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<!DOCTYPE html>

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<span id="id1"></span><h1>Backends<a class="headerlink" href="#backends" title="Link to this heading">#</a></h1>

<span id="id2"></span><h2>What is a backend?<a class="headerlink" href="#what-is-a-backend" title="Link to this heading">#</a></h2>

<p>A lot of documentation on the website and in the mailing lists refers

to the "backend" and many new users are confused by this term.

Matplotlib targets many different use cases and output formats. Some

people use Matplotlib interactively from the Python shell and have

plotting windows pop up when they type commands. Some people run

<a class="reference external" href="https://jupyter.org">Jupyter</a> notebooks and draw inline plots for

quick data analysis. Others embed Matplotlib into graphical user

interfaces like PyQt or PyGObject to build rich applications. Some

people use Matplotlib in batch scripts to generate postscript images

from numerical simulations, and still others run web application

servers to dynamically serve up graphs.</p>

<p>To support all of these use cases, Matplotlib can target different

outputs, and each of these capabilities is called a backend; the

"frontend" is the user facing code, i.e., the plotting code, whereas the

"backend" does all the hard work behind-the-scenes to make the figure.

There are two types of backends: user interface backends (for use in

PyQt/PySide, PyGObject, Tkinter, wxPython, or macOS/Cocoa); also referred to

as "interactive backends") and hardcopy backends to make image files

(PNG, SVG, PDF, PS; also referred to as "non-interactive backends").</p>

</section>

<h2>Selecting a backend<a class="headerlink" href="#selecting-a-backend" title="Link to this heading">#</a></h2>

<p>There are three ways to configure your backend:</p>

<li><p>The <code class="docutils literal notranslate"><a class="reference internal" href="../../tutorials/introductory/customizing.html?highlight=backend#matplotlibrc-sample"><span class="std std-ref"><span class="pre">rcParams["backend"]</span></span></a></code> parameter in your <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code> file</p></li>

<li><p>The <span class="target" id="index-0"></span><a class="reference internal" href="../faq/environment_variables_faq.html#envvar-MPLBACKEND"><code class="xref std std-envvar docutils literal notranslate"><span class="pre">MPLBACKEND</span></code></a> environment variable</p></li>

<li><p>The function <a class="reference internal" href="../../api/matplotlib_configuration_api.html#matplotlib.use" title="matplotlib.use"><code class="xref py py-func docutils literal notranslate"><span class="pre">matplotlib.use()</span></code></a></p></li>

</ul>

<p>Below is a more detailed description.</p>

<p>If there is more than one configuration present, the last one from the

list takes precedence; e.g. calling <a class="reference internal" href="../../api/matplotlib_configuration_api.html#matplotlib.use" title="matplotlib.use"><code class="xref py py-func docutils literal notranslate"><span class="pre">matplotlib.use()</span></code></a> will override

the setting in your <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code>.</p>

<p>Without a backend explicitly set, Matplotlib automatically detects a usable

backend based on what is available on your system and on whether a GUI event

loop is already running. The first usable backend in the following list is

selected: MacOSX, QtAgg, GTK4Agg, Gtk3Agg, TkAgg, WxAgg, Agg. The last, Agg,

is a non-interactive backend that can only write to files. It is used on

Linux, if Matplotlib cannot connect to either an X display or a Wayland

display.</p>

<p>Here is a detailed description of the configuration methods:</p>

<li><p>Setting <code class="docutils literal notranslate"><a class="reference internal" href="../../tutorials/introductory/customizing.html?highlight=backend#matplotlibrc-sample"><span class="std std-ref"><span class="pre">rcParams["backend"]</span></span></a></code> in your <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code> file:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">backend</span> <span class="p">:</span> <span class="n">qtagg</span> <span class="c1"># use pyqt with antigrain (agg) rendering</span>

</pre></div>

</div>

<p>See also <a class="reference internal" href="../../tutorials/introductory/customizing.html"><span class="doc">Customizing Matplotlib with style sheets and rcParams</span></a>.</p>

</li>

<li><p>Setting the <span class="target" id="index-1"></span><a class="reference internal" href="../faq/environment_variables_faq.html#envvar-MPLBACKEND"><code class="xref std std-envvar docutils literal notranslate"><span class="pre">MPLBACKEND</span></code></a> environment variable:</p>

<p>You can set the environment variable either for your current shell or for

a single script.</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">></span> <span class="n">export</span> <span class="n">MPLBACKEND</span><span class="o">=</span><span class="n">qtagg</span>

<span class="o">></span> <span class="n">python</span> <span class="n">simple_plot</span><span class="o">.</span><span class="n">py</span>

