Serialization (learnpython.org)

Serialization in Python refers to the process of converting data objects into a stream of bytes or a textual representation. This serialized data can then be stored in files, databases, or transmitted over networks. Serialization allows for easy storage, retrieval, and sharing of data.

#Serialization
import json

#json Load Method
import json 
print(json.loads(json_string))

Python offers powerful serialization libraries such as Pickle and JSON. Pickle is used to serialize Python objects, while JSON provides a lightweight, human-readable format for data exchange. These libraries simplify the serialization process and offer flexibility in data handling.

#Dumps Method
import json
json_string = json.dumps([1, 2, 3, "a", "b", "c"])
print(json_string)

Serialization offers several benefits, including compact data representation, platform independence, and easy integration with different systems. It allows for efficient storage, retrieval, and transfer of data, making it a valuable tool in many applications.

#cPickle
import pickle
pickled_string = pickle.dumps([1, 2, 3, "a", "b", "c"])
print(pickle.loads(pickled_string))

Serialization finds applications in a wide range of scenarios, including data persistence, inter-process communication, web APIs, and distributed systems. It enables seamless data transfer and integration between different components.

Serialization Exercise Solution

#Code Completed
import json

# fix this function, so it adds the given name
# and salary pair to salaries_json, and return it
def add_employee(salaries_json, name, salary):
    salaries = json.loads(salaries_json)
    salaries[name] = salary

    return json.dumps(salaries)

# test code
salaries = '{"Alfred" : 300, "Jane" : 400 }'
new_salaries = add_employee(salaries, "Me", 800)
decoded_salaries = json.loads(new_salaries)
print(decoded_salaries["Alfred"])
print(decoded_salaries["Jane"])
print(decoded_salaries["Me"])

Serialization is a powerful concept in Python that simplifies data storage and transfer. By converting complex data structures into a serialized format, we can efficiently store, retrieve, and share data across various systems.