marhar

# model.fit(img_iter,
#           epochs=10,
#           steps_per_epoch=len(x_train)/batch_size, # Run same number of steps we would if we were not using a generator.
#           validation_data=(x_valid, y_valid))

import matplotlib.pyplot as plt

# Plotting the training loss
plt.plot(model.history.history['loss'], label='Training Loss')

marhar

import logging
import logging.handlers

logf = logging.getLogger('MyLogger')
logf.setLevel(logging.INFO)
handler = logging.handlers.RotatingFileHandler(
         'logfile.txt', maxBytes=100*1000*1000, backupCount=5)
logf.addHandler(handler)

logf.info('this is a log message') 

marhar

def ismulticast(hostname):
    """is this address a multicast address?"""
    # -- yes if bits 0-3 are 1110
    import socket
    import struct
    ip=socket.gethostbyname(hostname)
    mreq=struct.pack("4sl",socket.inet_aton(ip),socket.INADDR_ANY)
    return ord(mreq[0]) & 0xf0 == 0xe0

marhar

a=['a1']
b=['b1','b2','b3']
c=['c1','c2']

print zip(a,b,c)