Immutable vs Mutable Objects in Python

Mutable objects can be modified in place after they are created; their content can be changed without creating a new object. Lists, dictionaries, sets, and user-defined objects (if attributes are modifiable) are mutable.

Immutable objects cannot be changed in place after they are created; any operation that seems to modify them actually creates a new object. Numbers, strings, tuples, and frozen sets are immutable.

Immutability means a new object is created whenever an operation appears to modify the original immutable object. For example, concatenating a string creates a new string instead of altering the original.

Mutability allows direct modification of an object's contents without creating a new one. This is efficient for frequent changes within a single object instance.

Immutable objects provide safety in multi-threaded environments as they prevent accidental changes during concurrent execution.

Mutable objects can be changed in place, which can be efficient for frequent modifications. However, this efficiency comes with the risk of unintended side effects.

Frequent changes to immutable objects lead to creating many new objects, potentially leading to inefficient memory usage.

Mutable objects do not create new objects on modification, which can reduce memory usage compared to immutable objects.

An immutable data type in Python that represents a sequence of characters.

A data type in Python used to store and manipulate data in key-value pairs.

A data type in Python that ensures uniqueness of its elements but does not maintain an order.

Objects whose internal state cannot be altered after their creation.

Objects whose internal state can be modified after their creation.

A special method used by Python to calculate a hash value for an object.

A special method used by Python to compare two objects for equality.

Data structures like lists, dictionaries, and sets that allow for modifications to their contents.

A string is a sequence of characters enclosed in quotes. It is an immutable data type, so you can't modify it directly. Strings like "hello" or "123" can be used as keys in dictionaries.

A list is a collection of items enclosed in square brackets. Lists are mutable, meaning you can modify them by adding, removing, or changing elements. Because of this mutability, they cannot be used as keys in dictionaries.

Dictionaries store data as key-value pairs. Keys are used to look up and retrieve associated values. To ensure consistent and efficient lookup, keys must be immutable objects. This means they cannot be modified after creation.

A hash value is a unique identifier that represents an object. Immutable objects produce the same hash value every time. This consistent hash value allows for efficient object retrieval in data structures like dictionaries.

The "eq" method is used to define equality between two objects. When two objects have the same hash value (hash collision), the eq method is used to determine if they are truly the same. This is crucial for managing equality checks when working with dictionaries.

A data type in Python representing whole numbers without decimal points.

A data type in Python representing numbers with decimal points. They allow precise representation of fractional values.

An ordered collection of elements enclosed in parentheses. They are immutable, meaning their elements cannot be changed after creation.

A set that is immutable. This means that its elements cannot be added or removed after creation.

A data type that stores key-value pairs, where keys must be immutable and values can be of any data type.

A rule that determines where Python searches for a variable in the code. It stands for Local, Enclosed, Global, and Built-in.

A keyword in Python used to modify variables defined in an enclosing scope within nested functions.

The area where a variable is accessible in a program. Three scopes are: global, enclosed, and local.

A keyword that allows modifying a global variable within a function.

The immediate surroundings of a function definition where it can access variables.

A nested function can access variables from its enclosing scope.

Variables defined outside of any function, accessible from anywhere in the program.

Accessing a global variable within a function.

Attempting to modify a global variable inside a function without explicitly declaring it using the global keyword.

The global keyword explicitly declares that you're working with a global variable within a function, enabling you to modify it.

Variables defined within a function, only accessible within that function.

A variable defined in an outer function, accessible within nested functions.

Accessing an enclosed scope variable from a nested function.

The global keyword is ineffective for enclosed scope variables, as it only searches the global scope, not the enclosing function's scope.

A programming practice that can make code harder to understand and debug, especially in larger programs.