New upstream version 0.1.6

LICENSE

 BSD 3-Clause License
 
-Copyright (c) 2019,
+Copyright (c) 2019-2022, IPython Development Team.
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

README.md

 # Matplotlib Inline Back-end for IPython and Jupyter
 
+This package provides support for matplotlib to display figures directly inline in the Jupyter notebook and related clients, as shown below.
+
 ## Installation
 
 With conda:
 
 ```bash
-conda install -c conda-forge notebook matplotlib
+conda install -c conda-forge matplotlib-inline
 ```
 
 With pip:
 
 ```bash
-pip install notebook matplotlib
+pip install matplotlib-inline
 ```
 
 ## Usage
 
-This package is included in IPython and can be used in a Jupyter Notebook:
+Note that in current versions of JupyterLab and Jupyter Notebook, the explicit use of the `%matplotlib inline` directive is not needed anymore, though other third-party clients may still require it.
+
+This will produce a figure immediately below:
 
 ```python
 %matplotlib inline
@@ -28,3 +32,7 @@ x = np.linspace(0, 3*np.pi, 500)
 plt.plot(x, np.sin(x**2))
 plt.title('A simple chirp');
 ```
+
+## License
+
+Licensed under the terms of the BSD 3-Clause License, by the IPython Development Team (see `LICENSE` file).

matplotlib_inline/__init__.py

+from . import backend_inline, config  # noqa
+__version__ = "0.1.6"  # noqa

matplotlib_inline/backend_inline.py

@@ -4,13 +4,11 @@
 # Distributed under the terms of the BSD 3-Clause License.
 
 import matplotlib
-from matplotlib.backends.backend_agg import (  # noqa
-    new_figure_manager,
-    FigureCanvasAgg,
-    new_figure_manager_given_figure,
-)
 from matplotlib import colors
+from matplotlib.backends import backend_agg
+from matplotlib.backends.backend_agg import FigureCanvasAgg
 from matplotlib._pylab_helpers import Gcf
+from matplotlib.figure import Figure
 
 from IPython.core.interactiveshell import InteractiveShell
 from IPython.core.getipython import get_ipython
@@ -20,6 +18,57 @@ from IPython.display import display
 from .config import InlineBackend
 
 
+def new_figure_manager(num, *args, FigureClass=Figure, **kwargs):
+    """
+    Return a new figure manager for a new figure instance.
+
+    This function is part of the API expected by Matplotlib backends.
+    """
+    return new_figure_manager_given_figure(num, FigureClass(*args, **kwargs))
+
+
+def new_figure_manager_given_figure(num, figure):
+    """
+    Return a new figure manager for a given figure instance.
+
+    This function is part of the API expected by Matplotlib backends.
+    """
+    manager = backend_agg.new_figure_manager_given_figure(num, figure)
+
+    # Hack: matplotlib FigureManager objects in interacive backends (at least
+    # in some of them) monkeypatch the figure object and add a .show() method
+    # to it.  This applies the same monkeypatch in order to support user code
+    # that might expect `.show()` to be part of the official API of figure
+    # objects.  For further reference:
+    # https://github.com/ipython/ipython/issues/1612
+    # https://github.com/matplotlib/matplotlib/issues/835
+
+    if not hasattr(figure, 'show'):
+        # Queue up `figure` for display
+        figure.show = lambda *a: display(
+            figure, metadata=_fetch_figure_metadata(figure))
+
+    # If matplotlib was manually set to non-interactive mode, this function
+    # should be a no-op (otherwise we'll generate duplicate plots, since a user
+    # who set ioff() manually expects to make separate draw/show calls).
+    if not matplotlib.is_interactive():
+        return manager
+
+    # ensure current figure will be drawn, and each subsequent call
+    # of draw_if_interactive() moves the active figure to ensure it is
+    # drawn last
+    try:
+        show._to_draw.remove(figure)
+    except ValueError:
+        # ensure it only appears in the draw list once
+        pass
+    # Queue up the figure for drawing in next show() call
+    show._to_draw.append(figure)
+    show._draw_called = True
+
+    return manager
+
+
 def show(close=None, block=None):
     """Show all figures as SVG/PNG payloads sent to the IPython clients.
 
