Python Variables: Syntax, Usage, and Examples
How to Use Variables in Python
my_variable = value
my_variable: The name of the variable to create or update- =: The operator to assign a value to a variable
- value: A value, such as a number, string, or list for the variable to store
In Python, variables aren't declared like they are in many other programming languages. Instead, you create a variable right when you assign a value to it.
When to Use Variables in Python
Examples of Python Variables in Python
User Input Storage
password = input("Enter a password: ")
Calculators
experience_multiplier = 1.3
salary = base_salary * experience_multiplier
print(salary)
print(i)
if login_successful:
print("Login succeeded.")
else:
print("Login failed.")
return width * height
def __init__(self, make, model):
self.make = make # 'make' and 'model' are variables storing state
self.model = model
width = height
height = temp_variable
Learn More About Variables in Python
A variable’s name identifies the variable and often indicates its purpose and the type of value it stores. Choosing meaningful and descriptive names helps in understanding Python code without needing excessive comments or documentation.
The Python programming language has some rules for naming variables:
1. Variable names must start with a letter (a-z, A-Z) or an underscore (_)2. Variable names can contain letters, numbers, and underscores but cannot begin with a number
3. Avoid using any of Python's reserved keywords (e.g., for, if, while, etc.) as variable names
Python variable names typically follow the “snake case” naming convention. Snake-case names start with a letter or underscore followed by letters, underscores, or numbers. As examples, consider base_salary and experience_multiplier.
In Python, variable names are case-sensitive, which means base_salary and BASE_SALARY are two different variable names. This feature allows for a flexible naming scheme but requires careful attention to avoid errors.
In Python, there are different types of variables, like integers, floats (floating-point numbers), strings, lists, and dictionaries. Each type has a specific purpose and operations it can handle. As opposed to many other programming languages, Python is dynamically typed. In Python, the variable type is determined at runtime based on the assigned value.
Consider a scenario where you're working with different variable types in a simple application. You might have an integer to store an age value, a float for a cash balance, and a string for a name. You might also use a list for favorite colors and a dictionary for a user profile:
balance = 100.50 # Float
name = "Alex" # String
favorite_colors = ["blue", "green", "red"] # List user_profile = {"username": "alex25", "active": True} # Dictionary
number_int = int(number_string) # converts string to integer print(number_int + 1) ## adds 1 to the integer
Similarly, you might need to convert an integer to a string:
age_string = str(age) # converts integer to string
Moreover, Python allows for implicit type conversion in certain operations to avoid type errors. For instance, adding an integer and a float creates a float value. Python implicitly converts the integer to a float to ensure the operation makes sense:
number_float = 3.5
result = number_int + number_float # integer is implicitly converted to float
However, Python doesn’t implicitly convert between strings and other types to avoid errors and unexpected behavior. Instead, it requires type functions like int(), float(), and str() to enable operating on variables of different types together. For instance, to concatenate a number with a string, you must explicitly convert the number to a string using str().
greeting = "You are " + str(age) + " years old." print(greeting)
Variable Scope
Scope defines the part of a Python application within which a variable exists. Python organizes variables into various scopes. The most important scopes are local and global variables.
Local variables live within a function and are only accessible inside that function. They're not available outside the function, making them temporary and function-specific. Consider a variable inside a function that counts how often the function has been called. This variable will only be available for use within that function.
local_var = 5 # Local variable, accessible only within 'function'
print(local_var)
print_local_var() # This will print 5
# print(local_var) # This would raise an error because local_var is not accessible here
In Python, global variables are defined outside functions. Global variables are accessible throughout a program, including inside functions.
def function():
print(global_var) # Accessing global variable inside a function
function() # This will print 10
print(global_var) # This will also print 10
def function():
global global_var # Correct way to use the global statement
global_var = 15 # Now modifying the global variable print(global_var) # This will print 15
function() # This will print 15, because the function modifies the global variable
print(global_var) # This will also print 15, as the global variable has been modified
Consider a situation where you're tracking the progress of a task in a program. Creating a global variable at the start of your program allows you to update it throughout the program. This can be particularly useful in applications that need to maintain some configuration across various program parts.
Global variables in Python can make debugging and understanding your code more challenging, especially in larger programs. Therefore, keeping the use of global variables at a minimum is a good idea.
Constants
In Python, constants are variables meant to remain unchanged throughout the execution of a program. The naming convention of constants requires uppercase letters with underscores separating any words, such as BASE_SALARY or EXPERIENCE_MULTIPLIER.Typically, such constants are defined at the top of a Python file.
In reality, Python has no enforcement for constants. Constants are only meant to remain unchanged and can technically be changed at any time.
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