Working with JSON files

Objective
By the end of this lesson, students will be able to read from and write to JSON files using Python’s json module. They will learn how to handle structured JSON data, making it easier to work with APIs and configuration files in Python.


1. Introduction to JSON files:

JSON (JavaScript Object Notation) is a lightweight data format commonly used for data exchange. JSON structures data in a human-readable format using key-value pairs, arrays, and nested objects, making it ideal for storing and transmitting data across various applications.


2. Using the json module for reading JSON files:

Python’s json module provides a straightforward way to read JSON data from files using the json.load() function.

import json

with open("data.json", "r") as file:
    data = json.load(file)
    print(data)  # Output the JSON data as a Python dictionary

Here, data.json is read and loaded into a Python dictionary, making it easy to access and manipulate fields.


3. Writing data to JSON files:

The json.dump() function allows you to write Python data structures (e.g., dictionaries, lists) to a JSON file.

data = {"name": "Alice", "age": 30, "city": "New York"}

with open("output.json", "w") as file:
    json.dump(data, file, indent=4)

Using indent=4 makes the JSON output easier to read by formatting it with indentation.


4. Converting Python objects to JSON strings and vice versa:

In addition to reading and writing JSON files, you can work directly with JSON strings using json.dumps() to convert Python objects to JSON-formatted strings and json.loads() to parse JSON strings into Python objects.

# Converting Python object to JSON string
json_string = json.dumps(data, indent=4)
print(json_string)

# Parsing JSON string back to Python object
parsed_data = json.loads(json_string)
print(parsed_data)

This is particularly useful for handling JSON data in web requests or other data streams.


5. Working with nested JSON data:

JSON files can contain nested objects and arrays, making it essential to understand how to access data within complex JSON structures.

nested_data = {
    "user": {
        "name": "Alice",
        "location": {"city": "New York", "country": "USA"},
        "hobbies": ["reading", "cycling"]
    }
}

print(nested_data["user"]["location"]["city"])  # Output: New York

Accessing nested JSON data requires understanding the structure and using key indices accordingly.


6. Practical use cases for JSON files:

JSON is commonly used for:

- Configuration files that store settings or preferences.
- Data exchange formats for APIs.
- Saving structured data in a portable, readable format.


7. Important considerations for working with JSON files:

8. Practical examples and exercises:

Exercise 1: Reading JSON data
1. Write a program to read data from a JSON file and print the content.

Exercise 2: Writing JSON data
1. Create a dictionary representing a student (e.g., name, age, courses).
2. Write this data to a JSON file.

Exercise 3: Working with nested JSON
1. Load a JSON file with nested data (e.g., user profile with multiple fields).
2. Access and print specific information, such as user location or hobbies.

Exercise 4: Converting JSON strings
1. Convert a Python dictionary to a JSON string and print it.
2. Parse a JSON string back to a dictionary.

Exercise 5: Using JSON for configuration
1. Create a JSON configuration file with settings (e.g., theme, language).
2. Write a program to load and print specific settings.


Conclusion
In this lesson, students learned to handle JSON data in Python, including reading, writing, and working with JSON strings. Understanding JSON is essential for working with APIs, configuration files, and various data formats in modern applications.