@@ -56,51 +105,6 @@ show._draw_called = False
 show._to_draw = []
 
 
-def draw_if_interactive():
-    """
-    Is called after every pylab drawing command
-    """
-    # signal that the current active figure should be sent at the end of
-    # execution.  Also sets the _draw_called flag, signaling that there will be
-    # something to send.  At the end of the code execution, a separate call to
-    # flush_figures() will act upon these values
-    manager = Gcf.get_active()
-    if manager is None:
-        return
-    fig = manager.canvas.figure
-
-    # Hack: matplotlib FigureManager objects in interacive backends (at least
-    # in some of them) monkeypatch the figure object and add a .show() method
-    # to it.  This applies the same monkeypatch in order to support user code
-    # that might expect `.show()` to be part of the official API of figure
-    # objects.
-    # For further reference:
-    # https://github.com/ipython/ipython/issues/1612
-    # https://github.com/matplotlib/matplotlib/issues/835
-
-    if not hasattr(fig, 'show'):
-        # Queue up `fig` for display
-        fig.show = lambda *a: display(fig, metadata=_fetch_figure_metadata(fig))
-
-    # If matplotlib was manually set to non-interactive mode, this function
-    # should be a no-op (otherwise we'll generate duplicate plots, since a user
-    # who set ioff() manually expects to make separate draw/show calls).
-    if not matplotlib.is_interactive():
-        return
-
-    # ensure current figure will be drawn, and each subsequent call
-    # of draw_if_interactive() moves the active figure to ensure it is
-    # drawn last
-    try:
-        show._to_draw.remove(fig)
-    except ValueError:
-        # ensure it only appears in the draw list once
-        pass
-    # Queue up the figure for drawing in next show() call
-    show._to_draw.append(fig)
-    show._draw_called = True
-
-
 def flush_figures():
     """Send all figures that changed
 
@@ -115,19 +119,20 @@ def flush_figures():
     if not show._draw_called:
         return
 
-    if InlineBackend.instance().close_figures:
-        # ignore the tracking, just draw and close all figures
-        try:
-            return show(True)
-        except Exception as e:
-            # safely show traceback if in IPython, else raise
-            ip = get_ipython()
-            if ip is None:
-                raise e
-            else:
-                ip.showtraceback()
-                return
     try:
+        if InlineBackend.instance().close_figures:
+            # ignore the tracking, just draw and close all figures
+            try:
+                return show(True)
+            except Exception as e:
+                # safely show traceback if in IPython, else raise
+                ip = get_ipython()
+                if ip is None:
+                    raise e
+                else:
+                    ip.showtraceback()
+                    return
+
         # exclude any figures that were closed:
         active = set([fm.canvas.figure for fm in Gcf.get_all_fig_managers()])
         for fig in [fig for fig in show._to_draw if fig in active]:

matplotlib_inline/config.py

@@ -32,26 +32,19 @@ class InlineBackendConfig(SingletonConfigurable):
 class InlineBackend(InlineBackendConfig):
     """An object to store configuration of the inline backend."""
 
-    # The typical default figure size is too large for inline use,
-    # so we shrink the figure size to 6x4, and tweak fonts to
-    # make that fit.
+    # While we are deprecating overriding matplotlib defaults out of the
+    # box, this structure should remain here (empty) for API compatibility
+    # and the use of other tools that may need it. Specifically Spyder takes
+    # advantage of it.
+    # See https://github.com/ipython/ipython/issues/10383 for details.
     rc = Dict(
-        {
-            'figure.figsize': (6.0, 4.0),
-            # play nicely with white background in the Qt and notebook frontend
-            'figure.facecolor': (1, 1, 1, 0),
-            'figure.edgecolor': (1, 1, 1, 0),
-            # 12pt labels get cutoff on 6x4 logplots, so use 10pt.
-            'font.size': 10,
-            # 72 dpi matches SVG/qtconsole
-            # this only affects PNG export, as SVG has no dpi setting
-            'figure.dpi': 72,
-            # 10pt still needs a little more room on the xlabel:
-            'figure.subplot.bottom': .125
-        },
-        help="""Subset of matplotlib rcParams that should be different for the
-        inline backend."""
-    ).tag(config=True)
+        {},
+        help="""Dict to manage matplotlib configuration defaults in the inline
+        backend. As of v0.1.4 IPython/Jupyter do not override defaults out of
+        the box, but third-party tools may use it to manage rc data. To change
+        personal defaults for matplotlib,  use matplotlib's configuration
+        tools, or customize this class in your `ipython_config.py` file for
+        IPython/Jupyter-specific usage.""").tag(config=True)
 
     figure_formats = Set(
         {'png'},

setup.cfg

 [metadata]
 name = matplotlib-inline
-version = 0.1.3
+version = attr: matplotlib_inline.__version__
 description = Inline Matplotlib backend for Jupyter
+long_description = file: README.md, LICENSE
+long_description_content_type = text/markdown
 author = IPython Development Team
 author_email = ipython-dev@scipy.org
 url = https://github.com/ipython/matplotlib-inline
@@ -27,3 +29,4 @@ classifiers =
     Programming Language :: Python :: 3.7
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.10