I would like to start using the matplotlib OO interface more, as I would prefer to use this when interactive plotting is not needed. It it slightly faster, and behaves more intuitively in terms of reference counting (pyplot keeps a reference to each figure, meaning that if figures are not closed by pyplot, memory goes out of control).

The reason I don't use it is because it's not easy to remember all the set-up of the canvas and figure:

from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure

fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(1, 1, 1)
ax.scatter(np.random.random(10), np.random.random(10))
fig.savefig('test.png')

So I was wondering whether it would be possible to make Figure more intelligent in terms of canvas? The 'ideal' API in my mind would be:

from matplotlib.figure import Figure

fig = Figure()
ax = fig.add_subplot(1, 1, 1)
ax.scatter(np.random.random(10), np.random.random(10))
fig.savefig('test.png')

i.e. I want the figure to just use the default backend (since this is set at the root level of matplotlib, not pyplot). So I would expect the following to work:

import matplotlib
matplotlib.use('Agg')
from matplotlib.figure import Figure

fig = Figure()
ax = fig.add_subplot(1, 1, 1)
ax.scatter(np.random.random(10), np.random.random(10))
fig.savefig('test.png')

and to use the non-interactive Agg backend.

Is this something that has been considered before?