import matplotlib
from matplotlib.lines import Line2D

class DynamicSeries:
    """ AutomaticTimeSeries handles drawing a line in an efficient way
        onto a matplotlib canvas. """
    def __init__(self, fig, ax):
        self.fig = fig
        self.ax = ax

        # Line associated with the figure used to draw the next line.
        self.dummyLine = ax.plot([0],[0], animated=True)[0]

        # Bitmap of previous background
        self._bg = None

        # Redraw time series on reveal.
        fig.canvas.mpl_connect("draw_event", self.on_draw)

        self.x_ax = []
        self.y_ax = []

        self.current_x_lims = 10

    def insert(self, x, y):
        self.x_ax.append([x])
        self.y_ax.append([y])

        if len(self.x_ax) == 1:
            return None

        prev_x = self.x_ax[-1]
        prev_y = self.y_ax[-1]
        self.dummyLine.set_data([(prev_x, prev_y), (x, y)])

        if self._bg is not None:
            self.fig.canvas.restore_region(self._bg)

        self.fig.draw_artist(self.dummyLine)
        self.fig.canvas.blit(self.fig.bbox)
        self.fig.canvas.flush_events()

        self._bg = self.fig.canvas.copy_from_bbox(self.fig.bbox)

    def on_invalidated(self):
        """ Redraw the entire canvas on invalidation. """
        self.ax.clear()
        self.ax.set_xlim(0, self.current_x_lims)
        self.ax.plot(self.x_ax, self.y_ax, color="blue")

    def on_draw(self, event):
        self.on_invalidated()

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
fig.show()
ats = AutomaticTimeSeries(fig, ax)