Python Interview Questions
Converting Python objects to and from JSON and pickle, and the safety trade-offs between them.
Ans
The json module converts between Python objects and JSON text/bytes representations using dumps, loads, dump, and load.
Example
pythonimport json text = json.dumps({"name": "Amit", "age": 25}) data = json.loads(text) print(data["name"])
Important Point
JSON supports a limited set of data types; arbitrary Python objects need custom serialization.
Ans
Serialization converts an in-memory object or data structure into a representation that can be stored or transmitted. JSON is common for interoperable data; pickle is Python-specific.
Example
pythonimport json text = json.dumps({"id": 1, "name": "Amit"}) print(text)
Important Point
Never unpickle untrusted data; pickle can execute arbitrary code during deserialization.
Ans
pickle serializes and deserializes many Python object structures into a Python-specific binary representation.
Example
pythonimport pickle obj = {"a": 1} data = pickle.dumps(obj) copy = pickle.loads(data) print(copy)
Important Point
Never load pickle data from an untrusted source because deserialization can execute arbitrary code.
Ans
JSON is text-based, interoperable, and limited to JSON-compatible data. Pickle can represent many Python-specific objects but is Python-specific and unsafe for untrusted input.
Example
pythonimport json payload = json.dumps({"name": "Amit"}) print(payload)
Important Point
For APIs and cross-language systems, JSON is usually the appropriate interchange format.