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7. What are the common built-in data types in Python?

Python comes with a variety of built-in data types that can be used without explicit type declarations. While Python’s dynamic nature doesn’t require defining data types during variable declarations, it’s crucial to understand them to avoid type errors. The type() and isinstance() functions can be used to check variable types. These data types fall into the following categories:

None Type:

• NoneType: Represents null values in Python, indicated by the None keyword. Boolean equality operations can be performed on these objects.

Numeric Types:

There are three distinct numeric types, plus a subtype for booleans:

• int: Stores integer literals, including hexadecimal, octal, and binary numbers.

• float: Stores floating-point numbers, which include decimal values and exponential notation.

• complex: Stores complex numbers in the form (A + Bj), with attributes real and imag.

• bool: A subtype of integers, storing boolean values (True or False).

Note: The standard library also provides fractions to store rational numbers and decimal for floating-point numbers with user-defined precision.

Sequence Types:

According to Python documentation, the three basic sequence types are lists, tuples, and range objects. These types support the in and not in operators for element traversal, sharing the same priority as comparison operations.

• list: A mutable sequence used to store a collection of items.

• tuple: An immutable sequence used to store a collection of items.

• range: Represents an immutable sequence of numbers generated during execution.

• str: An immutable sequence of Unicode code points to store textual data.

Note: Additional types for processing include binary data (bytearray, bytes, memoryview) and text strings (str).

Mapping Types:

Mapping objects map hashable values to arbitrary objects. They are mutable, and Python currently has one standard mapping type:

• dict: Stores a comma-separated list of key-value pairs.

Set Types:

Python has two built-in set types:

• set: A mutable unordered collection of distinct hashable objects, supporting methods like add() and remove().

• frozenset: An immutable collection of distinct hashable objects, which cannot be modified after creation.

Note: The set type is mutable and cannot be used as a dictionary key. In contrast, the frozenset is immutable, hashable, and can be used as a dictionary key or as an element of another set.

Modules:

Modules are special built-in types supported by the Python interpreter. They support one special operation, attribute access (e.g., mymod.myobj), where mymod is a module and myobj references a name defined in the module’s symbol table. The symbol table of the module resides in the special attribute __dict__, but direct assignment to this attribute is neither possible nor recommended.

Callable Types:

Callable types can be invoked with a function call. These include:

• User-defined functions

• Instance methods

• Generator functions

• Other built-in functions, methods, and classes.