)
print(
"Exit [End connection ]\n"
)
# If input is less than 2 e.g simply "query" which is unclear
# Structure of query timestamp of block 5: query timestamp 5
elif user_input[0].lower() == "query" and len(user_input) >= 2:
second_input = user_input[1]
if second_input == "timestamp" and len(user_input) == 3:
valid_input_flag = True
sock.sendall(user_action.encode())
# Structure of add command: add I am new block
elif user_input[0].lower() == "add":
valid_input_flag = True
data_string = user_action[3:]
add_flag = block_chain.addblock(data=data_string)
# if successfully added to blockchain, send out the new block
if add_flag is True:
data_to_send = pickle.dumps(block_chain.getlatest())
# Send client command to server
sock.sendall(b"add block")
# Send json string of new block
sock.sendall(data_to_send)
if exit_flag:
break
if valid_input_flag is False:
print("Invalid Action!")
elif list_flag is False:
# Commands received should not be able to exceed 100 bytes
# For this project assume block chain is small: within 256kb
received_string = sock.recv(100).decode()
import socket
import sys
from blockchain import BlockChain
import pickle
import threading
# Create a TCP/IP Socket
sock = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
# Bind the socket to the port
server_address = ('localhost', 10000)
blockchain = BlockChain()
blockchain.addblock("Assignment 2")
max_buffer_size = 256000 # kernel receive buffer size of socket
print('starting up on {} port {}'.format(*server_address))
sock.bind(server_address)
# Listen for incoming connections
sock.listen(1)
# Thread handle for new TCP Connection
def handle_connection(connection, client_address):
try:
print('connection from', client_address)
# Receive the data in small chunks and retransmit it
while True:
data = connection.recv(256)
print('received {!r}'.format(data))
if b"query latest" in data:
data_to_send = pickle.dumps(blockchain.getlatest()) # Convert latest block to json string and send
connection.sendall(b"send latest")
connection.sendall(data_to_send)
if b"query all" in data:
