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JSON (JavaScript Object Notation) is a lightweight data interchange format that is easy to read and write for humans and easy to parse and generate for machines. It is commonly used for transmitting data between a web server and a client. Although it originated from JavaScript, JSON is language-agnostic and is supported by many programming languages, including Python.

Key Features of JSON:

1. Data Types Supported:

• String

• Number

• Boolean

• Null

• Object (equivalent to Python dictionaries)

• Array (equivalent to Python lists)

2. Data Structures:

• Name/Value pairs: Similar to Python dictionaries (key-value pairs).

• Ordered lists of values: Similar to Python lists or arrays.

Using JSON in Python:

Python provides a built-in json module to work with JSON data. This module allows for the encoding (serialization) and decoding (deserialization) of JSON data.

Serializing JSON (Converting Python to JSON)

Serialization refers to the process of converting Python objects into JSON format. Python offers two methods for this:

• dump(): Converts Python objects into JSON format and writes them to a file.

• dumps(): Converts Python objects into a JSON string.

The following JSON items are created from Python objects. Following is a list of each:

SR.	JSON	Python
1	Object	dict
2	Array	list
3	String	str
4	number(int)	int
5	true	True
6	false	False
7	null	None

Example: Serializing JSON with dump()

import json

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

with open("data.json", "w") as write_file:
    json.dump(data, write_file) # Write JSON data to a file

In this example, we write a Python dictionary (data) to a JSON file (data.json) using json.dump().

Example: Serializing JSON with dumps()

import json

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

json_string = json.dumps(data) # Convert to JSON string
print(json_string)

Output:

{"name": "John", "age": 30, "city": "New York"}

In this case, we convert a Python dictionary into a JSON string using json.dumps().

Deserializing JSON (Converting JSON to Python)

Deserialization is the process of converting JSON data back into Python objects. Python offers two methods for this:

• load(): Reads JSON data from a file and converts it into a Python object.

• loads(): Converts a JSON string into a Python object.

Example: Deserializing JSON with load()

import json

with open("data.json", "r") as read_file:
data = json.load(read_file) # Read JSON data from a file
print(data)

Example: Deserializing JSON with loads()

import json

json_string = '{"name": "John", "age": 30, "city": "New York"}'
data = json.loads(json_string) # Convert JSON string to Python object
print(data)

Output:

{'name': 'John', 'age': 30, 'city': 'New York'}

In this case, we convert a JSON string into a Python dictionary using json.loads().

Comparison:

Method	Input Type	Output Type
json.load()	File	Python Object
json.loads()	String	Python Object
json.dump()	Python Object	JSON File
json.dumps()	Python Object	JSON String

Pretty-Printing JSON

To make JSON data easier to read and debug, we can use the indent and sort_keys parameters in the dumps() and dump() methods.

Example: Pretty Print JSON

import json

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

json_string = json.dumps(data, indent=4, sort_keys=True)
print(json_string)

Output:

{
    "name": "John",
    "age": 30,
    "city": "New York"
}

In this case, the indent parameter specifies how many spaces should be used for indentation, and sort_keys=True sorts the keys alphabetically.

Coding and Decoding in JSON

• Encoding is the process of converting Python objects into JSON format (serialization).

• Decoding is the process of converting JSON data back into Python objects (deserialization).

In Python, json.dumps() and json.dump() are used for encoding, while json.loads() and json.load() are used for decoding.

Advantages of JSON:

1. Readable and Lightweight: JSON is human-readable and uses fewer characters compared to XML.

2. Language-Agnostic: JSON can be used with most programming languages (Python, JavaScript, Java, etc.).

3. Widely Used for APIs: JSON is the most commonly used format for API data exchange between a client and a server.

4. Supports Complex Data Structures: JSON supports nested objects and arrays, making it highly flexible.

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