_matplotlib_manages_backends uses hasattr not version check

IPython/core/pylabtools.py

@@ -1,479 +1,498 b''
 # -*- coding: utf-8 -*-
 """Pylab (matplotlib) support utilities."""
 
 # Copyright (c) IPython Development Team.
 # Distributed under the terms of the Modified BSD License.
 
 from io import BytesIO
 from binascii import b2a_base64
 from functools import partial
 import warnings
 
 from IPython.core.display import _pngxy
 from IPython.utils.decorators import flag_calls
 
 
 # Matplotlib backend resolution functionality moved from IPython to Matplotlib
 # in IPython 8.24 and Matplotlib 3.9.1. Need to keep `backends` and `backend2gui`
 # here for earlier Matplotlib and for external backend libraries such as
 # mplcairo that might rely upon it.
 _deprecated_backends = {
     "tk": "TkAgg",
     "gtk": "GTKAgg",
     "gtk3": "GTK3Agg",
     "gtk4": "GTK4Agg",
     "wx": "WXAgg",
     "qt4": "Qt4Agg",
     "qt5": "Qt5Agg",
     "qt6": "QtAgg",
     "qt": "QtAgg",
     "osx": "MacOSX",
     "nbagg": "nbAgg",
     "webagg": "WebAgg",
     "notebook": "nbAgg",
     "agg": "agg",
     "svg": "svg",
     "pdf": "pdf",
     "ps": "ps",
     "inline": "module://matplotlib_inline.backend_inline",
     "ipympl": "module://ipympl.backend_nbagg",
     "widget": "module://ipympl.backend_nbagg",
 }
 
 # We also need a reverse backends2guis mapping that will properly choose which
 # GUI support to activate based on the desired matplotlib backend.  For the
 # most part it's just a reverse of the above dict, but we also need to add a
 # few others that map to the same GUI manually:
 _deprecated_backend2gui = dict(
     zip(_deprecated_backends.values(), _deprecated_backends.keys())
 )
 # In the reverse mapping, there are a few extra valid matplotlib backends that
 # map to the same GUI support
 _deprecated_backend2gui["GTK"] = _deprecated_backend2gui["GTKCairo"] = "gtk"
 _deprecated_backend2gui["GTK3Cairo"] = "gtk3"
 _deprecated_backend2gui["GTK4Cairo"] = "gtk4"
 _deprecated_backend2gui["WX"] = "wx"
 _deprecated_backend2gui["CocoaAgg"] = "osx"
 # There needs to be a hysteresis here as the new QtAgg Matplotlib backend
 # supports either Qt5 or Qt6 and the IPython qt event loop support Qt4, Qt5,
 # and Qt6.
 _deprecated_backend2gui["QtAgg"] = "qt"
 _deprecated_backend2gui["Qt4Agg"] = "qt4"
 _deprecated_backend2gui["Qt5Agg"] = "qt5"
 
 # And some backends that don't need GUI integration
 del _deprecated_backend2gui["nbAgg"]
 del _deprecated_backend2gui["agg"]
 del _deprecated_backend2gui["svg"]
 del _deprecated_backend2gui["pdf"]
 del _deprecated_backend2gui["ps"]
 del _deprecated_backend2gui["module://matplotlib_inline.backend_inline"]
 del _deprecated_backend2gui["module://ipympl.backend_nbagg"]
 
 
 # Deprecated attributes backends and backend2gui mostly following PEP 562.
 def __getattr__(name):
     if name in ("backends", "backend2gui"):
         warnings.warn(
             f"{name} is deprecated since IPython 8.24, backends are managed "
             "in matplotlib and can be externally registered.",
             DeprecationWarning)
         return globals()[f"_deprecated_{name}"]
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 
 #-----------------------------------------------------------------------------
 # Matplotlib utilities
 #-----------------------------------------------------------------------------
 
 
 def getfigs(*fig_nums):
     """Get a list of matplotlib figures by figure numbers.
 
     If no arguments are given, all available figures are returned.  If the
     argument list contains references to invalid figures, a warning is printed
     but the function continues pasting further figures.
 
