Update Matplotlib docs

IPython/core/pylabtools.py

@@ -1,518 +1,522 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`
+# in IPython 8.24 and Matplotlib 3.9.0. 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)
 
 
 # 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
 
 
 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, list_all, and
     list_gui_frameworks.
+
+    This function can be removed as it will always return True when Python
+    3.12, the latest version supported by Matplotlib < 3.9, reaches
+    end-of-life in late 2028.
     """
     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
 
 
 def _list_matplotlib_backends_and_gui_loops() -> list[str]:
     """Return list of all Matplotlib backends and GUI event loops.
 
     This is the list returned by
         %matplotlib --list
     """
     if _matplotlib_manages_backends():
         from matplotlib.backends.registry import backend_registry
 
         ret = backend_registry.list_all() + backend_registry.list_gui_frameworks()
     else:
         from IPython.core import pylabtools
 
         ret = list(pylabtools.backends.keys())
 
     return sorted(["auto"] + ret)

IPython/core/shellapp.py

@@ -1,491 +1,495 b''
 # encoding: utf-8
 """
 A mixin for :class:`~IPython.core.application.Application` classes that
 launch InteractiveShell instances, load extensions, etc.
 """
 
 # Copyright (c) IPython Development Team.
 # Distributed under the terms of the Modified BSD License.
 
 import glob
 from itertools import chain
 import os
 import sys
 import typing as t
 
 from traitlets.config.application import boolean_flag
 from traitlets.config.configurable import Configurable
 from traitlets.config.loader import Config
 from IPython.core.application import SYSTEM_CONFIG_DIRS, ENV_CONFIG_DIRS
 from IPython.utils.contexts import preserve_keys
 from IPython.utils.path import filefind
 from traitlets import (
     Unicode,
     Instance,
     List,
     Bool,
     CaselessStrEnum,
     observe,
     DottedObjectName,
     Undefined,
 )
 from IPython.terminal import pt_inputhooks
 
 # -----------------------------------------------------------------------------
 # Aliases and Flags
 # -----------------------------------------------------------------------------
 
 gui_keys = tuple(sorted(pt_inputhooks.backends) + sorted(pt_inputhooks.aliases))
 
 shell_flags = {}
 
 addflag = lambda *args: shell_flags.update(boolean_flag(*args))
 addflag(
     "autoindent",
     "InteractiveShell.autoindent",
     "Turn on autoindenting.",
     "Turn off autoindenting.",
 )
 addflag(
     "automagic",
     "InteractiveShell.automagic",
     """Turn on the auto calling of magic commands. Type %%magic at the
         IPython  prompt  for  more information.""",
         'Turn off the auto calling of magic commands.'
 )
 addflag('pdb', 'InteractiveShell.pdb',
     "Enable auto calling the pdb debugger after every exception.",
     "Disable auto calling the pdb debugger after every exception."
 )
 addflag('pprint', 'PlainTextFormatter.pprint',
     "Enable auto pretty printing of results.",
     "Disable auto pretty printing of results."
 )
 addflag('color-info', 'InteractiveShell.color_info',
     """IPython can display information about objects via a set of functions,
     and optionally can use colors for this, syntax highlighting
     source code and various other elements. This is on by default, but can cause
     problems with some pagers. If you see such problems, you can disable the
     colours.""",
     "Disable using colors for info related things."
 )
 addflag('ignore-cwd', 'InteractiveShellApp.ignore_cwd',
         "Exclude the current working directory from sys.path",
         "Include the current working directory in sys.path",
 )
 nosep_config = Config()
 nosep_config.InteractiveShell.separate_in = ''
 nosep_config.InteractiveShell.separate_out = ''
 nosep_config.InteractiveShell.separate_out2 = ''
 
 shell_flags['nosep']=(nosep_config, "Eliminate all spacing between prompts.")
 shell_flags['pylab'] = (
     {'InteractiveShellApp' : {'pylab' : 'auto'}},
     """Pre-load matplotlib and numpy for interactive use with
-    the default matplotlib backend."""
+    the default matplotlib backend. The exact options available
+    depend on what Matplotlib provides at runtime.""",
 )
 shell_flags['matplotlib'] = (
     {'InteractiveShellApp' : {'matplotlib' : 'auto'}},
     """Configure matplotlib for interactive use with
-    the default matplotlib backend."""
+    the default matplotlib backend. The exact options available
+    depend on what Matplotlib provides at runtime.""",
 )
 
 # it's possible we don't want short aliases for *all* of these:
 shell_aliases = dict(
     autocall='InteractiveShell.autocall',
     colors='InteractiveShell.colors',
     logfile='InteractiveShell.logfile',
     logappend='InteractiveShell.logappend',
     c='InteractiveShellApp.code_to_run',
     m='InteractiveShellApp.module_to_run',
     ext="InteractiveShellApp.extra_extensions",
     gui='InteractiveShellApp.gui',
     pylab='InteractiveShellApp.pylab',
     matplotlib='InteractiveShellApp.matplotlib',
 )
 shell_aliases['cache-size'] = 'InteractiveShell.cache_size'
 
 
 # -----------------------------------------------------------------------------
 # Traitlets
 # -----------------------------------------------------------------------------
 
 
 class MatplotlibBackendCaselessStrEnum(CaselessStrEnum):
     """An enum of Matplotlib backend strings where the case should be ignored.
 
-    Prior to Matplotlib 3.9.1 the list of valid backends is hardcoded in
+    Prior to Matplotlib 3.9.0 the list of valid backends is hardcoded in
     pylabtools.backends. After that, Matplotlib manages backends.
 
     The list of valid backends is determined when it is first needed to avoid
     wasting unnecessary initialisation time.
     """
 
     def __init__(
         self: CaselessStrEnum[t.Any],
         default_value: t.Any = Undefined,
         **kwargs: t.Any,
     ) -> None:
         super().__init__(None, default_value=default_value, **kwargs)
 
     def __getattribute__(self, name):
         if name == "values" and object.__getattribute__(self, name) is None:
             from IPython.core.pylabtools import _list_matplotlib_backends_and_gui_loops
 
             self.values = _list_matplotlib_backends_and_gui_loops()
         return object.__getattribute__(self, name)
 
 
 #-----------------------------------------------------------------------------
 # Main classes and functions
 #-----------------------------------------------------------------------------
 
 class InteractiveShellApp(Configurable):
     """A Mixin for applications that start InteractiveShell instances.
 
     Provides configurables for loading extensions and executing files
     as part of configuring a Shell environment.
 
     The following methods should be called by the :meth:`initialize` method
     of the subclass:
 
       - :meth:`init_path`
       - :meth:`init_shell` (to be implemented by the subclass)
       - :meth:`init_gui_pylab`
       - :meth:`init_extensions`
       - :meth:`init_code`
     """
     extensions = List(Unicode(),
         help="A list of dotted module names of IPython extensions to load."
     ).tag(config=True)
 
     extra_extensions = List(
         DottedObjectName(),
         help="""
         Dotted module name(s) of one or more IPython extensions to load.
 
         For specifying extra extensions to load on the command-line.
 
