Core Python fundamentals

Python Data Types

In Python, data types classify structural items, deciding what computational actions apply to variables. Python uses dynamic allocation: variable categories are resolved explicitly behind the scenes during performance execution based on your active values.

Python Data Types Summary

Category	Data Type	Example
Numeric	`int`, `float`, `complex`	`x = 10`
Sequence	`str`, `list`, `tuple`	`L = [1, 2]`
Mapping	`dict`	`{"id": 1}`
Set	`set`, `frozenset`	`{1, 2, 3}`
Boolean	`bool`	`True`, `False`

1. Numeric Types

Contains pure mathematical representations. Includes integers, floats, and real/imaginary complex assignments.

# Integer type print(1, 2, 3) # Floating type print(25.3, 2.01) # Complex type print(10+2j, 3+1j)

Integer (int)

Represents complete numbers without decimal remainders, holding both positive or negative values.

x = 10 print(type(x))

Float (float)

Represents fractional or decimal numbers.

x = 10.2 print(type(x))

Complex (complex)

Represents numbers containing distinct real and imaginary mathematical components.

x = 1 + 3j print(type(x))

2. Boolean Type

Conditional statements evaluating directly to True or False parameters.

a = True b = False print(type(a))

3. Sequence Types

Ordered collections that allow access to elements via index positions.

String (str)

An immutable list containing ordered arrays of Unicode symbols wrapped inside quote markers.

x = 'Python' print(type(x))

List (list)

Mutable, dynamic arrays containing mixed metadata variables inside standard square brackets.

my_list = [10, 'Python', 2.5] print(type(my_list))

Tuple (tuple)

Fixed sequence arrays that are immutable, wrapped inside standard parentheses.

my_tuple = (10, 'Tuple', 3.12) print(type(my_tuple))

4. Set Type (set)

Unordered, mutable collection values completely stripped of duplicated items using curly brace blocks.

set1 = {1, 9.0, 2, 5, 1} print(set1)

{1, 2, 5, 9.0} # Duplicates filtered automatically

5. Dictionary Type (dict)

Ordered structured maps connecting custom key arrays to separate value points via colon operators.

dict1 = {'key1': 1.0, 'key2': 2.0} print(type(dict1))

Interactive Sandbox Lab Workspace

# Enter dynamic data types testing structures variable_name = "Custom Verification Run" print(variable_name)

Custom Verification Run

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