Python, a versatile programming language, provides a range of built-in types to handle different kinds of data. In this blog, we will explore the basics of Python data types and how to work with them effectively.
String
Strings are sequences of characters enclosed in quotes (’’ or “”). To check if a variable is of the string data type, you can use the type()
function or the isinstance()
function:
name = "Roger"
type(name) == str # True
isinstance(name, str) # True
Numbers
Python supports two types of numbers: integers (int
) and floating-point numbers (float
). Integers are whole numbers without a fractional component, while floating-point numbers have decimal places. Here’s how you can define and determine the data type of numbers:
age = 1
type(age) == int # True
fraction = 0.1
type(fraction) == float # True
Creating Variables
In Python, variables are dynamically typed, which means that you don’t need to explicitly specify the data type when creating a variable. Python automatically detects the type from the assigned value. For example:
name = "Flavio" # String
age = 20 # Integer
You can also explicitly define a variable of a specific type by using the class constructor:
name = str("Flavio") # String
anotherName = str(name) # String
Type Conversion: Casting
Python allows you to convert variables from one type to another using the class constructor. This process is known as casting. Python will try to determine the correct value based on the conversion. For example, you can convert a string to an integer:
age = int("20")
print(age) # 20
fraction = 0.1
intFraction = int(fraction)
print(intFraction) # 0
However, note that not all conversions are possible. If you try to convert a value that is not compatible with the target type, you will encounter an error. For instance, converting the string “test” to an integer will result in a ValueError: invalid literal for int() with base 10: 'test'
error.
Other Data Types
In addition to strings and numbers, Python offers several other built-in types for different purposes. Here are some notable examples:
complex
for complex numbersbool
for booleanslist
for liststuple
for tuplesrange
for rangesdict
for dictionariesset
for sets
These are just the basics of Python data types. In future articles, we will delve into each type individually, exploring their features and practical usage.