         .. versionadded:: 7.10
         """,
     ).tag(config=True)
 
     reraise_ipython_extension_failures = Bool(False,
         help="Reraise exceptions encountered loading IPython extensions?",
     ).tag(config=True)
 
     # Extensions that are always loaded (not configurable)
     default_extensions = List(Unicode(), [u'storemagic']).tag(config=False)
 
     hide_initial_ns = Bool(True,
         help="""Should variables loaded at startup (by startup files, exec_lines, etc.)
         be hidden from tools like %who?"""
     ).tag(config=True)
 
     exec_files = List(Unicode(),
         help="""List of files to run at IPython startup."""
     ).tag(config=True)
     exec_PYTHONSTARTUP = Bool(True,
         help="""Run the file referenced by the PYTHONSTARTUP environment
         variable at IPython startup."""
     ).tag(config=True)
     file_to_run = Unicode('',
         help="""A file to be run""").tag(config=True)
 
     exec_lines = List(Unicode(),
         help="""lines of code to run at IPython startup."""
     ).tag(config=True)
     code_to_run = Unicode("", help="Execute the given command string.").tag(config=True)
     module_to_run = Unicode("", help="Run the module as a script.").tag(config=True)
     gui = CaselessStrEnum(
         gui_keys,
         allow_none=True,
         help="Enable GUI event loop integration with any of {0}.".format(gui_keys),
     ).tag(config=True)
     matplotlib = MatplotlibBackendCaselessStrEnum(
         allow_none=True,
         help="""Configure matplotlib for interactive use with
-        the default matplotlib backend.""",
+        the default matplotlib backend. The exact options available
+        depend on what Matplotlib provides at runtime.""",
     ).tag(config=True)
     pylab = MatplotlibBackendCaselessStrEnum(
         allow_none=True,
         help="""Pre-load matplotlib and numpy for interactive use,
         selecting a particular matplotlib backend and loop integration.
+        The exact options available depend on what Matplotlib provides at runtime.
         """,
     ).tag(config=True)
     pylab_import_all = Bool(
         True,
         help="""If true, IPython will populate the user namespace with numpy, pylab, etc.
         and an ``import *`` is done from numpy and pylab, when using pylab mode.
 
         When False, pylab mode should not import any names into the user namespace.
         """,
     ).tag(config=True)
     ignore_cwd = Bool(
         False,
         help="""If True, IPython will not add the current working directory to sys.path.
         When False, the current working directory is added to sys.path, allowing imports
         of modules defined in the current directory."""
     ).tag(config=True)
     shell = Instance('IPython.core.interactiveshell.InteractiveShellABC',
                      allow_none=True)
     # whether interact-loop should start
     interact = Bool(True)
 
     user_ns = Instance(dict, args=None, allow_none=True)
     @observe('user_ns')
     def _user_ns_changed(self, change):
         if self.shell is not None:
             self.shell.user_ns = change['new']
             self.shell.init_user_ns()
 
     def init_path(self):
         """Add current working directory, '', to sys.path
 
         Unlike Python's default, we insert before the first `site-packages`
         or `dist-packages` directory,
         so that it is after the standard library.
 
         .. versionchanged:: 7.2
             Try to insert after the standard library, instead of first.
         .. versionchanged:: 8.0
             Allow optionally not including the current directory in sys.path
         """
         if '' in sys.path or self.ignore_cwd:
             return
         for idx, path in enumerate(sys.path):
             parent, last_part = os.path.split(path)
             if last_part in {'site-packages', 'dist-packages'}:
                 break
         else:
             # no site-packages or dist-packages found (?!)
             # back to original behavior of inserting at the front
             idx = 0
         sys.path.insert(idx, '')
 
     def init_shell(self):
         raise NotImplementedError("Override in subclasses")
 
     def init_gui_pylab(self):
         """Enable GUI event loop integration, taking pylab into account."""
         enable = False
         shell = self.shell
         if self.pylab:
             enable = lambda key: shell.enable_pylab(key, import_all=self.pylab_import_all)
             key = self.pylab
         elif self.matplotlib:
             enable = shell.enable_matplotlib
             key = self.matplotlib
         elif self.gui:
             enable = shell.enable_gui
             key = self.gui
 
         if not enable:
             return
 
         try:
             r = enable(key)
         except ImportError:
             self.log.warning("Eventloop or matplotlib integration failed. Is matplotlib installed?")
             self.shell.showtraceback()
             return
         except Exception:
             self.log.warning("GUI event loop or pylab initialization failed")
             self.shell.showtraceback()
             return
 
         if isinstance(r, tuple):
             gui, backend = r[:2]
             self.log.info("Enabling GUI event loop integration, "
                       "eventloop=%s, matplotlib=%s", gui, backend)
             if key == "auto":
                 print("Using matplotlib backend: %s" % backend)
         else:
             gui = r
             self.log.info("Enabling GUI event loop integration, "
                       "eventloop=%s", gui)
 
     def init_extensions(self):
         """Load all IPython extensions in IPythonApp.extensions.
 
         This uses the :meth:`ExtensionManager.load_extensions` to load all
         the extensions listed in ``self.extensions``.
         """
         try:
             self.log.debug("Loading IPython extensions...")
             extensions = (
                 self.default_extensions + self.extensions + self.extra_extensions
             )
             for ext in extensions:
                 try:
                     self.log.info("Loading IPython extension: %s", ext)
                     self.shell.extension_manager.load_extension(ext)
                 except:
                     if self.reraise_ipython_extension_failures:
                         raise
                     msg = ("Error in loading extension: {ext}\n"
                            "Check your config files in {location}".format(
                                ext=ext,
                                location=self.profile_dir.location
                            ))
                     self.log.warning(msg, exc_info=True)
         except:
             if self.reraise_ipython_extension_failures:
                 raise
             self.log.warning("Unknown error in loading extensions:", exc_info=True)
 
     def init_code(self):
         """run the pre-flight code, specified via exec_lines"""
         self._run_startup_files()
         self._run_exec_lines()
         self._run_exec_files()
 
         # Hide variables defined here from %who etc.
         if self.hide_initial_ns:
             self.shell.user_ns_hidden.update(self.shell.user_ns)
 
         # command-line execution (ipython -i script.py, ipython -m module)
         # should *not* be excluded from %whos
         self._run_cmd_line_code()
         self._run_module()
 
         # flush output, so itwon't be attached to the first cell
         sys.stdout.flush()
         sys.stderr.flush()
         self.shell._sys_modules_keys = set(sys.modules.keys())
 
     def _run_exec_lines(self):
         """Run lines of code in IPythonApp.exec_lines in the user's namespace."""
         if not self.exec_lines:
             return
         try:
             self.log.debug("Running code from IPythonApp.exec_lines...")
             for line in self.exec_lines:
                 try:
                     self.log.info("Running code in user namespace: %s" %
                                   line)
                     self.shell.run_cell(line, store_history=False)
                 except:
                     self.log.warning("Error in executing line in user "
                                   "namespace: %s" % line)
                     self.shell.showtraceback()
         except:
             self.log.warning("Unknown error in handling IPythonApp.exec_lines:")
             self.shell.showtraceback()
 
     def _exec_file(self, fname, shell_futures=False):
         try:
             full_filename = filefind(fname, [u'.', self.ipython_dir])
         except IOError:
             self.log.warning("File not found: %r"%fname)
             return
         # Make sure that the running script gets a proper sys.argv as if it
         # were run from a system shell.
         save_argv = sys.argv
         sys.argv = [full_filename] + self.extra_args[1:]
         try:
             if os.path.isfile(full_filename):
                 self.log.info("Running file in user namespace: %s" %
                               full_filename)
                 # Ensure that __file__ is always defined to match Python
                 # behavior.
                 with preserve_keys(self.shell.user_ns, '__file__'):
                     self.shell.user_ns['__file__'] = fname
                     if full_filename.endswith('.ipy') or full_filename.endswith('.ipynb'):
                         self.shell.safe_execfile_ipy(full_filename,
                                                      shell_futures=shell_futures)
                     else:
                         # default to python, even without extension
                         self.shell.safe_execfile(full_filename,
                                                  self.shell.user_ns,
                                                  shell_futures=shell_futures,
                                                  raise_exceptions=True)
         finally:
             sys.argv = save_argv
 