     Parameters
     ----------
     figs : tuple
         A tuple of ints giving the figure numbers of the figures to return.
     """
     from matplotlib._pylab_helpers import Gcf
     if not fig_nums:
         fig_managers = Gcf.get_all_fig_managers()
         return [fm.canvas.figure for fm in fig_managers]
     else:
         figs = []
         for num in fig_nums:
             f = Gcf.figs.get(num)
             if f is None:
                 print('Warning: figure %s not available.' % num)
             else:
                 figs.append(f.canvas.figure)
         return figs
 
 
 def figsize(sizex, sizey):
     """Set the default figure size to be [sizex, sizey].
 
     This is just an easy to remember, convenience wrapper that sets::
 
       matplotlib.rcParams['figure.figsize'] = [sizex, sizey]
     """
     import matplotlib
     matplotlib.rcParams['figure.figsize'] = [sizex, sizey]
 
 
 def print_figure(fig, fmt="png", bbox_inches="tight", base64=False, **kwargs):
     """Print a figure to an image, and return the resulting file data
 
     Returned data will be bytes unless ``fmt='svg'``,
     in which case it will be unicode.
 
     Any keyword args are passed to fig.canvas.print_figure,
     such as ``quality`` or ``bbox_inches``.
 
     If `base64` is True, return base64-encoded str instead of raw bytes
     for binary-encoded image formats
 
     .. versionadded:: 7.29
         base64 argument
     """
     # When there's an empty figure, we shouldn't return anything, otherwise we
     # get big blank areas in the qt console.
     if not fig.axes and not fig.lines:
         return
 
     dpi = fig.dpi
     if fmt == 'retina':
         dpi = dpi * 2
         fmt = 'png'
 
     # build keyword args
     kw = {
         "format":fmt,
         "facecolor":fig.get_facecolor(),
         "edgecolor":fig.get_edgecolor(),
         "dpi":dpi,
         "bbox_inches":bbox_inches,
     }
     # **kwargs get higher priority
     kw.update(kwargs)
 
     bytes_io = BytesIO()
     if fig.canvas is None:
         from matplotlib.backend_bases import FigureCanvasBase
         FigureCanvasBase(fig)
 
     fig.canvas.print_figure(bytes_io, **kw)
     data = bytes_io.getvalue()
     if fmt == 'svg':
         data = data.decode('utf-8')
     elif base64:
         data = b2a_base64(data, newline=False).decode("ascii")
     return data
 
 def retina_figure(fig, base64=False, **kwargs):
     """format a figure as a pixel-doubled (retina) PNG
 
     If `base64` is True, return base64-encoded str instead of raw bytes
     for binary-encoded image formats
 
     .. versionadded:: 7.29
         base64 argument
     """
     pngdata = print_figure(fig, fmt="retina", base64=False, **kwargs)
     # Make sure that retina_figure acts just like print_figure and returns
     # None when the figure is empty.
     if pngdata is None:
         return
     w, h = _pngxy(pngdata)
     metadata = {"width": w//2, "height":h//2}
     if base64:
         pngdata = b2a_base64(pngdata, newline=False).decode("ascii")
     return pngdata, metadata
 
 
 # We need a little factory function here to create the closure where
 # safe_execfile can live.
 def mpl_runner(safe_execfile):
     """Factory to return a matplotlib-enabled runner for %run.
 
     Parameters
     ----------
     safe_execfile : function
         This must be a function with the same interface as the
         :meth:`safe_execfile` method of IPython.
 
     Returns
     -------
     A function suitable for use as the ``runner`` argument of the %run magic
     function.
     """
 
     def mpl_execfile(fname,*where,**kw):
         """matplotlib-aware wrapper around safe_execfile.
 
         Its interface is identical to that of the :func:`execfile` builtin.
 
         This is ultimately a call to execfile(), but wrapped in safeties to
         properly handle interactive rendering."""
 
         import matplotlib
         import matplotlib.pyplot as plt
 
         #print '*** Matplotlib runner ***' # dbg
         # turn off rendering until end of script
         with matplotlib.rc_context({"interactive": False}):
             safe_execfile(fname, *where, **kw)
 
         if matplotlib.is_interactive():
             plt.show()
 
         # make rendering call now, if the user tried to do it
         if plt.draw_if_interactive.called:
             plt.draw()
             plt.draw_if_interactive.called = False
 
         # re-draw everything that is stale
         try:
             da = plt.draw_all
         except AttributeError:
             pass
         else:
             da()
 
     return mpl_execfile
 
 
 def _reshow_nbagg_figure(fig):
     """reshow an nbagg figure"""
     try:
         reshow = fig.canvas.manager.reshow
     except AttributeError as e:
         raise NotImplementedError() from e
     else:
         reshow()
 
 
 def select_figure_formats(shell, formats, **kwargs):
     """Select figure formats for the inline backend.
 
