mahesh Reddy
Anvi Staff answered 4 years ago
Serialization in Python refers to the process of converting Python objects into a byte stream or a string representation that can be easily stored, transmitted, or reconstructed later. Serialization is commonly used for tasks such as data persistence, inter-process communication, and network communication.
Python provides built-in modules and libraries to support serialization, such as:
pickle: The pickle module in Python allows you to serialize and deserialize Python objects. It can handle most Python data types, including custom objects, and is suitable for use cases where both the producer and consumer of the serialized data are Python processes.
Example:
import pickle
# Serialize an object
data = {'name': 'John', 'age': 30}
serialized_data = pickle.dumps(data)
# Deserialize the object
deserialized_data = pickle.loads(serialized_data)
json: The json module provides functions for encoding and decoding JSON (JavaScript Object Notation) data. JSON is a lightweight and human-readable data interchange format widely used for data exchange between different platforms and programming languages.
Example:
import json
# Serialize an object to JSON
data = {'name': 'John', 'age': 30}
serialized_data = json.dumps(data)
# Deserialize JSON data
deserialized_data = json.loads(serialized_data)
marshal: The marshal module is used for serializing and deserializing Python objects into a binary format. It is more efficient than pickle for some data types but may not be as portable across different Python versions.
Example:
import marshal
# Serialize an object
data = {'name': 'John', 'age': 30}
serialized_data = marshal.dumps(data)
# Deserialize the object
deserialized_data = marshal.loads(serialized_data)
Serialization allows Python objects to be persisted to disk, transmitted over the network, or stored in databases in a format that can be easily reconstructed later, enabling data sharing and interoperability between different components of an application or between different systems.
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