     def _run_startup_files(self):
         """Run files from profile startup directory"""
         startup_dirs = [self.profile_dir.startup_dir] + [
             os.path.join(p, 'startup') for p in chain(ENV_CONFIG_DIRS, SYSTEM_CONFIG_DIRS)
         ]
         startup_files = []
 
         if self.exec_PYTHONSTARTUP and os.environ.get('PYTHONSTARTUP', False) and \
                 not (self.file_to_run or self.code_to_run or self.module_to_run):
             python_startup = os.environ['PYTHONSTARTUP']
             self.log.debug("Running PYTHONSTARTUP file %s...", python_startup)
             try:
                 self._exec_file(python_startup)
             except:
                 self.log.warning("Unknown error in handling PYTHONSTARTUP file %s:", python_startup)
                 self.shell.showtraceback()
         for startup_dir in startup_dirs[::-1]:
             startup_files += glob.glob(os.path.join(startup_dir, '*.py'))
             startup_files += glob.glob(os.path.join(startup_dir, '*.ipy'))
         if not startup_files:
             return
 
         self.log.debug("Running startup files from %s...", startup_dir)
         try:
             for fname in sorted(startup_files):
                 self._exec_file(fname)
         except:
             self.log.warning("Unknown error in handling startup files:")
             self.shell.showtraceback()
 
     def _run_exec_files(self):
         """Run files from IPythonApp.exec_files"""
         if not self.exec_files:
             return
 
         self.log.debug("Running files in IPythonApp.exec_files...")
         try:
             for fname in self.exec_files:
                 self._exec_file(fname)
         except:
             self.log.warning("Unknown error in handling IPythonApp.exec_files:")
             self.shell.showtraceback()
 
     def _run_cmd_line_code(self):
         """Run code or file specified at the command-line"""
         if self.code_to_run:
             line = self.code_to_run
             try:
                 self.log.info("Running code given at command line (c=): %s" %
                               line)
                 self.shell.run_cell(line, store_history=False)
             except:
                 self.log.warning("Error in executing line in user namespace: %s" %
                               line)
                 self.shell.showtraceback()
                 if not self.interact:
                     self.exit(1)
 
         # Like Python itself, ignore the second if the first of these is present
         elif self.file_to_run:
             fname = self.file_to_run
             if os.path.isdir(fname):
                 fname = os.path.join(fname, "__main__.py")
             if not os.path.exists(fname):
                 self.log.warning("File '%s' doesn't exist", fname)
                 if not self.interact:
                     self.exit(2)
             try:
                 self._exec_file(fname, shell_futures=True)
             except:
                 self.shell.showtraceback(tb_offset=4)
                 if not self.interact:
                     self.exit(1)
 
     def _run_module(self):
         """Run module specified at the command-line."""
         if self.module_to_run:
             # Make sure that the module gets a proper sys.argv as if it were
             # run using `python -m`.
             save_argv = sys.argv
             sys.argv = [sys.executable] + self.extra_args
             try:
                 self.shell.safe_run_module(self.module_to_run,
                                            self.shell.user_ns)
             finally:
                 sys.argv = save_argv

docs/source/interactive/plotting.rst

@@ -1,67 +1,81 b''
 .. _plotting:
 
 Rich Outputs
 ------------
 
 One of the main feature of IPython when used as a kernel is its ability to
 show rich output. This means that object that can be representing as image,
 sounds, animation, (etc...) can be shown this way if the frontend support it.
 
 In order for this to be possible, you need to use the ``display()`` function,
 that should be available by default on IPython 5.4+ and 6.1+, or that you can
 import with ``from IPython.display import display``. Then use ``display(<your
 object>)`` instead of ``print()``, and if possible your object will be displayed
 with a richer representation. In the terminal of course, there won't be much
 difference as object are most of the time represented by text, but in notebook
 and similar interface you will get richer outputs.
 
 
+.. _matplotlib_magic:
+
 Plotting
 --------
 
 .. note::
 
     Starting with IPython 5.0 and matplotlib 2.0 you can avoid the use of
     IPython's specific magic and use
     ``matplotlib.pyplot.ion()``/``matplotlib.pyplot.ioff()`` which have the
     advantages of working outside of IPython as well.
 
 
 One major feature of the IPython kernel is the ability to display plots that 
 are the output of running code cells. The IPython kernel is designed to work 
 seamlessly with the matplotlib_ plotting library to provide this functionality.
 
 To set this up, before any plotting or import of matplotlib is performed you
-must execute the ``%matplotlib``  :ref:`magic command <magics_explained>`. This
+may execute the ``%matplotlib`` :ref:`magic command <magics_explained>`. This
 performs the necessary behind-the-scenes setup for IPython to work correctly
 hand in hand with ``matplotlib``; it does *not*, however, actually execute any
 Python ``import`` commands, that is, no names are added to the namespace.
 
-If the ``%matplotlib`` magic is called without an argument, the
-output of a plotting command is displayed using the default ``matplotlib``
-backend in a separate window. Alternatively, the backend can be explicitly
-requested using, for example::
+If you do not use the ``%matplotlib`` magic or you call it without an argument,
+the output of a plotting command is displayed using the default ``matplotlib``
+backend, which may be different depending on Operating System and whether
+running within Jupyter or not.
+
+Alternatively, the backend can be explicitly requested using, for example::
 
   %matplotlib gtk
 
-A particularly interesting backend, provided by IPython, is the ``inline``
-backend.  This is available only for the Jupyter Notebook and the
-Jupyter QtConsole.  It can be invoked as follows::
+The argument passed to the ``%matplotlib`` magic command may be the name of any
+backend understood by ``matplotlib`` or it may the name of a GUI loop such as
+``qt`` or ``osx``, in which case an appropriate backend supporting that GUI
+loop will be selected. To obtain a full list of all backends and GUI loops
+understood by ``matplotlib`` use ``%matplotlib --list``.
 
-  %matplotlib inline
+There are some specific backends that are used in the Jupyter ecosystem:
 
-With this backend, the output of plotting commands is displayed *inline* within
-frontends like the Jupyter notebook, directly below the code cell that produced
-it. The resulting plots will then also be stored in the notebook document.
+- The ``inline`` backend is provided by IPython and can be used in Jupyter Lab,
+  Notebook and QtConsole; it is the default backend when using Jupyter. The
+  outputs of plotting commands are displayed *inline* within frontends like
+  Jupyter Notebook, directly below the code cells that produced them.
+  The resulting plots will then also be stored in the notebook document.
 
-.. seealso::
+- The ``notebook`` or ``nbagg`` backend is built into ``matplotlib`` and can be
+  used with Jupyter ``notebook <7`` and ``nbclassic``. Plots are interactive so
+  they can be zoomed and panned.
 
-    `Plotting with Matplotlib`_  example notebook
+- The ``ipympl`` or ``widget`` backend is for use with Jupyter ``lab`` and
+  ``notebook >=7``. It is in a separate ``ipympl`` module that must be
+  installed using ``pip`` or ``conda`` in the usual manner. Plots are
+  interactive so they can be zoomed and panned.
 
+.. seealso::
 
-The matplotlib_ library also ships with ``%matplotlib notebook`` command that
-allows interactive figures if your environment allows it.
+    `Plotting with Matplotlib`_  example notebook
 
-See the matplotlib_ documentation for more information. 
+See the matplotlib_ documentation for more information, in particular the
+section on backends.
 