     Parameters
     ----------
     shell : InteractiveShell
         The main IPython instance.
     formats : str or set
         One or a set of figure formats to enable: 'png', 'retina', 'jpeg', 'svg', 'pdf'.
     **kwargs : any
         Extra keyword arguments to be passed to fig.canvas.print_figure.
     """
     import matplotlib
     from matplotlib.figure import Figure
 
     svg_formatter = shell.display_formatter.formatters['image/svg+xml']
     png_formatter = shell.display_formatter.formatters['image/png']
     jpg_formatter = shell.display_formatter.formatters['image/jpeg']
     pdf_formatter = shell.display_formatter.formatters['application/pdf']
 
     if isinstance(formats, str):
         formats = {formats}
     # cast in case of list / tuple
     formats = set(formats)
 
     [ f.pop(Figure, None) for f in shell.display_formatter.formatters.values() ]
     mplbackend = matplotlib.get_backend().lower()
     if mplbackend in ("nbagg", "ipympl", "widget", "module://ipympl.backend_nbagg"):
         formatter = shell.display_formatter.ipython_display_formatter
         formatter.for_type(Figure, _reshow_nbagg_figure)
 
     supported = {'png', 'png2x', 'retina', 'jpg', 'jpeg', 'svg', 'pdf'}
     bad = formats.difference(supported)
     if bad:
         bs = "%s" % ','.join([repr(f) for f in bad])
         gs = "%s" % ','.join([repr(f) for f in supported])
         raise ValueError("supported formats are: %s not %s" % (gs, bs))
 
     if "png" in formats:
         png_formatter.for_type(
             Figure, partial(print_figure, fmt="png", base64=True, **kwargs)
         )
     if "retina" in formats or "png2x" in formats:
         png_formatter.for_type(Figure, partial(retina_figure, base64=True, **kwargs))
     if "jpg" in formats or "jpeg" in formats:
         jpg_formatter.for_type(
             Figure, partial(print_figure, fmt="jpg", base64=True, **kwargs)
         )
     if "svg" in formats:
         svg_formatter.for_type(Figure, partial(print_figure, fmt="svg", **kwargs))
     if "pdf" in formats:
         pdf_formatter.for_type(
             Figure, partial(print_figure, fmt="pdf", base64=True, **kwargs)
         )
 
 #-----------------------------------------------------------------------------
 # Code for initializing matplotlib and importing pylab
 #-----------------------------------------------------------------------------
 
 
 def find_gui_and_backend(gui=None, gui_select=None):
     """Given a gui string return the gui and mpl backend.
 
     Parameters
     ----------
     gui : str
         Can be one of ('tk','gtk','wx','qt','qt4','inline','agg').
     gui_select : str
         Can be one of ('tk','gtk','wx','qt','qt4','inline').
         This is any gui already selected by the shell.
 
     Returns
     -------
     A tuple of (gui, backend) where backend is one of ('TkAgg','GTKAgg',
     'WXAgg','Qt4Agg','module://matplotlib_inline.backend_inline','agg').
     """
 
     import matplotlib
 
     if _matplotlib_manages_backends():
         backend_registry = matplotlib.backends.registry.backend_registry
 
         # gui argument may be a gui event loop or may be a backend name.
         if gui in ("auto", None):
             backend = matplotlib.rcParamsOrig["backend"]
             backend, gui = backend_registry.resolve_backend(backend)
         else:
             backend, gui = backend_registry.resolve_gui_or_backend(gui)
 
         return gui, backend
 
     # Fallback to previous behaviour (Matplotlib < 3.9)
     mpl_version_info = getattr(matplotlib, "__version_info__", (0, 0))
     has_unified_qt_backend = mpl_version_info >= (3, 5)
 
     from IPython.core.pylabtools import backends
 
     backends_ = dict(backends)
     if not has_unified_qt_backend:
         backends_["qt"] = "qt5agg"
 
     if gui and gui != 'auto':
         # select backend based on requested gui
         backend = backends_[gui]
         if gui == 'agg':
             gui = None
     else:
         # We need to read the backend from the original data structure, *not*
         # from mpl.rcParams, since a prior invocation of %matplotlib may have
         # overwritten that.
         # WARNING: this assumes matplotlib 1.1 or newer!!
         backend = matplotlib.rcParamsOrig['backend']
         # In this case, we need to find what the appropriate gui selection call
         # should be for IPython, so we can activate inputhook accordingly
         from IPython.core.pylabtools import backend2gui
         gui = backend2gui.get(backend, None)
 
