Data persistence

• Enables applications to save user preferences, settings, and other essential data.
• Facilitates recovery of application state after crashes or restarts.
• Provides a way to analyze historical data over time.

• Text files: Simple to read and write but may lack structure.
• CSV files: Ideal for tabular data.
• JSON files: Good for structured data, especially for configurations and web applications.
• Binary files: Efficient for storing non-text data.

def save_data(filename, data):
    with open(filename, 'w') as file:
        file.write(data)

save_data('data.txt', 'This is some sample data.')

import csv

def save_data_to_csv(filename, data):
    with open(filename, 'w', newline='') as csvfile:
        writer = csv.writer(csvfile)
        writer.writerows(data)

data = [['Name', 'Age'], ['Alice', 30], ['Bob', 25]]
save_data_to_csv('data.csv', data)

import json

def save_data_to_json(filename, data):
    with open(filename, 'w') as jsonfile:
        json.dump(data, jsonfile)

data = {'name': 'Alice', 'age': 30}
save_data_to_json('data.json', data)

def read_data(filename):
    with open(filename, 'r') as file:
        return file.read()

data = read_data('data.txt')
print(data)  # Output: This is some sample data.

def read_data_from_csv(filename):
    with open(filename, 'r') as csvfile:
        reader = csv.reader(csvfile)
        return list(reader)

data = read_data_from_csv('data.csv')
print(data)  # Output: [['Name', 'Age'], ['Alice', '30'], ['Bob', '25']]

def read_data_from_json(filename):
    with open(filename, 'r') as jsonfile:
        return json.load(jsonfile)

data = read_data_from_json('data.json')
print(data)  # Output: {'name': 'Alice', 'age': 30}

• Use structured formats (like JSON or CSV) for better data management and readability.
• Handle exceptions when reading/writing files to avoid crashes due to missing files or incorrect formats.
• Regularly back up important data to prevent loss.