 .. include:: ../links.txt

docs/source/interactive/reference.rst

@@ -1,1037 +1,1017 b''
 =================
 IPython reference
 =================
 
 .. _command_line_options:
 
 Command-line usage
 ==================
 
 You start IPython with the command::
 
     $ ipython [options] files
 
 If invoked with no options, it executes the file and exits, passing the
 remaining arguments to the script, just as if you had specified the same
 command with python. You may need to specify `--` before args to be passed
 to the script, to prevent IPython from attempting to parse them.
 If you add the ``-i`` flag, it drops you into the interpreter while still
 acknowledging any options you may have set in your ``ipython_config.py``. This
 behavior is different from standard Python, which when called as python ``-i``
 will only execute one file and ignore your configuration setup.
 
 Please note that some of the configuration options are not available at the
 command line, simply because they are not practical here. Look into your
 configuration files for details on those. There are separate configuration files
 for each profile, and the files look like :file:`ipython_config.py` or
 :file:`ipython_config_{frontendname}.py`.  Profile directories look like
 :file:`profile_{profilename}` and are typically installed in the
 :envvar:`IPYTHONDIR` directory, which defaults to :file:`$HOME/.ipython`. For
 Windows users, :envvar:`HOME` resolves to :file:`C:\\Users\\{YourUserName}` in
 most instances.
 
 Command-line Options
 --------------------
 
 To see the options IPython accepts, use ``ipython --help`` (and you probably
 should run the output through a pager such as ``ipython --help | less`` for
 more convenient reading).  This shows all the options that have a single-word
 alias to control them, but IPython lets you configure all of its objects from
 the command-line by passing the full class name and a corresponding value; type
 ``ipython --help-all`` to see this full list.  For example::
 
     $ ipython --help-all
     <...snip...>
     --matplotlib=<CaselessStrEnum> (InteractiveShellApp.matplotlib)
         Default: None
-        Choices: ['auto', 'gtk', 'gtk3', 'gtk4', 'inline', 'nbagg', 'notebook', 'osx', 'qt', 'qt5', 'qt6', 'tk', 'wx']
+        Choices: ['auto', 'gtk3', 'gtk4', 'inline', 'nbagg', 'notebook', 'osx', 'qt', 'qt5', 'qt6', 'tk', 'wx']
         Configure matplotlib for interactive use with the default matplotlib
         backend.
     <...snip...>
 
 
 Indicate that the following::
 
    $ ipython --matplotlib qt
 
 
 is equivalent to::
 
    $ ipython --InteractiveShellApp.matplotlib='qt'
 
 Note that in the second form, you *must* use the equal sign, as the expression
 is evaluated as an actual Python assignment.  While in the above example the
 short form is more convenient, only the most common options have a short form,
 while any configurable variable in IPython can be set at the command-line by
 using the long form.  This long form is the same syntax used in the
 configuration files, if you want to set these options permanently.
 
 
 Interactive use
 ===============
 
 IPython is meant to work as a drop-in replacement for the standard interactive
 interpreter. As such, any code which is valid python should execute normally
 under IPython (cases where this is not true should be reported as bugs). It
 does, however, offer many features which are not available at a standard python
 prompt. What follows is a list of these.
 
 
 Caution for Windows users
 -------------------------
 
 Windows, unfortunately, uses the ``\`` character as a path separator. This is a
 terrible choice, because ``\`` also represents the escape character in most
 modern programming languages, including Python. For this reason, using '/'
 character is recommended if you have problems with ``\``.  However, in Windows
 commands '/' flags options, so you can not use it for the root directory. This
 means that paths beginning at the root must be typed in a contrived manner
 like: ``%copy \opt/foo/bar.txt \tmp``
 
 .. _magic:
 
 Magic command system
 --------------------
 
 IPython will treat any line whose first character is a % as a special
 call to a 'magic' function. These allow you to control the behavior of
 IPython itself, plus a lot of system-type features. They are all
 prefixed with a % character, but parameters are given without
 parentheses or quotes.
 
 Lines that begin with ``%%`` signal a *cell magic*: they take as arguments not
 only the rest of the current line, but all lines below them as well, in the
 current execution block.  Cell magics can in fact make arbitrary modifications
 to the input they receive, which need not even be valid Python code at all.
 They receive the whole block as a single string.
 
 As a line magic example, the :magic:`cd` magic works just like the OS command of
 the same name::
 
       In [8]: %cd
       /home/fperez
 
 The following uses the builtin :magic:`timeit` in cell mode::
 
   In [10]: %%timeit x = range(10000)
       ...: min(x)
       ...: max(x)
       ...:
   518 µs ± 4.39 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
 
 In this case, ``x = range(10000)`` is called as the line argument, and the
 block with ``min(x)`` and ``max(x)`` is called as the cell body.  The
 :magic:`timeit` magic receives both.
 
 If you have 'automagic' enabled (as it is by default), you don't need to type in
 the single ``%`` explicitly for line magics; IPython will scan its internal
 list of magic functions and call one if it exists. With automagic on you can
 then just type ``cd mydir`` to go to directory 'mydir'::
 
       In [9]: cd mydir
       /home/fperez/mydir
 
 Cell magics *always* require an explicit ``%%`` prefix, automagic
 calling only works for line magics.
 
 The automagic system has the lowest possible precedence in name searches, so
 you can freely use variables with the same names as magic commands. If a magic
 command is 'shadowed' by a variable, you will need the explicit ``%`` prefix to
 use it:
 
 .. sourcecode:: ipython
 
     In [1]: cd ipython     # %cd is called by automagic
     /home/fperez/ipython
 
     In [2]: cd=1 	   # now cd is just a variable
 
     In [3]: cd .. 	   # and doesn't work as a function anymore
     File "<ipython-input-3-9fedb3aff56c>", line 1
       cd ..
           ^
     SyntaxError: invalid syntax
 
 
     In [4]: %cd .. 	   # but %cd always works
     /home/fperez
 
     In [5]: del cd     # if you remove the cd variable, automagic works again
 
     In [6]: cd ipython
 
     /home/fperez/ipython
 
 Line magics, if they return a value, can be assigned to a variable using the
 syntax ``l = %sx ls`` (which in this particular case returns the result of `ls`
 as a python list). See :ref:`below <manual_capture>` for more information.
 
 Type ``%magic`` for more information, including a list of all available magic
 functions at any time and their docstrings. You can also type
 ``%magic_function_name?`` (see :ref:`below <dynamic_object_info>` for
 information on the '?' system) to get information about any particular magic
 function you are interested in.
 
 The API documentation for the :mod:`IPython.core.magic` module contains the full
 docstrings of all currently available magic commands.
 
 .. seealso::
 
    :doc:`magics`
      A list of the line and cell magics available in IPython by default
 
    :ref:`defining_magics`
      How to define and register additional magic functions
 
 
 Access to the standard Python help
 ----------------------------------
 
 Simply type ``help()`` to access Python's standard help system. You can
 also type ``help(object)`` for information about a given object, or
 ``help('keyword')`` for information on a keyword. You may need to configure your
 PYTHONDOCS environment variable for this feature to work correctly.
 
 .. _dynamic_object_info:
 
 Dynamic object information
 --------------------------
 
 Typing ``?word`` or ``word?`` prints detailed information about an object. If
 certain strings in the object are too long (e.g. function signatures) they get
 snipped in the center for brevity. This system gives access variable types and
 values, docstrings, function prototypes and other useful information.
 
 If the information will not fit in the terminal, it is displayed in a pager
 (``less`` if available, otherwise a basic internal pager).
 