         # If we have already had a gui active, we need it and inline are the
         # ones allowed.
         if gui_select and gui != gui_select:
             gui = gui_select
             backend = backends_[gui]
 
     # Matplotlib before _matplotlib_manages_backends() can return "inline" for
     # no gui event loop rather than the None that IPython >= 8.24.0 expects.
     if gui == "inline":
         gui = None
 
     return gui, backend
 
 
 def activate_matplotlib(backend):
     """Activate the given backend and set interactive to True."""
 
     import matplotlib
     matplotlib.interactive(True)
 
     # Matplotlib had a bug where even switch_backend could not force
     # the rcParam to update. This needs to be set *before* the module
     # magic of switch_backend().
     matplotlib.rcParams['backend'] = backend
 
     # Due to circular imports, pyplot may be only partially initialised
     # when this function runs.
     # So avoid needing matplotlib attribute-lookup to access pyplot.
     from matplotlib import pyplot as plt
 
     plt.switch_backend(backend)
 
     plt.show._needmain = False
     # We need to detect at runtime whether show() is called by the user.
     # For this, we wrap it into a decorator which adds a 'called' flag.
     plt.draw_if_interactive = flag_calls(plt.draw_if_interactive)
 
 
 def import_pylab(user_ns, import_all=True):
     """Populate the namespace with pylab-related values.
 
     Imports matplotlib, pylab, numpy, and everything from pylab and numpy.
 
     Also imports a few names from IPython (figsize, display, getfigs)
 
     """
 
     # Import numpy as np/pyplot as plt are conventions we're trying to
     # somewhat standardize on.  Making them available to users by default
     # will greatly help this.
     s = ("import numpy\n"
           "import matplotlib\n"
           "from matplotlib import pylab, mlab, pyplot\n"
           "np = numpy\n"
           "plt = pyplot\n"
           )
     exec(s, user_ns)
 
     if import_all:
         s = ("from matplotlib.pylab import *\n"
              "from numpy import *\n")
         exec(s, user_ns)
 
     # IPython symbols to add
     user_ns['figsize'] = figsize
     from IPython.display import display
     # Add display and getfigs to the user's namespace
     user_ns['display'] = display
     user_ns['getfigs'] = getfigs
 
 
 def configure_inline_support(shell, backend):
     """
     .. deprecated:: 7.23
 
         use `matplotlib_inline.backend_inline.configure_inline_support()`
 
     Configure an IPython shell object for matplotlib use.
 
     Parameters
     ----------
     shell : InteractiveShell instance
     backend : matplotlib backend
     """
     warnings.warn(
         "`configure_inline_support` is deprecated since IPython 7.23, directly "
         "use `matplotlib_inline.backend_inline.configure_inline_support()`",
         DeprecationWarning,
         stacklevel=2,
     )
 
     from matplotlib_inline.backend_inline import (
         configure_inline_support as configure_inline_support_orig,
     )
 
     configure_inline_support_orig(shell, backend)
 
 
-def _matplotlib_manages_backends():
-    import matplotlib
+# Determine if Matplotlib manages backends only if needed, and cache result.
+# Do not read this directly, instead use _matplotlib_manages_backends().
+_matplotlib_manages_backends_value: bool | None = None
 
-    mpl_version_info = getattr(matplotlib, "__version_info__", (0, 0))
-    return mpl_version_info >= (3, 9)
+
+def _matplotlib_manages_backends() -> bool:
+    """Return True if Matplotlib manages backends, False otherwise.
+
+    If it returns True, the caller can be sure that
+    matplotlib.backends.registry.backend_registry is available along with
+    member functions resolve_gui_or_backend, resolve_backend and list_all.
+    """
+    global _matplotlib_manages_backends_value
+    if _matplotlib_manages_backends_value is None:
+        try:
+            from matplotlib.backends.registry import backend_registry
+
+            _matplotlib_manages_backends_value = hasattr(
+                backend_registry, "resolve_gui_or_backend"
+            )
+        except ImportError:
+            _matplotlib_manages_backends_value = False
+
+    return _matplotlib_manages_backends_value