When working with multiple Python scripts running on different Linux screens, it can be challenging to avoid conflicts when reading and writing data between them. In this article, we will explore three different solutions to tackle this problem.

Solution 1: Using a Shared File

One way to avoid conflicts between two Python scripts running on different Linux screens is by using a shared file to exchange data. Both scripts can read from and write to this file, ensuring that they do not interfere with each other’s operations.

# Python script 1
shared_file = open("shared.txt", "w")
shared_file.write("Data from script 1")
shared_file.close()

# Python script 2
shared_file = open("shared.txt", "r")
data = shared_file.read()
shared_file.close()
print(data)

In this solution, script 1 writes data to the shared file, and script 2 reads the data from it. However, this approach has some drawbacks. It requires both scripts to have access to the shared file, and there is a risk of data corruption if both scripts try to write to the file simultaneously.

Solution 2: Using Sockets

Another approach to avoid conflicts between two Python scripts running on different Linux screens is by using sockets for inter-process communication. Sockets allow scripts to communicate with each other over a network, even if they are running on different machines.

# Python script 1
import socket

HOST = 'localhost'
PORT = 12345

s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind((HOST, PORT))
s.listen(1)

conn, addr = s.accept()
data = conn.recv(1024)
conn.close()
print(data.decode())

# Python script 2
import socket

HOST = 'localhost'
PORT = 12345

s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect((HOST, PORT))
s.sendall(b"Data from script 2")
s.close()

In this solution, script 1 listens for incoming connections on a specific port, while script 2 connects to that port and sends data. The data is then received and printed by script 1. This approach allows for more robust communication between the scripts, but it requires both scripts to be running simultaneously and have network access.

Solution 3: Using a Message Queue

A third solution to avoid conflicts between two Python scripts running on different Linux screens is by using a message queue. A message queue acts as a buffer between the scripts, ensuring that data is exchanged in a synchronized manner.

# Python script 1
import queue

message_queue = queue.Queue()

message_queue.put("Data from script 1")

# Python script 2
import queue

message_queue = queue.Queue()

data = message_queue.get()
print(data)

In this solution, script 1 puts data into the message queue, and script 2 retrieves and prints the data. The message queue ensures that the scripts do not interfere with each other’s operations and provides a synchronized way of exchanging data. However, this approach requires both scripts to have access to the message queue object.

After exploring these three solutions, it is clear that the best option depends on the specific requirements of your project. If simplicity is a priority and both scripts have access to a shared file, Solution 1 can be a suitable choice. If robust communication and network access are available, Solution 2 using sockets can be a better option. Finally, if synchronization and data exchange are crucial, Solution 3 using a message queue can be the most appropriate.

Consider the specific needs and constraints of your project to determine which solution is the best fit.