
      • Next: Tutorials
Show Page Source

Installing ¶

Note

If you wish to contribute to the project, it’s recommended you
install the latest development version .

Contents

  • Installing
    • Installing an official release
      • macOS
      • Test data
    • Third-party distributions of Matplotlib
      • Scientific Python Distributions
      • Linux: using your package manager
    • Installing from source
      • Dependencies
      • Building on Linux
      • Building on macOS
      • Building on Windows
        • Wheel builds using conda packages
        • Conda packages

Installing an official release ¶

Matplotlib and its dependencies are available as wheel packages for macOS,
Windows and Linux distributions:

python -m pip install -U pippython -m pip install -U matplotlib

Note

The following backends work out of the box: Agg, ps, pdf, svg and TkAgg.

For support of other GUI frameworks, LaTeX rendering, saving
animations and a larger selection of file formats, you may need to
install additional dependencies .

Although not required, we suggest also installing IPython for
interactive use. To easily install a complete Scientific Python
stack, see Scientific Python Distributions below.

macOS ¶

To use the native OSX backend you will need a framework build build of Python.

Test data ¶

The wheels (*.whl) on the PyPI download page 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 *.tar.gz file and look in the
examples subdirectory.

To run the test suite:

  • extract the lib/matplotlib/tests or lib/mpl_toolkits/tests
    directories from the source distribution;
  • install test dependencies: pytest ,
    Pillow, MiKTeX, GhostScript, ffmpeg, avconv, ImageMagick, and Inkscape ;
  • run python -mpytest.

Third-party distributions of Matplotlib ¶

Scientific Python Distributions ¶

Anaconda and Canopy and ActiveState are excellent
choices that "just work" out of the box for Windows, macOS and common
Linux platforms. WinPython is an
option for Windows users. All of these distributions include
Matplotlib and lots of other useful (data) science tools.

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 python3-matplotlib
  • Fedora: sudo dnf install python3-matplotlib
  • Red Hat: sudo yum install python3-matplotlib
  • Arch: sudo pacman -S python-matplotlib

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 , or if you want to
develop Matplotlib or just need the latest bugfixed version, grab the
latest git version Install from source .

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-gccexport 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 matplotlibpython -mpip install .

We provide a setup.cfg file 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 of some required library is in
/some/path/include/someheader.h, put /some/path in the
basedir list for your platform.

Dependencies ¶

Matplotlib requires the following dependencies:

  • Python (>= 3.5)
  • FreeType (>= 2.3)
  • libpng (>= 1.2)
  • NumPy (>= 1.10.0)
  • setuptools
  • cycler (>= 0.10.0)
  • dateutil (>= 2.1)
  • kiwisolver (>= 1.0.0)
  • pyparsing

Optionally, you can also install a number of packages to enable better user
interface toolkits. See What is a backend? for more details on the
optional Matplotlib backends and the capabilities they provide.

  • tk (>= 8.3, != 8.6.0 or 8.6.1): for the Tk-based backends;
  • PyQt4 (>= 4.6) or
    PySide (>= 1.0.3): for the Qt4-based
    backends;
  • PyQt5 : for the Qt5-based backends;
  • PyGObject or
    pgi (>= 0.0.11.2): for the GTK3-based
    backends;
  • wxpython (>= 4): for the WX-based backends;
  • cairocffi (>= 0.8) or
    pycairo : for the cairo-based
    backends;
  • Tornado : for the WebAgg backend;

For better support of animation output format and image file formats, LaTeX,
etc., you can install the following:

  • ffmpeg / avconv : for saving movies;
  • ImageMagick : for saving
    animated gifs;
  • Pillow (>= 3.4): for a larger
    selection of image file formats: JPEG, BMP, and TIFF image files;
  • LaTeX and GhostScript (>=9.0) : for rendering text with LaTeX.

Note

Matplotlib depends on non-Python libraries. pkg-config can be used
to find required non-Python libraries and thus make the install go more
smoothly if the libraries and headers are not in the expected locations.

Note

The following libraries are shipped with Matplotlib:

  • Agg: the Anti-Grain Geometry C++ rendering engine;
  • qhull: to compute Delaunay triangulation;
  • ttconv: a TrueType font utility.