<span class="o">></span> <span class="n">MPLBACKEND</span><span class="o">=</span><span class="n">qtagg</span> <span class="n">python</span> <span class="n">simple_plot</span><span class="o">.</span><span class="n">py</span>

</pre></div>

</div>

<p>On Windows, only the former is possible:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">></span> <span class="nb">set</span> <span class="n">MPLBACKEND</span><span class="o">=</span><span class="n">qtagg</span>

<span class="o">></span> <span class="n">python</span> <span class="n">simple_plot</span><span class="o">.</span><span class="n">py</span>

</pre></div>

</div>

<p>Setting this environment variable will override the <code class="docutils literal notranslate"><span class="pre">backend</span></code> parameter

in <em>any</em> <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code>, even if there is a <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code> in

your current working directory. Therefore, setting <span class="target" id="index-2"></span><a class="reference internal" href="../faq/environment_variables_faq.html#envvar-MPLBACKEND"><code class="xref std std-envvar docutils literal notranslate"><span class="pre">MPLBACKEND</span></code></a>

globally, e.g. in your <code class="file docutils literal notranslate"><span class="pre">.bashrc</span></code> or <code class="file docutils literal notranslate"><span class="pre">.profile</span></code>, is discouraged

as it might lead to counter-intuitive behavior.</p>

</li>

<li><p>If your script depends on a specific backend you can use the function

<a class="reference internal" href="../../api/matplotlib_configuration_api.html#matplotlib.use" title="matplotlib.use"><code class="xref py py-func docutils literal notranslate"><span class="pre">matplotlib.use()</span></code></a>:</p>

<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib</span>

<span class="n">matplotlib</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s1">'qtagg'</span><span class="p">)</span>

</pre></div>

</div>

<p>This should be done before any figure is created, otherwise Matplotlib may

fail to switch the backend and raise an ImportError.</p>

<p>Using <a class="reference internal" href="../../api/matplotlib_configuration_api.html#matplotlib.use" title="matplotlib.use"><code class="xref py py-obj docutils literal notranslate"><span class="pre">use</span></code></a> will require changes in your code if users want to

use a different backend. Therefore, you should avoid explicitly calling

<a class="reference internal" href="../../api/matplotlib_configuration_api.html#matplotlib.use" title="matplotlib.use"><code class="xref py py-obj docutils literal notranslate"><span class="pre">use</span></code></a> unless absolutely necessary.</p>

</li>

</ol>

</section>

<span id="id3"></span><h2>The builtin backends<a class="headerlink" href="#the-builtin-backends" title="Link to this heading">#</a></h2>

<p>By default, Matplotlib should automatically select a default backend which

allows both interactive work and plotting from scripts, with output to the

screen and/or to a file, so at least initially, you will not need to worry

about the backend. The most common exception is if your Python distribution

comes without <a class="reference external" href="https://docs.python.org/3/library/tkinter.html#module-tkinter" title="(in Python v3.12)"><code class="xref py py-mod docutils literal notranslate"><span class="pre">tkinter</span></code></a> and you have no other GUI toolkit installed.

This happens with certain Linux distributions, where you need to install a

Linux package named <code class="docutils literal notranslate"><span class="pre">python-tk</span></code> (or similar).</p>

<p>If, however, you want to write graphical user interfaces, or a web

application server

(<a class="reference internal" href="../../gallery/user_interfaces/web_application_server_sgskip.html"><span class="doc">Embedding in a web application server (Flask)</span></a>), or need a

better understanding of what is going on, read on. To make things easily

more customizable for graphical user interfaces, Matplotlib separates

the concept of the renderer (the thing that actually does the drawing)

from the canvas (the place where the drawing goes). The canonical

renderer for user interfaces is <code class="docutils literal notranslate"><span class="pre">Agg</span></code> which uses the <a class="reference external" href="http://agg.sourceforge.net/antigrain.com/">Anti-Grain

Geometry</a> C++ library to make a raster (pixel) image of the figure; it

is used by the <code class="docutils literal notranslate"><span class="pre">QtAgg</span></code>, <code class="docutils literal notranslate"><span class="pre">GTK4Agg</span></code>, <code class="docutils literal notranslate"><span class="pre">GTK3Agg</span></code>, <code class="docutils literal notranslate"><span class="pre">wxAgg</span></code>, <code class="docutils literal notranslate"><span class="pre">TkAgg</span></code>, and

<code class="docutils literal notranslate"><span class="pre">macosx</span></code> backends. An alternative renderer is based on the Cairo library,

used by <code class="docutils literal notranslate"><span class="pre">QtCairo</span></code>, etc.</p>