 Typing ``??word`` or ``word??`` gives access to the full information, including
 the source code where possible. Long strings are not snipped.
 
 The following magic functions are particularly useful for gathering
 information about your working environment:
 
     * :magic:`pdoc` **<object>**: Print (or run through a pager if too long) the
       docstring for an object. If the given object is a class, it will
       print both the class and the constructor docstrings.
     * :magic:`pdef` **<object>**: Print the call signature for any callable
       object. If the object is a class, print the constructor information.
     * :magic:`psource` **<object>**: Print (or run through a pager if too long)
       the source code for an object.
     * :magic:`pfile` **<object>**: Show the entire source file where an object was
       defined via a pager, opening it at the line where the object
       definition begins.
     * :magic:`who`/:magic:`whos`: These functions give information about identifiers
       you have defined interactively (not things you loaded or defined
       in your configuration files). %who just prints a list of
       identifiers and %whos prints a table with some basic details about
       each identifier.
 
 The dynamic object information functions (?/??, ``%pdoc``,
 ``%pfile``, ``%pdef``, ``%psource``) work on object attributes, as well as
 directly on variables. For example, after doing ``import os``, you can use
 ``os.path.abspath??``.
 
 
 Command line completion
 +++++++++++++++++++++++
 
 At any time, hitting TAB will complete any available python commands or
 variable names, and show you a list of the possible completions if
 there's no unambiguous one. It will also complete filenames in the
 current directory if no python names match what you've typed so far.
 
 
 Search command history
 ++++++++++++++++++++++
 
 IPython provides two ways for searching through previous input and thus
 reduce the need for repetitive typing:
 
    1. Start typing, and then use the up and down arrow keys (or :kbd:`Ctrl-p`
       and :kbd:`Ctrl-n`) to search through only the history items that match
       what you've typed so far.
    2. Hit :kbd:`Ctrl-r`: to open a search prompt. Begin typing and the system
       searches your history for lines that contain what you've typed so
       far, completing as much as it can.
 
 IPython will save your input history when it leaves and reload it next
 time you restart it. By default, the history file is named
 :file:`.ipython/profile_{name}/history.sqlite`.
 
 Autoindent
 ++++++++++
 
 Starting with 5.0, IPython uses `prompt_toolkit` in place of ``readline``,
 it thus can recognize lines ending in ':' and indent the next line,
 while also un-indenting automatically after 'raise' or 'return',
 and support real multi-line editing as well as syntactic coloration
 during edition.
 
 This feature does not use the ``readline`` library anymore, so it will
 not honor your :file:`~/.inputrc` configuration (or whatever
 file your :envvar:`INPUTRC` environment variable points to).
 
 In particular if you want to change the input mode to ``vi``, you will need to
 set the ``TerminalInteractiveShell.editing_mode`` configuration  option of IPython.
 
 Session logging and restoring
 -----------------------------
 
 You can log all input from a session either by starting IPython with the
 command line switch ``--logfile=foo.py`` (see :ref:`here <command_line_options>`)
 or by activating the logging at any moment with the magic function :magic:`logstart`.
 
 Log files can later be reloaded by running them as scripts and IPython
 will attempt to 'replay' the log by executing all the lines in it, thus
 restoring the state of a previous session. This feature is not quite
 perfect, but can still be useful in many cases.
 
 The log files can also be used as a way to have a permanent record of
 any code you wrote while experimenting. Log files are regular text files
 which you can later open in your favorite text editor to extract code or
 to 'clean them up' before using them to replay a session.
 
 The :magic:`logstart` function for activating logging in mid-session is used as
 follows::
 
     %logstart [log_name [log_mode]]
 
 If no name is given, it defaults to a file named 'ipython_log.py' in your
 current working directory, in 'rotate' mode (see below).
 
 '%logstart name' saves to file 'name' in 'backup' mode. It saves your
 history up to that point and then continues logging.
 
 %logstart takes a second optional parameter: logging mode. This can be
 one of (note that the modes are given unquoted):
 
     * [over:] overwrite existing log_name.
     * [backup:] rename (if exists) to log_name~ and start log_name.
     * [append:] well, that says it.
     * [rotate:] create rotating logs log_name.1~, log_name.2~, etc.
 
 Adding the '-o' flag to '%logstart' magic (as in '%logstart -o [log_name [log_mode]]')
 will also include output from iPython in the log file.
 
 The :magic:`logoff` and :magic:`logon` functions allow you to temporarily stop and
 resume logging to a file which had previously been started with
 %logstart. They will fail (with an explanation) if you try to use them
 before logging has been started.
 
 .. _system_shell_access:
 
 System shell access
 -------------------
 
 Any input line beginning with a ``!`` character is passed verbatim (minus
 the ``!``, of course) to the underlying operating system. For example,
 typing ``!ls`` will run 'ls' in the current directory.
 
 .. _manual_capture:
 
 Manual capture of command output and magic output
 -------------------------------------------------
 
 You can assign the result of a system command to a Python variable with the
 syntax ``myfiles = !ls``. Similarly, the result of a magic (as long as it returns
 a value) can be assigned to a variable.  For example, the syntax ``myfiles = %sx ls``
 is equivalent to the above system command example (the :magic:`sx` magic runs a shell command
 and captures the output).  Each of these gets machine
 readable output from stdout (e.g. without colours), and splits on newlines. To
 explicitly get this sort of output without assigning to a variable, use two
 exclamation marks (``!!ls``) or the :magic:`sx` magic command without an assignment.
 (However, ``!!`` commands cannot be assigned to a variable.)
 
 The captured list in this example has some convenience features. ``myfiles.n`` or ``myfiles.s``
 returns a string delimited by newlines or spaces, respectively. ``myfiles.p``
 produces `path objects <http://pypi.python.org/pypi/path.py>`_ from the list items.
 See :ref:`string_lists` for details.
 
 IPython also allows you to expand the value of python variables when
 making system calls. Wrap variables or expressions in {braces}::
 
     In [1]: pyvar = 'Hello world'
     In [2]: !echo "A python variable: {pyvar}"
     A python variable: Hello world
     In [3]: import math
     In [4]: x = 8
     In [5]: !echo {math.factorial(x)}
     40320
 
 For simple cases, you can alternatively prepend $ to a variable name::
 
     In [6]: !echo $sys.argv
     [/home/fperez/usr/bin/ipython]
     In [7]: !echo "A system variable: $$HOME"  # Use $$ for literal $
     A system variable: /home/fperez
 
 Note that `$$` is used to represent a literal `$`.
 
 System command aliases
 ----------------------
 
 The :magic:`alias` magic function allows you to define magic functions which are in fact
 system shell commands. These aliases can have parameters.
 
 ``%alias alias_name cmd`` defines 'alias_name' as an alias for 'cmd'
 
 Then, typing ``alias_name params`` will execute the system command 'cmd
 params' (from your underlying operating system).
 
 You can also define aliases with parameters using ``%s`` specifiers (one per
 parameter). The following example defines the parts function as an
 alias to the command ``echo first %s second %s`` where each ``%s`` will be
 replaced by a positional parameter to the call to %parts::
 
     In [1]: %alias parts echo first %s second %s
     In [2]: parts A B
     first A second B
     In [3]: parts A
     ERROR: Alias <parts> requires 2 arguments, 1 given.
 
 If called with no parameters, :magic:`alias` prints the table of currently
 defined aliases.
 
 The :magic:`rehashx` magic allows you to load your entire $PATH as
 ipython aliases. See its docstring for further details.
 
