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Converts a Python object to a formatted JSON string with 2-space indentation, using a safe serialization helper function.

Purpose

This function provides a safe way to convert Python objects to JSON strings, handling objects that may not be directly JSON-serializable through the safe_json_serialize helper. It's useful for logging, API responses, data export, and debugging where human-readable JSON output is needed. The 2-space indentation makes the output more readable for display or file storage.

Source Code

def to_json(obj: Any) -> str:
    """
    Convert object to JSON string.
    
    Args:
        obj: Object to convert
        
    Returns:
        JSON string
    """
    return json.dumps(safe_json_serialize(obj), indent=2)

Parameters

Parameter Details

obj: Any Python object to be converted to JSON. Can be dictionaries, lists, strings, numbers, booleans, None, or custom objects. Non-serializable objects are handled by the safe_json_serialize function before JSON conversion.

Return Value

Type: str

Returns a string containing the JSON representation of the input object, formatted with 2-space indentation for readability. The output is a valid JSON string that can be parsed back into a Python object or used in JSON-compatible systems.

Dependencies

• json

Required Imports

import json

Usage Example

# Assuming safe_json_serialize is defined
def safe_json_serialize(obj):
    if hasattr(obj, '__dict__'):
        return obj.__dict__
    return str(obj)

def to_json(obj):
    return json.dumps(safe_json_serialize(obj), indent=2)

# Example usage
data = {'name': 'John', 'age': 30, 'city': 'New York'}
json_string = to_json(data)
print(json_string)
# Output:
# {
#   "name": "John",
#   "age": 30,
#   "city": "New York"
# }

# With a list
items = [1, 2, 3, {'key': 'value'}]
json_string = to_json(items)
print(json_string)

Best Practices

• Ensure the safe_json_serialize function is properly implemented to handle all object types you expect to serialize
• Be aware that the indent=2 parameter creates formatted output which increases string size compared to compact JSON
• For large objects, consider using json.dumps without indent for more compact output in production environments
• Handle potential json.JSONDecodeError exceptions when the safe_json_serialize function doesn't properly convert objects
• Consider adding error handling around the json.dumps call for production code
• For API responses, you may want to use indent=None or compact separators for bandwidth efficiency

Tags

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