<p>For the rendering engines, users can also distinguish between <a class="reference external" href="https://en.wikipedia.org/wiki/Vector_graphics">vector</a> or <a class="reference external" href="https://en.wikipedia.org/wiki/Raster_graphics">raster</a> renderers. Vector

graphics languages issue drawing commands like "draw a line from this

point to this point" and hence are scale free. Raster backends

generate a pixel representation of the line whose accuracy depends on a

DPI setting.</p>

<h3>Static backends<a class="headerlink" href="#static-backends" title="Link to this heading">#</a></h3>

<p>Here is a summary of the Matplotlib renderers (there is an eponymous

backend for each; these are <em>non-interactive backends</em>, capable of

writing to a file):</p>

<thead>

<tr class="row-odd"><th class="head"><p>Renderer</p></th>

<th class="head"><p>Filetypes</p></th>

<th class="head"><p>Description</p></th>

</tr>

</thead>

<tbody>

<td><p><a class="reference external" href="https://en.wikipedia.org/wiki/Raster_graphics">raster</a> graphics -- high quality images using the

<a class="reference external" href="http://agg.sourceforge.net/antigrain.com/">Anti-Grain Geometry</a> engine.</p></td>

</tr>

<td><p><a class="reference external" href="https://en.wikipedia.org/wiki/Vector_graphics">vector</a> graphics -- <a class="reference external" href="https://en.wikipedia.org/wiki/Portable_Document_Format">Portable Document Format</a> output.</p></td>

</tr>

</tr>

<td><p><a class="reference external" href="https://en.wikipedia.org/wiki/Vector_graphics">vector</a> graphics -- <a class="reference external" href="https://en.wikipedia.org/wiki/Scalable_Vector_Graphics">Scalable Vector Graphics</a> output.</p></td>

</tr>

<td><p><a class="reference external" href="https://en.wikipedia.org/wiki/Vector_graphics">vector</a> graphics -- using the <a class="reference external" href="https://ctan.org/pkg/pgf">pgf</a> package.</p></td>

</tr>

<tr class="row-odd"><td><p>Cairo</p></td>

<td><p>png, ps,

pdf, svg</p></td>

<td><p><a class="reference external" href="https://en.wikipedia.org/wiki/Raster_graphics">raster</a> or <a class="reference external" href="https://en.wikipedia.org/wiki/Vector_graphics">vector</a> graphics -- using the <a class="reference external" href="https://www.cairographics.org">Cairo</a> library

(requires <a class="reference external" href="https://www.cairographics.org/pycairo/">pycairo</a> or <a class="reference external" href="https://pythonhosted.org/cairocffi/">cairocffi</a>).</p></td>

</tr>

</tbody>

</table>

<p>To save plots using the non-interactive backends, use the

<code class="docutils literal notranslate"><span class="pre">matplotlib.pyplot.savefig('filename')</span></code> method.</p>

</section>

<h3>Interactive backends<a class="headerlink" href="#interactive-backends" title="Link to this heading">#</a></h3>

<p>These are the user interfaces and renderer combinations supported;

these are <em>interactive backends</em>, capable of displaying to the screen

and using appropriate renderers from the table above to write to

a file:</p>

<thead>

<tr class="row-odd"><th class="head"><p>Backend</p></th>

<th class="head"><p>Description</p></th>

</tr>

</thead>

<tbody>

<tr class="row-even"><td><p>QtAgg</p></td>

<td><p>Agg rendering in a <a class="reference external" href="https://qt.io/">Qt</a> canvas (requires <a class="reference external" href="https://riverbankcomputing.com/software/pyqt/intro">PyQt</a> or <a class="reference external" href="https://doc.qt.io/qtforpython/">Qt for Python</a>,

a.k.a. PySide). This backend can be activated in IPython with

<code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">qt</span></code>. The Qt binding can be selected via the

<span class="target" id="index-3"></span><a class="reference internal" href="../faq/environment_variables_faq.html#envvar-QT_API"><code class="xref std std-envvar docutils literal notranslate"><span class="pre">QT_API</span></code></a> environment variable; see <a class="reference internal" href="../../api/backend_qt_api.html#qt-bindings"><span class="std std-ref">Qt Bindings</span></a> for

more details.</p></td>

</tr>

<tr class="row-odd"><td><p>ipympl</p></td>

<td><p>Agg rendering embedded in a Jupyter widget (requires <a class="reference external" href="https://www.matplotlib.org/ipympl">ipympl</a>).

