My code:
Client.py
import socket
import pandas as pd
import time
import pickle
# Load data
File = pd.read_csv('Data.txt', sep='\t', skipinitialspace=True, header=None, skiprows=1)
client_socket = socket.socket()
client_socket.connect(('localhost', 5555)) # Connect to server
client_socket.send(bytes("Sending file...", 'utf-8')) # Note
Buffer = []
for x in range(File.shape[0]):
count = 1
Buffer = File.loc[count]
client_socket.send(pickle.dumps(Buffer))
count += 1
time.sleep(2) # Wait 2 sec
This is my server:
Server.py
import socket
import pickle
server_socket = socket.socket()
server_socket.bind(('localhost', 5555)) # local server-client
server_socket.listen(3) # Max. 3 connections
print('Waiting for connection')
Buffer = []
i = 0
while True:
client_socket, addr = server_socket.accept()
received_data = client_socket.recv(1024).decode()
print('Client address', addr, received_data)
client_socket.recv(pickle.loads(Buffer)).decode()
print(Buffer[i])
i =+ 1
if(i == 10000):
client_socket.close() # Closing server socket
else: continue
I am stuck with the following error:
BrokenPipeError: [Errno 32] Broken pipe
The problem is with SIGPIPE, because the connection is interrupted based on what I found, in case I managed to implement the pickle correctly.
Server error:
Traceback (most recent call last):
File "/Users/David/PycharmProjects/DP1/Server.py", line 19, in <module>
client_socket.recv(pickle.loads(Buffer))
TypeError: a bytes-like object is required, not 'list'
I expected that decode() decodes the received pickle in bytes format to readable format on the side of the server. pickle.loads uses only one argument, so I cannot specify any encoding such as utf-8.
.txt file was exported from Excel (tab spacing):
Data.txt
Time Speed R_Ax Activation Delay KP
11:11:37 13,1 124,45 100 2 4
11:11:39 13,08 124,26 100 2 4
11:11:41 13,15 124,925 100 2 4
11:11:43 13,08 124,26 100 2 4
11:11:45 13,11 124,545 100 2 4
11:11:47 13,13 124,735 100 2 4
11:11:49 13,13 124,735 100 2 4
11:11:51 13,05 123,975 100 2 4
11:11:53 13,07 124,165 100 2 4
11:11:55 13,11 124,545 0 2 999
11:11:57 13,1 124,45 0 2 999
11:11:59 13,06 124,07 0 2 999
11:12:01 13,07 124,165 0 2 999
11:12:03 12,99 123,405 0 2 999
11:12:05 13,03 123,785 0 2 999
11:12:07 13,05 123,975 0 2 999
11:12:09 13,11 124,545 0 2 999
11:12:11 13,04 123,88 0 2 999
11:12:13 13,04 123,88 0 2 999
Thank You.
Since you'd like to transfer a pandas series over the wire, one way to achieve this would be to use pickle. pickle can take a Series and convert it to a byte array, and then go in the other direction and convert a byte array to a series.
On the client-side, use:
client_socket.send(pickle.dumps(Buffer))
Then, on the server-side use: pickle.loads
The actual code on both sides would look like that:
client:
import socket
import pandas as pd
import time
import pickle
# Load data
File = pd.read_csv('Data.txt', sep='\t', skipinitialspace=True, header=None, skiprows=1)
client_socket = socket.socket()
client_socket.connect(('localhost', 5555)) # Connect to server
client_socket.send(bytes("Sending file...", 'utf-8')) # Note
Buffer = []
for inx in range(File.shape[0]):
Buffer = File.loc[inx]
print(f"Sending \n {Buffer}")
client_socket.send(pickle.dumps(Buffer))
time.sleep(2) # Wait 2 sec
Server:
import socket
import pickle
server_socket = socket.socket()
server_socket.bind(('localhost', 5555)) # local server-client
server_socket.listen(3) # Max. 3 connections
print('Waiting for connection')
Buffer = []
i = 0
client_socket, addr = server_socket.accept()
received_data = client_socket.recv(1024)
print('Client address', addr, received_data)
while True:
received_data = client_socket.recv(10000)
Buffer.append(pickle.loads(received_data))
print(Buffer[i])
i =+ 1
client_socket.close() # Closing server socket (we'll never get here)