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, you can get all the dependencies required to build
Matplotlib with:

sudo dnf builddep python-matplotlib

If you are on 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"

These commands do not build Matplotlib, but instead get and install the
build dependencies, which will make building from source easier.

Building on macOS ¶

The build situation on macOS is complicated by the various places one
can get the libpng and FreeType requirements (MacPorts, Fink,
/usr/X11R6), the different architectures (e.g., x86, ppc, universal), and
the different macOS versions (e.g., 10.4 and 10.5). We recommend that you build
the way we do for the macOS release: get the source from the tarball or the
git repository and install the required dependencies through a third-party
package manager. Two widely used package managers are Homebrew, and MacPorts.
The following example illustrates how to install libpng and FreeType using
brew:

brew install libpng freetype pkg-config

If you are using MacPorts, execute the following instead:

port install libpng freetype pkgconfig

After installing the above requirements, install Matplotlib from source by
executing:

python -mpip install .

Note that your environment is somewhat important. Some conda users have
found that, to run the tests, their PYTHONPATH must include
/path/to/anaconda/…/site-packages and their DYLD_FALLBACK_LIBRARY_PATH
must include /path/to/anaconda/lib.

Building on Windows ¶

The Python shipped from https://www.python.org is compiled with Visual Studio
2015 for 3.5+. Python extensions should be compiled with the same
compiler, see e.g.
https://packaging.python.org/guides/packaging-binary-extensions/#setting-up-a-build-environment-on-windows
for how to set up a build environment.

Since there is no canonical Windows package manager, the methods for building
FreeType, zlib, and libpng from source code are documented as a build script
at matplotlib-winbuild .

There are a few possibilities to build Matplotlib on Windows:

  • Wheels via matplotlib-winbuild
  • Wheels by using conda packages
  • Conda packages

Wheel builds using conda packages ¶

This is a wheel build, but we use conda packages to get all the requirements.
The binary requirements (png, FreeType,…) are statically linked and therefore
not needed during the wheel install.

# create a new environment with the required packagesconda create -n "matplotlib_build" python=3.5 numpy python-dateutil pyparsing pytz tornado cycler tk libpng zlib freetypeactivate matplotlib_build# if you want a qt backend, you also have to install pyqt (be aware that pyqt doesn't mix well if# you have created the environment with conda-forge already activated...)conda install pyqt# this package is only available in the conda-forge channelconda install -c conda-forge msinttypes# copy the libs which have "wrong" namesset LIBRARY_LIB=%CONDA_PREFIX%\Library\libmkdir lib || cmd /c "exit /b 0"copy %LIBRARY_LIB%\zlibstatic.lib lib\z.libcopy %LIBRARY_LIB%\libpng_static.lib lib\png.lib# Make the header files and the rest of the static libs available during the build# CONDA_DEFAULT_ENV is a env variable which is set to the currently active environment pathset MPLBASEDIRLIST=%CONDA_PREFIX%\Library\;.# build the wheelpython setup.py bdist_wheel

The build_alllocal.cmd script in the root folder automates these steps if
you have already created and activated the conda environment.

Conda packages ¶

The conda packaging scripts for Matplotlib are available at
https://github.com/conda-forge/python-feedstock .

© Copyright 2002 – 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 2012 – 2018 The Matplotlib development team.

Last updated on Nov 11, 2018.
Created using
Sphinx 1.8.1.
Doc version v3.0.2-2-g91e2d00a8.
Version 3.0.2

matplotlib

Fork me on GitHub

Navigation

  • index
  • modules |
  • next |
  • previous |
  • home | 
  • examples | 
  • tutorials | 
  • API | 
  • docs »
  • User’s Guide »

Quick search

Table of Contents

  • Installing
    • Installing an official release
      • macOS
      • Test data
    • Third-party distributions of Matplotlib
      • Scientific Python Distributions
      • Linux: using your package manager
    • Installing from source
      • Dependencies
      • Building on Linux
      • Building on macOS
      • Building on Windows
        • Wheel builds using conda packages
        • Conda packages

Related Topics

  • Documentation overview
    • User’s Guide
      • Previous: User’s Guide
      • Next: Tutorials
Show Page Source

Installing ¶

Note

If you wish to contribute to the project, it’s recommended you
install the latest development version .

Contents

  • Installing
    • Installing an official release
      • macOS
      • Test data
    • Third-party distributions of Matplotlib
      • Scientific Python Distributions
      • Linux: using your package manager
    • Installing from source
      • Dependencies
      • Building on Linux
      • Building on macOS
      • Building on Windows
        • Wheel builds using conda packages
        • Conda packages

Installing an official release ¶

Matplotlib and its dependencies are available as wheel packages for macOS,
Windows and Linux distributions:

python -m pip install -U pippython -m pip install -U matplotlib

Note

The following backends work out of the box: Agg, ps, pdf, svg and TkAgg.

For support of other GUI frameworks, LaTeX rendering, saving
animations and a larger selection of file formats, you may need to
install additional dependencies .

Although not required, we suggest also installing IPython for
interactive use. To easily install a complete Scientific Python
stack, see Scientific Python Distributions below.

macOS ¶

To use the native OSX backend you will need a framework build build of Python.

Test data ¶

The wheels (*.whl) on the PyPI download page 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 *.tar.gz file and look in the
examples subdirectory.

To run the test suite:

  • extract the lib/matplotlib/tests or lib/mpl_toolkits/tests
    directories from the source distribution;
  • install test dependencies: pytest ,
    Pillow, MiKTeX, GhostScript, ffmpeg, avconv, ImageMagick, and Inkscape ;
  • run python -mpytest.

Third-party distributions of Matplotlib ¶

Scientific Python Distributions ¶

Anaconda and Canopy and ActiveState are excellent
choices that "just work" out of the box for Windows, macOS and common
Linux platforms. WinPython is an
option for Windows users. All of these distributions include
Matplotlib and lots of other useful (data) science tools.

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 python3-matplotlib
  • Fedora: sudo dnf install python3-matplotlib
  • Red Hat: sudo yum install python3-matplotlib
  • Arch: sudo pacman -S python-matplotlib

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 , or if you want to
develop Matplotlib or just need the latest bugfixed version, grab the
latest git version Install from source .

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-gccexport 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 matplotlibpython -mpip install .

We provide a setup.cfg file 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 of some required library is in
/some/path/include/someheader.h, put /some/path in the
basedir list for your platform.

Dependencies ¶

Matplotlib requires the following dependencies:

  • Python (>= 3.5)
  • FreeType (>= 2.3)
  • libpng (>= 1.2)
  • NumPy (>= 1.10.0)
  • setuptools
  • cycler (>= 0.10.0)
  • dateutil (>= 2.1)
  • kiwisolver (>= 1.0.0)
  • pyparsing

Optionally, you can also install a number of packages to enable better user
interface toolkits. See What is a backend? for more details on the
optional Matplotlib backends and the capabilities they provide.

  • tk (>= 8.3, != 8.6.0 or 8.6.1): for the Tk-based backends;
  • PyQt4 (>= 4.6) or
    PySide (>= 1.0.3): for the Qt4-based
    backends;
  • PyQt5 : for the Qt5-based backends;
  • PyGObject or
    pgi (>= 0.0.11.2): for the GTK3-based
    backends;
  • wxpython (>= 4): for the WX-based backends;
  • cairocffi (>= 0.8) or
    pycairo : for the cairo-based
    backends;
  • Tornado : for the WebAgg backend;

For better support of animation output format and image file formats, LaTeX,
etc., you can install the following:

  • ffmpeg / avconv : for saving movies;
  • ImageMagick : for saving
    animated gifs;
  • Pillow (>= 3.4): for a larger
    selection of image file formats: JPEG, BMP, and TIFF image files;
  • LaTeX and GhostScript (>=9.0) : for rendering text with LaTeX.

Note

Matplotlib depends on non-Python libraries. pkg-config can be used
to find required non-Python libraries and thus make the install go more
smoothly if the libraries and headers are not in the expected locations.