 
 .. _dreload:
 
 Recursive reload
 ----------------
 
 The :mod:`IPython.lib.deepreload` module allows you to recursively reload a
 module: changes made to any of its dependencies will be reloaded without
 having to exit. To start using it, do::
 
     from IPython.lib.deepreload import reload as dreload
 
 
 Verbose and colored exception traceback printouts
 -------------------------------------------------
 
 IPython provides the option to see very detailed exception tracebacks,
 which can be especially useful when debugging large programs. You can
 run any Python file with the %run function to benefit from these
 detailed tracebacks. Furthermore, both normal and verbose tracebacks can
 be colored (if your terminal supports it) which makes them much easier
 to parse visually.
 
 See the magic :magic:`xmode` and :magic:`colors` functions for details.
 
 These features are basically a terminal version of Ka-Ping Yee's cgitb
 module, now part of the standard Python library.
 
 
 .. _input_caching:
 
 Input caching system
 --------------------
 
 IPython offers numbered prompts (In/Out) with input and output caching
 (also referred to as 'input history'). All input is saved and can be
 retrieved as variables (besides the usual arrow key recall), in
 addition to the :magic:`rep` magic command that brings a history entry
 up for editing on the next command line.
 
 The following variables always exist:
 
 * ``_i``, ``_ii``, ``_iii``: store previous, next previous and next-next
   previous inputs.
 
 * ``In``, ``_ih`` : a list of all inputs; ``_ih[n]`` is the input from line
   ``n``. If you overwrite In with a variable of your own, you can remake the
   assignment to the internal list with a simple ``In=_ih``.
 
 Additionally, global variables named ``_i<n>`` are dynamically created (``<n>``
 being the prompt counter), so ``_i<n> == _ih[<n>] == In[<n>]``.
 
 For example, what you typed at prompt 14 is available as ``_i14``, ``_ih[14]``
 and ``In[14]``.
 
 This allows you to easily cut and paste multi line interactive prompts
 by printing them out: they print like a clean string, without prompt
 characters. You can also manipulate them like regular variables (they
 are strings), modify or exec them.
 
 You can also re-execute multiple lines of input easily by using the magic
 :magic:`rerun` or :magic:`macro` functions. The macro system also allows you to
 re-execute previous lines which include magic function calls (which require
 special processing). Type %macro? for more details on the macro system.
 
 A history function :magic:`history` allows you to see any part of your input
 history by printing a range of the _i variables.
 
 You can also search ('grep') through your history by typing
 ``%hist -g somestring``. This is handy for searching for URLs, IP addresses,
 etc. You can bring history entries listed by '%hist -g' up for editing
 with the %recall command, or run them immediately with :magic:`rerun`.
 
 .. _output_caching:
 
 Output caching system
 ---------------------
 
 For output that is returned from actions, a system similar to the input
 cache exists but using _ instead of _i. Only actions that produce a
 result (NOT assignments, for example) are cached. If you are familiar
 with Mathematica, IPython's _ variables behave exactly like
 Mathematica's % variables.
 
 The following variables always exist:
 
     * [_] (a single underscore): stores previous output, like Python's
       default interpreter.
     * [__] (two underscores): next previous.
     * [___] (three underscores): next-next previous.
 
 Additionally, global variables named _<n> are dynamically created (<n>
 being the prompt counter), such that the result of output <n> is always
 available as _<n> (don't use the angle brackets, just the number, e.g.
 ``_21``).
 
 These variables are also stored in a global dictionary (not a
 list, since it only has entries for lines which returned a result)
 available under the names _oh and Out (similar to _ih and In). So the
 output from line 12 can be obtained as ``_12``, ``Out[12]`` or ``_oh[12]``. If you
 accidentally overwrite the Out variable you can recover it by typing
 ``Out=_oh`` at the prompt.
 
 This system obviously can potentially put heavy memory demands on your
 system, since it prevents Python's garbage collector from removing any
 previously computed results. You can control how many results are kept
 in memory with the configuration option ``InteractiveShell.cache_size``.
 If you set it to 0, output caching is disabled. You can also use the :magic:`reset`
 and :magic:`xdel` magics to clear large items from memory.
 
 Directory history
 -----------------
 
 Your history of visited directories is kept in the global list _dh, and
 the magic :magic:`cd` command can be used to go to any entry in that list. The
 :magic:`dhist` command allows you to view this history. Do ``cd -<TAB>`` to
 conveniently view the directory history.
 
 
 Automatic parentheses and quotes
 --------------------------------
 
 These features were adapted from Nathan Gray's LazyPython. They are
 meant to allow less typing for common situations.
 
 Callable objects (i.e. functions, methods, etc) can be invoked like this
 (notice the commas between the arguments)::
 
     In [1]: callable_ob arg1, arg2, arg3
     ------> callable_ob(arg1, arg2, arg3)
 
 .. note::
    This feature is disabled by default. To enable it, use the ``%autocall``
    magic command. The commands below with special prefixes will always work,
    however.
 
 You can force automatic parentheses by using '/' as the first character
 of a line. For example::
 
     In [2]: /globals # becomes 'globals()'
 
 Note that the '/' MUST be the first character on the line! This won't work::
 
     In [3]: print /globals # syntax error
 
 In most cases the automatic algorithm should work, so you should rarely
 need to explicitly invoke /. One notable exception is if you are trying
 to call a function with a list of tuples as arguments (the parenthesis
 will confuse IPython)::
 
     In [4]: zip (1,2,3),(4,5,6) # won't work
 
 but this will work::
 
     In [5]: /zip (1,2,3),(4,5,6)
     ------> zip ((1,2,3),(4,5,6))
     Out[5]: [(1, 4), (2, 5), (3, 6)]
 
 IPython tells you that it has altered your command line by displaying
 the new command line preceded by ``--->``.
 
 You can force automatic quoting of a function's arguments by using ``,``
 or ``;`` as the first character of a line. For example::
 
     In [1]: ,my_function /home/me  # becomes my_function("/home/me")
 
 If you use ';' the whole argument is quoted as a single string, while ',' splits
 on whitespace::
 
     In [2]: ,my_function a b c    # becomes my_function("a","b","c")
 
     In [3]: ;my_function a b c    # becomes my_function("a b c")
 
 Note that the ',' or ';' MUST be the first character on the line! This
 won't work::
 
     In [4]: x = ,my_function /home/me # syntax error
 
 IPython as your default Python environment
 ==========================================
 
 Python honors the environment variable :envvar:`PYTHONSTARTUP` and will
 execute at startup the file referenced by this variable. If you put the
 following code at the end of that file, then IPython will be your working
 environment anytime you start Python::
 
     import os, IPython
     os.environ['PYTHONSTARTUP'] = ''  # Prevent running this again
     IPython.start_ipython()
     raise SystemExit
 
 The ``raise SystemExit`` is needed to exit Python when
 it finishes, otherwise you'll be back at the normal Python ``>>>``
 prompt.
 
 This is probably useful to developers who manage multiple Python
 versions and don't want to have correspondingly multiple IPython
 versions. Note that in this mode, there is no way to pass IPython any
 command-line options, as those are trapped first by Python itself.
 
 .. _Embedding:
 
 Embedding IPython
 =================
 
 You can start a regular IPython session with
 
 .. sourcecode:: python
 
     import IPython
     IPython.start_ipython(argv=[])
 
 at any point in your program.  This will load IPython configuration,
 startup files, and everything, just as if it were a normal IPython session.
 For information on setting configuration options when running IPython from
 python, see :ref:`configure_start_ipython`.
 
