G-Fact 150 | Sending Objects Over Socket in Python
Sending Objects Over Socket in Python
In this article, we will explore how to send objects over a network using sockets in Python. Sending objects, such as custom data structures or complex data types, requires serialization to convert them into a format suitable for transmission over a socket.
Why Send Objects Over a Socket?
Sending objects over a socket allows for:
- Remote Communication: Transmit structured data between devices or applications.
- Distributed Systems: Share complex data across nodes in distributed systems.
- Client-Server Models: Implement more sophisticated client-server interactions by exchanging custom objects.
Key Concepts
Serialization
- Definition: Serialization is the process of converting an object into a byte stream, which can be sent over a network. In Python, this is typically done using the pickle module.
Deserialization
- Definition: Deserialization is the reverse process of converting a byte stream back into a Python object.
Tools and Libraries
- Socket Library: The built-in Python library for socket programming.
- Pickle Library: A Python module used for serializing and deserializing objects.
Practical Example
Steps to Send Objects Over a Socket
Serialize the Object:
- Use the pickle module to convert the object into a byte stream.
Establish a Socket Connection:
- Set up a socket connection between the client and server.
Send the Serialized Object:
- Transmit the serialized object over the socket.
Receive and Deserialize the Object:
- On the receiving end, deserialize the byte stream back into the original object using pickle.
Practical Example Steps
Server Setup:
- The server listens for incoming connections and receives serialized objects.
Client Setup:
- The client connects to the server, serializes an object using pickle, and sends it over the socket.
Data Transfer:
- The serialized object is sent as bytes, and the server deserializes it back into a Python object.
Example Use Cases
- Sending Configuration Data: Transmit configuration settings as objects between devices.
- Distributed Computing: Share tasks and data structures across nodes in a distributed system.
- Inter-Process Communication (IPC): Exchange complex data structures between processes running on different machines.
Practical Applications
- Client-Server Applications: Implement applications where structured data (like dictionaries, lists, or custom classes) is exchanged between clients and servers.
- Remote Procedure Calls (RPC): Use serialized objects to pass parameters and receive results in remote method invocations.
- IoT Applications: Send sensor data as objects from edge devices to a central server.