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Python json.loads() Function

The Python json.loads() function is used to parse a JSON-formatted string and convert it into a corresponding Python object.

This function is useful when working with JSON data received from APIs, reading configuration settings, or processing structured data stored as a string.

Following is the syntax of the Python json.loads() function −

json.loads(s, *, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None)

This function accepts the following parameters −

• s: A JSON-formatted string to be parsed.
• cls (optional): A custom decoder class that subclasses json.JSONDecoder.
• object_hook (optional): A function that transforms dictionary objects.
• parse_float (optional): A function that processes floating-point numbers. Default is float.
• parse_int (optional): A function that processes integer numbers. Default is int.
• parse_constant (optional): A function that processes constants like NaN and Infinity.
• object_pairs_hook (optional): A function that processes key-value pairs in a dictionary.

This function returns a Python object representing the parsed JSON data.

In this example, we use the json.loads() function to convert a JSON-formatted string into a Python dictionary −

import json

# JSON string
json_string = '{"name": "John", "age": 30, "city": "New York"}'

# Convert JSON string to Python dictionary
data = json.loads(json_string)

print("Parsed Data:", data)

We get the output as shown below −

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

The object_hook parameter allows us to define a custom function that modifies the JSON objects when they are loaded. In this example, we convert all keys to uppercase −

import json

# Custom function to transform JSON objects
def custom_decoder(obj):
   return {key.upper(): value for key, value in obj.items()}

# JSON string
json_string = '{"name": "John", "age": 30, "city": "New York"}'

# Convert JSON string to dictionary with custom object_hook
data = json.loads(json_string, object_hook=custom_decoder)

print("Transformed Data:", data)

Following is the transformed output −

Transformed Data: {'NAME': 'John', 'AGE': 30, 'CITY': 'New York'}

We can use the parse_int and parse_float parameters to customize how numbers are processed while loading JSON data −

import json

# Custom parsing functions
def parse_int_custom(value):
   return int(value) * 10  # Multiply integers by 10

def parse_float_custom(value):
   return round(float(value), 2)  # Round floats to 2 decimal places

# JSON string
json_string = '{"integer": "10", "floating": "12.3456"}'

# Convert JSON string to dictionary with custom number parsing
data = json.loads(json_string, parse_int=parse_int_custom, parse_float=parse_float_custom)

print("Parsed Data:", data)

Following is the output obtained −

Parsed Data: {'integer': 100, 'floating': 12.35}

By default, Python dictionaries do not maintain order before Python 3.7. If you need to preserve the order of keys while loading JSON, you can use the object_pairs_hook parameter with OrderedDict −

import json
from collections import OrderedDict

# JSON string
json_string = '{"name": "John", "age": 30, "city": "New York"}'

# Convert JSON string to OrderedDict
data = json.loads(json_string, object_pairs_hook=OrderedDict)

print("Ordered Data:", data)

The result produced is as follows −

Ordered Data: OrderedDict({'name': 'John', 'age': 30, 'city': 'New York'})

The parse_constant parameter allows us to customize how special constants like NaN and Infinity are handled −

import json

# Custom function for parsing special constants
def custom_parse_constant(value):
   return f"Constant: {value}"

# JSON string with special constants
json_string = '{"number": Infinity, "value": NaN}'

# Convert JSON string to dictionary with custom parse_constant
data = json.loads(json_string, parse_constant=custom_parse_constant)

print("Parsed Data:", data)

Following is the output obtained −

Parsed Data: {'number': 'Constant: Infinity', 'value': 'Constant: NaN'}

python_json.htm

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