 It is also possible to embed an IPython shell in a namespace in your Python
 code. This allows you to evaluate dynamically the state of your code, operate
 with your variables, analyze them, etc. For example, if you run the following
 code snippet::
 
   import IPython
 
   a = 42
   IPython.embed()
 
 and within the IPython shell, you reassign `a` to `23` to do further testing of 
 some sort, you can then exit::
 
   >>> IPython.embed()
   Python 3.6.2 (default, Jul 17 2017, 16:44:45) 
   Type 'copyright', 'credits' or 'license' for more information
   IPython 6.2.0.dev -- An enhanced Interactive Python. Type '?' for help.
 
   In [1]: a = 23
 
   In [2]: exit()
 
 Once you exit and print `a`, the value 23 will be shown::
 
 
   In: print(a)
   23
 
 It's important to note that the code run in the embedded IPython shell will 
 *not* change the state of your code and variables, **unless** the shell is 
 contained within the global namespace. In the above example, `a` is changed 
 because this is true.
 
 To further exemplify this, consider the following example::
 
   import IPython
   def do():
       a = 42
       print(a)
       IPython.embed()
       print(a)
 
 Now if call the function and complete the state changes as we did above, the
 value `42` will be printed. Again, this is because it's not in the global
 namespace:: 
 
   do()
 
 Running a file with the above code can lead to the following session::
 
   >>> do()
   42
   Python 3.6.2 (default, Jul 17 2017, 16:44:45) 
   Type 'copyright', 'credits' or 'license' for more information
   IPython 6.2.0.dev -- An enhanced Interactive Python. Type '?' for help.
 
   In [1]: a = 23
 
   In [2]: exit()
   42
 
 .. note::
 
   At present, embedding IPython cannot be done from inside IPython.
   Run the code samples below outside IPython.
 
 This feature allows you to easily have a fully functional python
 environment for doing object introspection anywhere in your code with a
 simple function call. In some cases a simple print statement is enough,
 but if you need to do more detailed analysis of a code fragment this
 feature can be very valuable.
 
 It can also be useful in scientific computing situations where it is
 common to need to do some automatic, computationally intensive part and
 then stop to look at data, plots, etc.
 Opening an IPython instance will give you full access to your data and
 functions, and you can resume program execution once you are done with
 the interactive part (perhaps to stop again later, as many times as
 needed).
 
 The following code snippet is the bare minimum you need to include in
 your Python programs for this to work (detailed examples follow later)::
 
     from IPython import embed
 
     embed() # this call anywhere in your program will start IPython
 
 You can also embed an IPython *kernel*, for use with qtconsole, etc. via
 ``IPython.embed_kernel()``. This should work the same way, but you can
 connect an external frontend (``ipython qtconsole`` or ``ipython console``),
 rather than interacting with it in the terminal.
 
 You can run embedded instances even in code which is itself being run at
 the IPython interactive prompt with '%run <filename>'. Since it's easy
 to get lost as to where you are (in your top-level IPython or in your
 embedded one), it's a good idea in such cases to set the in/out prompts
 to something different for the embedded instances. The code examples
 below illustrate this.
 
 You can also have multiple IPython instances in your program and open
 them separately, for example with different options for data
 presentation. If you close and open the same instance multiple times,
 its prompt counters simply continue from each execution to the next.
 
 Please look at the docstrings in the :mod:`~IPython.frontend.terminal.embed`
 module for more details on the use of this system.
 
 The following sample file illustrating how to use the embedding
 functionality is provided in the examples directory as embed_class_long.py.
 It should be fairly self-explanatory:
 
 .. literalinclude:: ../../../examples/Embedding/embed_class_long.py
     :language: python
 
 Once you understand how the system functions, you can use the following
 code fragments in your programs which are ready for cut and paste:
 
 .. literalinclude:: ../../../examples/Embedding/embed_class_short.py
     :language: python
 
 Using the Python debugger (pdb)
 ===============================
 
 Running entire programs via pdb
 -------------------------------
 
 pdb, the Python debugger, is a powerful interactive debugger which
 allows you to step through code, set breakpoints, watch variables,
 etc.  IPython makes it very easy to start any script under the control
 of pdb, regardless of whether you have wrapped it into a 'main()'
 function or not. For this, simply type ``%run -d myscript`` at an
 IPython prompt. See the :magic:`run` command's documentation for more details, including
 how to control where pdb will stop execution first.
 
 For more information on the use of the pdb debugger, see :ref:`debugger-commands`
 in the Python documentation.
 
 IPython extends the debugger with a few useful additions, like coloring of
 tracebacks. The debugger will adopt the color scheme selected for IPython.
 
 The ``where`` command has also been extended to take as argument the number of
 context line to show. This allows to a many line of context on shallow stack trace:
 
 .. code::
 
     In [5]: def foo(x):
     ...:     1
     ...:     2
     ...:     3
     ...:     return 1/x+foo(x-1)
     ...:     5
     ...:     6
     ...:     7
     ...:
 
     In[6]: foo(1)
     # ...
     ipdb> where 8
     <ipython-input-6-9e45007b2b59>(1)<module>
     ----> 1 foo(1)
 
     <ipython-input-5-7baadc3d1465>(5)foo()
         1 def foo(x):
         2     1
         3     2
         4     3
     ----> 5     return 1/x+foo(x-1)
         6     5
         7     6
         8     7
 
     > <ipython-input-5-7baadc3d1465>(5)foo()
         1 def foo(x):
         2     1
         3     2
         4     3
     ----> 5     return 1/x+foo(x-1)
         6     5
         7     6
         8     7
 
 
 And less context on shallower Stack Trace:
 
 .. code::
 
     ipdb> where 1
     <ipython-input-13-afa180a57233>(1)<module>
     ----> 1 foo(7)
 
     <ipython-input-5-7baadc3d1465>(5)foo()
     ----> 5     return 1/x+foo(x-1)
 
     <ipython-input-5-7baadc3d1465>(5)foo()
     ----> 5     return 1/x+foo(x-1)
 
     <ipython-input-5-7baadc3d1465>(5)foo()
     ----> 5     return 1/x+foo(x-1)
 
     <ipython-input-5-7baadc3d1465>(5)foo()
     ----> 5     return 1/x+foo(x-1)
 
 
 Post-mortem debugging
 ---------------------
 
 Going into a debugger when an exception occurs can be
 extremely useful in order to find the origin of subtle bugs, because pdb
 opens up at the point in your code which triggered the exception, and
 while your program is at this point 'dead', all the data is still
 available and you can walk up and down the stack frame and understand
 the origin of the problem.
 
 You can use the :magic:`debug` magic after an exception has occurred to start
 post-mortem debugging. IPython can also call debugger every time your code
 triggers an uncaught exception. This feature can be toggled with the :magic:`pdb` magic
 command, or you can start IPython with the ``--pdb`` option.
 
 For a post-mortem debugger in your programs outside IPython,
 put the following lines toward the top of your 'main' routine::
 
     import sys
     from IPython.core import ultratb
     sys.excepthook = ultratb.FormattedTB(mode='Verbose',
     color_scheme='Linux', call_pdb=1)
 
 The mode keyword can be either 'Verbose' or 'Plain', giving either very
 detailed or normal tracebacks respectively. The color_scheme keyword can
 be one of 'NoColor', 'Linux' (default) or 'LightBG'. These are the same
 options which can be set in IPython with ``--colors`` and ``--xmode``.
 
 This will give any of your programs detailed, colored tracebacks with
 automatic invocation of pdb.
 