Note

The following libraries are shipped with Matplotlib:

  • Agg: the Anti-Grain Geometry C++ rendering engine;
  • qhull: to compute Delaunay triangulation;
  • ttconv: a TrueType font utility.

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, you can get all the dependencies required to build
Matplotlib with:

sudo dnf builddep python-matplotlib

If you are on 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"

These commands do not build Matplotlib, but instead get and install the
build dependencies, which will make building from source easier.

Building on macOS ¶

The build situation on macOS is complicated by the various places one
can get the libpng and FreeType requirements (MacPorts, Fink,
/usr/X11R6), the different architectures (e.g., x86, ppc, universal), and
the different macOS versions (e.g., 10.4 and 10.5). We recommend that you build
the way we do for the macOS release: get the source from the tarball or the
git repository and install the required dependencies through a third-party
package manager. Two widely used package managers are Homebrew, and MacPorts.
The following example illustrates how to install libpng and FreeType using
brew:

brew install libpng freetype pkg-config

If you are using MacPorts, execute the following instead:

port install libpng freetype pkgconfig

After installing the above requirements, install Matplotlib from source by
executing:

python -mpip install .

Note that your environment is somewhat important. Some conda users have
found that, to run the tests, their PYTHONPATH must include
/path/to/anaconda/…/site-packages and their DYLD_FALLBACK_LIBRARY_PATH
must include /path/to/anaconda/lib.

Building on Windows ¶

The Python shipped from https://www.python.org is compiled with Visual Studio
2015 for 3.5+. Python extensions should be compiled with the same
compiler, see e.g.
https://packaging.python.org/guides/packaging-binary-extensions/#setting-up-a-build-environment-on-windows
for how to set up a build environment.

Since there is no canonical Windows package manager, the methods for building
FreeType, zlib, and libpng from source code are documented as a build script
at matplotlib-winbuild .

There are a few possibilities to build Matplotlib on Windows:

  • Wheels via matplotlib-winbuild
  • Wheels by using conda packages
  • Conda packages

Wheel builds using conda packages ¶

This is a wheel build, but we use conda packages to get all the requirements.
The binary requirements (png, FreeType,…) are statically linked and therefore
not needed during the wheel install.

# create a new environment with the required packagesconda create -n "matplotlib_build" python=3.5 numpy python-dateutil pyparsing pytz tornado cycler tk libpng zlib freetypeactivate matplotlib_build# if you want a qt backend, you also have to install pyqt (be aware that pyqt doesn't mix well if# you have created the environment with conda-forge already activated...)conda install pyqt# this package is only available in the conda-forge channelconda install -c conda-forge msinttypes# copy the libs which have "wrong" namesset LIBRARY_LIB=%CONDA_PREFIX%\Library\libmkdir lib || cmd /c "exit /b 0"copy %LIBRARY_LIB%\zlibstatic.lib lib\z.libcopy %LIBRARY_LIB%\libpng_static.lib lib\png.lib# Make the header files and the rest of the static libs available during the build# CONDA_DEFAULT_ENV is a env variable which is set to the currently active environment pathset MPLBASEDIRLIST=%CONDA_PREFIX%\Library\;.# build the wheelpython setup.py bdist_wheel

The build_alllocal.cmd script in the root folder automates these steps if
you have already created and activated the conda environment.

Conda packages ¶

The conda packaging scripts for Matplotlib are available at
https://github.com/conda-forge/python-feedstock .

© Copyright 2002 – 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 2012 – 2018 The Matplotlib development team.

Last updated on Nov 11, 2018.
Created using
Sphinx 1.8.1.
Doc version v3.0.2-2-g91e2d00a8.

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License: Python Software Foundation License (BSD)

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cp36

matplotlib-3.0.2-cp36-cp36m-win_amd64.whl

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cp36

matplotlib-3.0.2-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl

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cp37

matplotlib-3.0.2-cp37-cp37m-manylinux1_x86_64.whl

(12.9 MB)


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cp37

matplotlib-3.0.2-cp37-cp37m-win32.whl

(8.7 MB)


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cp37

matplotlib-3.0.2-cp37-cp37m-win_amd64.whl

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cp37

matplotlib-3.0.2.tar.gz

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