Переделать код на python

try:
    from urllib2 import urlopen
except ImportError:
    from urllib.request import urlopen
 
from io import StringIO
 
import numpy as np
from datetime import datetime
import cartopy.crs as ccrs
from cartopy.feature.nightshade import Nightshade
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
 
 
def aurora_forecast():
    """
 Get the latest Aurora Forecast from https://www.swpc.noaa.gov.
 
 Returns
 - - - - - - -
 img : numpy array
 The pixels of the image in a numpy array.
 img_proj : cartopy CRS
 The rectangular coordinate system of the image.
 img_extent : tuple of floats
 The extent of the image ``(x0, y0, x1, y1)`` referenced in
 the ``img_proj`` coordinate system.
 origin : str
 The origin of the image to be passed through to matplotlib's imshow.
 dt : datetime
 Time of forecast validity.
 
 """
 
    # GitHub gist to download the example data from
    url = ('https://gist.githubusercontent.com/belteshassar/'
           'c7ea9e02a3e3934a9ddc/raw/aurora-nowcast-map.txt')
    # To plot the current forecast instead, uncomment the following line
    # url = 'https://services.swpc.noaa.gov/text/aurora-nowcast-map.txt'
 
    response_text = StringIO(urlopen(url).read().decode('utf-8'))
    img = np.loadtxt(response_text)
    # Read forecast date and time
    response_text.seek(0)
    for line in response_text:
        if line.startswith('Product Valid At:', 2):
            dt = datetime.strptime(line[-17:-1], '%Y-%m-%d %H:%M')
 
    img_proj = ccrs.PlateCarree()
    img_extent = (-180, 180, -90, 90)
    return img, img_proj, img_extent, 'lower', dt
 
 
def aurora_cmap():
    """Return a colormap with aurora like colors"""
    stops = {'red': [(0.00, 0.1725, 0.1725),
                     (0.50, 0.1725, 0.1725),
                     (1.00, 0.8353, 0.8353)],
 
             'green': [(0.00, 0.9294, 0.9294),
                       (0.50, 0.9294, 0.9294),
                       (1.00, 0.8235, 0.8235)],
 
             'blue': [(0.00, 0.3843, 0.3843),
                      (0.50, 0.3843, 0.3843),
                      (1.00, 0.6549, 0.6549)],
 
             'alpha': [(0.00, 0.0, 0.0),
                       (0.50, 1.0, 1.0),
                       (1.00, 1.0, 1.0)]}
 
    return LinearSegmentedColormap('aurora', stops)
 
 
def main():
    fig = plt.figure(figsize=[10, 5])
 
    # We choose to plot in an Orthographic projection as it looks natural
    # and the distortion is relatively small around the poles where
    # the aurora is most likely.
 
    # ax1 for Northern Hemisphere
    ax1 = fig.add_subplot(1, 2, 1, projection=ccrs.Orthographic(0, 90))
 
    # ax2 for Southern Hemisphere
    ax2 = fig.add_subplot(1, 2, 2, projection=ccrs.Orthographic(180, -90))
 
    img, crs, extent, origin, dt = aurora_forecast()
 
    for ax in [ax1, ax2]:
        ax.coastlines(zorder=3)
        ax.stock_img()
        ax.gridlines()
        ax.add_feature(Nightshade(dt))
        ax.imshow(img, vmin=0, vmax=100, transform=crs,
                  extent=extent, origin=origin, zorder=2,
                  cmap=aurora_cmap())
 
    plt.show()
 
 
if __name__ = = '__main__':
    main()