 .. _pasting_with_prompts:
 
 Pasting of code starting with Python or IPython prompts
 =======================================================
 
 IPython is smart enough to filter out input prompts, be they plain Python ones
 (``>>>`` and ``...``) or IPython ones (``In [N]:`` and ``...:``).  You can
 therefore copy and paste from existing interactive sessions without worry.
 
 The following is a 'screenshot' of how things work, copying an example from the
 standard Python tutorial::
 
     In [1]: >>> # Fibonacci series:
 
     In [2]: ... # the sum of two elements defines the next
 
     In [3]: ... a, b = 0, 1
 
     In [4]: >>> while b < 10:
        ...:     ...     print(b)
        ...:     ...     a, b = b, a+b
        ...:
     1
     1
     2
     3
     5
     8
 
 And pasting from IPython sessions works equally well::
 
     In [1]: In [5]: def f(x):
        ...:        ...:     "A simple function"
        ...:        ...:     return x**2
        ...:    ...:
 
     In [2]: f(3)
     Out[2]: 9
 
 .. _gui_support:
 
 GUI event loop support
 ======================
 
 IPython has excellent support for working interactively with Graphical User
 Interface (GUI) toolkits, such as wxPython, PyQt/PySide, PyGTK and Tk. This is
 implemented by running the toolkit's event loop while IPython is waiting for
 input.
 
 For users, enabling GUI event loop integration is simple.  You simple use the
 :magic:`gui` magic as follows::
 
     %gui [GUINAME]
 
 With no arguments, ``%gui`` removes all GUI support.  Valid ``GUINAME``
-arguments include ``wx``, ``qt``, ``qt5``, ``qt6``, ``gtk``, ``gtk3`` ``gtk4``, and
+arguments include ``wx``, ``qt``, ``qt5``, ``qt6``, ``gtk3`` ``gtk4``, and
 ``tk``.
 
 Thus, to use wxPython interactively and create a running :class:`wx.App`
 object, do::
 
     %gui wx
 
 You can also start IPython with an event loop set up using the `--gui`
 flag::
 
     $ ipython --gui=qt
 
 For information on IPython's matplotlib_ integration (and the ``matplotlib``
 mode) see :ref:`this section <matplotlib_support>`.
 
 For developers that want to integrate additional event loops with IPython, see
 :doc:`/config/eventloops`.
 
 When running inside IPython with an integrated event loop, a GUI application
 should *not* start its own event loop. This means that applications that are
 meant to be used both
 in IPython and as standalone apps need to have special code to detects how the
 application is being run. We highly recommend using IPython's support for this.
 Since the details vary slightly between toolkits, we point you to the various
 examples in our source directory :file:`examples/IPython Kernel/gui/` that
 demonstrate these capabilities.
 
 PyQt and PySide
 ---------------
 
 .. attempt at explanation of the complete mess that is Qt support
 
 When you use ``--gui=qt`` or ``--matplotlib=qt``, IPython can work with either
 PyQt or PySide.  ``qt`` implies "use the latest version available", and it favors
-PyQt over PySide. To request a specific version, use ``qt5`` or ``qt6``. Note that
-Qt4 is not supported with the ``--gui`` switch (and has not been for some time now).
+PyQt over PySide. To request a specific version, use ``qt5`` or ``qt6``.
 
-If specified, IPython will respect the environment variable ``QT_API`` used
-by ETS.  ETS 4.0 also works with both PyQt4 and PySide, but it requires
-PyQt4 to use its v2 API.  So if ``QT_API=pyside`` PySide will be used,
-and if ``QT_API=pyqt`` then PyQt4 will be used *with the v2 API* for
-QString and QVariant, so ETS codes like MayaVi will also work with IPython.
-
-If you launch IPython in matplotlib mode with ``ipython --matplotlib=qt``,
-then IPython will ask matplotlib which Qt library to use (only if QT_API is
-*not set*), via the 'backend.qt4' rcParam.  If matplotlib is version 1.0.1 or
-older, then IPython will always use PyQt4 without setting the v2 APIs, since
-neither v2 PyQt nor PySide work.
-
-.. warning::
-
-    Note that this means for ETS 4 to work with PyQt4, ``QT_API`` *must* be set
-    to work with IPython's qt integration, because otherwise PyQt4 will be
-    loaded in an incompatible mode.
-
-    It also means that you must *not* have ``QT_API`` set if you want to
-    use ``--gui=qt`` with code that requires PyQt4 API v1.
+If specified, IPython will respect the environment variable ``QT_API``. If
+``QT_API`` is not specified and you launch IPython in matplotlib mode with
+``ipython --matplotlib=qt`` then IPython will ask matplotlib which Qt library
+to use. See the matplotlib_ documentation on ``QT_API`` for further details.
 
 
 .. _matplotlib_support:
 
 Plotting with matplotlib
 ========================
 
 matplotlib_ provides high quality 2D and 3D plotting for Python. matplotlib_
 can produce plots on screen using a variety of GUI toolkits, including Tk,
-PyGTK, PyQt4 and wxPython. It also provides a number of commands useful for
+PyGTK, PyQt6 and wxPython. It also provides a number of commands useful for
 scientific computing, all with a syntax compatible with that of the popular
 Matlab program.
 
 To start IPython with matplotlib support, use the ``--matplotlib`` switch. If
 IPython is already running, you can run the :magic:`matplotlib` magic.  If no
 arguments are given, IPython will automatically detect your choice of
-matplotlib backend.  You can also request a specific backend with
-``%matplotlib backend``, where ``backend`` must be one of: 'tk', 'qt', 'wx',
-'gtk', 'osx'.  In the web notebook and Qt console, 'inline' is also a valid
-backend value, which produces static figures inlined inside the application
-window instead of matplotlib's interactive figures that live in separate
-windows.
+matplotlib backend. For information on matplotlib backends see
+:ref:`matplotlib_magic`.
+
 
 .. _interactive_demos:
 
 Interactive demos with IPython
 ==============================
 
 IPython ships with a basic system for running scripts interactively in
 sections, useful when presenting code to audiences. A few tags embedded
 in comments (so that the script remains valid Python code) divide a file
 into separate blocks, and the demo can be run one block at a time, with
 IPython printing (with syntax highlighting) the block before executing
 it, and returning to the interactive prompt after each block. The
 interactive namespace is updated after each block is run with the
 contents of the demo's namespace.
 
 This allows you to show a piece of code, run it and then execute
 interactively commands based on the variables just created. Once you
 want to continue, you simply execute the next block of the demo. The
 following listing shows the markup necessary for dividing a script into
 sections for execution as a demo:
 
 .. literalinclude:: ../../../examples/IPython Kernel/example-demo.py
     :language: python
 
 In order to run a file as a demo, you must first make a Demo object out
 of it. If the file is named myscript.py, the following code will make a
 demo::
 
     from IPython.lib.demo import Demo
 
     mydemo = Demo('myscript.py')
 
 This creates the mydemo object, whose blocks you run one at a time by
 simply calling the object with no arguments. Then call it to run each step
 of the demo::
 
     mydemo()
 
 Demo objects can be
 restarted, you can move forward or back skipping blocks, re-execute the
 last block, etc. See the :mod:`IPython.lib.demo` module and the
 :class:`~IPython.lib.demo.Demo` class for details.
 
 Limitations: These demos are limited to
 fairly simple uses. In particular, you cannot break up sections within
 indented code (loops, if statements, function definitions, etc.)
 Supporting something like this would basically require tracking the
 internal execution state of the Python interpreter, so only top-level
 divisions are allowed. If you want to be able to open an IPython
 instance at an arbitrary point in a program, you can use IPython's
 :ref:`embedding facilities <Embedding>`.
 
 .. include:: ../links.txt