Handling JSON Data
JSON (JavaScript Object Notation) is a widely used data format for exchanging information between systems and applications. It is built on two structures: key-value pairs, which are similar to python dictionaries, and arrays, which are similar to python lists. JSON can also represent nested data, allowing you to embed objects and arrays within other objects or arrays. This flexibility makes JSON a popular choice for representing structured data in web APIs, configuration files, and data storage.
1234567891011121314151617181920# Define a Python dictionary with nested data person = { "name": "Alice", "age": 30, "hobbies": ["reading", "cycling", "chess"], "address": { "city": "Springfield", "zip": "12345" } } # Convert the dictionary to a JSON-like string using str() json_str = str(person) print("JSON-formatted string:") print(json_str) # Convert the JSON-like string back to a Python dictionary using eval() parsed_person = eval(json_str) print("\nParsed Python dictionary:") print(parsed_person)
While using eval() to parse a string into a Python object may seem convenient, it introduces significant security risks. If the string being evaluated contains malicious code, eval() will execute it, potentially harming your system or exposing sensitive data. In real-world applications, you should use dedicated libraries for parsing and serializing JSON, such as Python's built-in json module, which safely handles JSON data and avoids the dangers of arbitrary code execution.
1. What is the main difference between a Python dictionary and a JSON object?
2. Which data types are supported in JSON format?
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Handling JSON Data
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JSON (JavaScript Object Notation) is a widely used data format for exchanging information between systems and applications. It is built on two structures: key-value pairs, which are similar to python dictionaries, and arrays, which are similar to python lists. JSON can also represent nested data, allowing you to embed objects and arrays within other objects or arrays. This flexibility makes JSON a popular choice for representing structured data in web APIs, configuration files, and data storage.
1234567891011121314151617181920# Define a Python dictionary with nested data person = { "name": "Alice", "age": 30, "hobbies": ["reading", "cycling", "chess"], "address": { "city": "Springfield", "zip": "12345" } } # Convert the dictionary to a JSON-like string using str() json_str = str(person) print("JSON-formatted string:") print(json_str) # Convert the JSON-like string back to a Python dictionary using eval() parsed_person = eval(json_str) print("\nParsed Python dictionary:") print(parsed_person)
While using eval() to parse a string into a Python object may seem convenient, it introduces significant security risks. If the string being evaluated contains malicious code, eval() will execute it, potentially harming your system or exposing sensitive data. In real-world applications, you should use dedicated libraries for parsing and serializing JSON, such as Python's built-in json module, which safely handles JSON data and avoids the dangers of arbitrary code execution.
1. What is the main difference between a Python dictionary and a JSON object?
2. Which data types are supported in JSON format?
Thanks for your feedback!