from sklearn import datasets
import random
try:
# Make socket
transport = TSocket.TSocket('localhost', 9090)
# Buffering is critical. Raw sockets are very slow
transport = TTransport.TBufferedTransport(transport)
# Wrap in a protocol
protocol = TBinaryProtocol.TBinaryProtocol(transport)
# Create a client to use the protocol encoder
client = Classifier.Client(protocol)
# Connect!
transport.open()
digits = datasets.load_digits()
data = zip(digits.data, digits.target)
random.shuffle(data)
for i in range(10):
result = client.predict(data[i][0])
answer = data[i][1]
if result == answer:
print 'Correct!'
else:
print 'Wrong: answer is %d, predicted as %d' % (answer, result)