This backend can be enabled in a Jupyter notebook with

<code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">ipympl</span></code>.</p></td>

</tr>

<td><p>Agg rendering to a <a class="reference external" href="https://www.gtk.org/">GTK</a> 3.x canvas (requires <a class="reference external" href="https://wiki.gnome.org/action/show/Projects/PyGObject">PyGObject</a> and

<a class="reference external" href="https://www.cairographics.org/pycairo/">pycairo</a>). This backend can be activated in IPython with

<code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">gtk3</span></code>.</p></td>

</tr>

<td><p>Agg rendering to a <a class="reference external" href="https://www.gtk.org/">GTK</a> 4.x canvas (requires <a class="reference external" href="https://wiki.gnome.org/action/show/Projects/PyGObject">PyGObject</a> and

<a class="reference external" href="https://www.cairographics.org/pycairo/">pycairo</a>). This backend can be activated in IPython with

<code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">gtk4</span></code>.</p></td>

</tr>

<tr class="row-even"><td><p>macosx</p></td>

<td><p>Agg rendering into a Cocoa canvas in OSX. This backend can be

activated in IPython with <code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">osx</span></code>.</p></td>

</tr>

<tr class="row-odd"><td><p>TkAgg</p></td>

<td><p>Agg rendering to a <a class="reference external" href="https://www.tcl.tk/">Tk</a> canvas (requires <a class="reference external" href="https://docs.python.org/3/library/tk.html">TkInter</a>). This

backend can be activated in IPython with <code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">tk</span></code>.</p></td>

</tr>

<tr class="row-even"><td><p>nbAgg</p></td>

<td><p>Embed an interactive figure in a Jupyter classic notebook. This

backend can be enabled in Jupyter notebooks via

<code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">notebook</span></code>.</p></td>

</tr>

<tr class="row-odd"><td><p>WebAgg</p></td>

<td><p>On <code class="docutils literal notranslate"><span class="pre">show()</span></code> will start a tornado server with an interactive

figure.</p></td>

</tr>

<tr class="row-even"><td><p>GTK3Cairo</p></td>

<td><p>Cairo rendering to a <a class="reference external" href="https://www.gtk.org/">GTK</a> 3.x canvas (requires <a class="reference external" href="https://wiki.gnome.org/action/show/Projects/PyGObject">PyGObject</a> and

<a class="reference external" href="https://www.cairographics.org/pycairo/">pycairo</a>).</p></td>

</tr>

<tr class="row-odd"><td><p>GTK4Cairo</p></td>

<td><p>Cairo rendering to a <a class="reference external" href="https://www.gtk.org/">GTK</a> 4.x canvas (requires <a class="reference external" href="https://wiki.gnome.org/action/show/Projects/PyGObject">PyGObject</a> and

<a class="reference external" href="https://www.cairographics.org/pycairo/">pycairo</a>).</p></td>

</tr>

<tr class="row-even"><td><p>wxAgg</p></td>

<td><p>Agg rendering to a <a class="reference external" href="https://www.wxwidgets.org/">wxWidgets</a> canvas (requires <a class="reference external" href="https://www.wxpython.org/">wxPython</a> 4).

This backend can be activated in IPython with <code class="docutils literal notranslate"><span class="pre">%matplotlib</span> <span class="pre">wx</span></code>.</p></td>

</tr>

</tbody>

</table>

<p>The names of builtin backends case-insensitive; e.g., 'QtAgg' and

'qtagg' are equivalent.</p>

</div>

</section>

<h3>ipympl<a class="headerlink" href="#id4" title="Link to this heading">#</a></h3>

<p>The Jupyter widget ecosystem is moving too fast to support directly in

Matplotlib. To install ipympl:</p>

<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>ipympl

</pre></div>

</div>

<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>conda<span class="w"> </span>install<span class="w"> </span>ipympl<span class="w"> </span>-c<span class="w"> </span>conda-forge

</pre></div>

</div>

<p>See <a class="reference external" href="https://matplotlib.org/ipympl/installing.html">installing ipympl</a> for more details.</p>

</section>

<h2>Using non-builtin backends<a class="headerlink" href="#using-non-builtin-backends" title="Link to this heading">#</a></h2>

<p>More generally, any importable backend can be selected by using any of the

methods above. If <code class="docutils literal notranslate"><span class="pre">name.of.the.backend</span></code> is the module containing the

backend, use <code class="docutils literal notranslate"><span class="pre">module://name.of.the.backend</span></code> as the backend name, e.g.

<code class="docutils literal notranslate"><span class="pre">matplotlib.use('module://name.of.the.backend')</span></code>.</p>

<p>Information for backend implementers is available at

<a class="reference internal" href="writing_a_backend_pyplot_interface.html"><span class="doc">Writing a backend -- the pyplot interface</span></a>.</p>

</section>

</article>

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What is a backend?

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Selecting a backend

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The builtin backends

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Static backends

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Interactive backends

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ipympl

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Using non-builtin backends

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