Explain mutable vs immutable in Python.

Summary

Mutable objects can change in place after creation; immutable objects cannot change their value once created.

Longer Answer

Lists, dictionaries, and sets are mutable, so aliases to the same object can observe changes made through any reference. Integers, strings, tuples, frozensets, and bytes are immutable, so operations create new objects or reuse existing immutable values.

This matters for default arguments, hashing, caching, defensive copying, and API design. A common bug is using a mutable default such as [] in a function signature, which is shared across calls.

Key Points

• Lists, dictionaries, and sets are mutable, so aliases to the same object can observe changes made through any reference
• Integers, strings, tuples, frozensets, and bytes are immutable, so operations create new objects or reuse existing immutable values
• This matters for default arguments, hashing, caching, defensive copying, and API design
• For 'Explain mutable vs immutable in Python.', a strong interview answer should define the mechanism, name the common failure mode, and explain the production decision it affects.

This matters for default arguments, hashing, caching, defensive copying, and API design. A common bug is using a mutable default such as [] in a function signature, which is shared across calls

Comparison / Tradeoffs

This matters for default arguments, hashing, caching, defensive copying, and API design. A common bug is using a mutable default such as [] in a function signature, which is shared across calls. |

Summary

Mutable objects can change in place after creation; immutable objects cannot change their value once created.

Longer Answer

For 'Explain mutable vs immutable in Python.', a strong interview answer should define the mechanism, name the common failure mode, and explain the production decision it affects.

This matters for default arguments, hashing, caching, defensive copying, and API design. A common bug is using a mutable default such as [] in a function signature, which is shared across calls.

Key Points

• For 'Explain mutable vs immutable in Python.', a strong interview answer should define the mechanism, name the common failure mode, and explain the production decision it affects
• This matters for default arguments, hashing, caching, defensive copying, and API design
• A common bug is using a mutable default such as [] in a function signature, which is shared across calls
• Use the answer to connect the concept back to a realistic production or interview scenario for 'Explain mutable vs immutable in Python.'

Comparison / Tradeoffs