@@ -271,7 +271,7 @@ def my_plotter(ax, data1, data2, param_dict):
271271# plotting windows pop up when they type commands. Some people run
272272# `Jupyter <https://jupyter.org>`_ notebooks and draw inline plots for
273273# quick data analysis. Others embed Matplotlib into graphical user
274- # interfaces like wxpython or pygtk to build rich applications. Some
274+ # interfaces like PyQt or PyGObject to build rich applications. Some
275275# people use Matplotlib in batch scripts to generate postscript images
276276# from numerical simulations, and still others run web application
277277# servers to dynamically serve up graphs.
@@ -281,8 +281,8 @@ def my_plotter(ax, data1, data2, param_dict):
281281# "frontend" is the user facing code, i.e., the plotting code, whereas the
282282# "backend" does all the hard work behind-the-scenes to make the figure.
283283# There are two types of backends: user interface backends (for use in
284- # pygtk, wxpython, tkinter, qt4, qt5, or macosx ; also referred to as
285- # "interactive backends") and hardcopy backends to make image files
284+ # PyQt/PySide, PyGObject, Tkinter, wxPython, or macOS/Cocoa) ; also referred to
285+ # as "interactive backends") and hardcopy backends to make image files
286286# (PNG, SVG, PDF, PS; also referred to as "non-interactive backends").
287287#
288288# Selecting a backend
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