A simple Python script illustrating the architecture of matplotlib http://www.aosabook.org/en/matplotlib.html

architecture_of_matplotlib.py

# A simple Python script illustrating the architecture of matplotlib.
# It defines the backend, connects a Figure to it,
#  uses the array library numpy to create 10,000 normally distributed random
#  numbers, and plots a histogram of these.
# http://www.aosabook.org/en/matplotlib.html

# Import the FigureCanvas from the backend of your choice
#  and attach the Figure artist to it.
import numpy as np
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
fig = Figure()
canvas = FigureCanvas(fig)

# Import the numpy library to generate the random numbers.
x = np.random.randn(10000)

# Now use a figure method to create an Axes artist; the Axes artist is
#  added automatically to the figure container fig.axes.
# Here "111" is from the MATLAB convention: create a grid with 1 row and 1
#  column, and use the first cell in that grid for the location of the new
#  Axes.
ax = fig.add_subplot(111)

# Call the Axes method hist to generate the histogram; hist creates a
#  sequence of Rectangle artists for each histogram bar and adds them
#  to the Axes container.  Here "100" means create 100 bins.
ax.hist(x, 100)

# Decorate the figure with a title and save it.
ax.set_title('Normal distribution with $\mu=0, \sigma=1$')
fig.savefig('matplotlib_histogram.png')