6.4 Parameters

Functions are the building blocks of Python programming, allowing you to organize code into reusable units. Parameters and arguments are key concepts in function design, enabling you to pass information to functions and customize their behavior.

Understanding function parameters, arguments, and scope is crucial for writing effective and flexible code. This knowledge empowers you to create functions that can handle various inputs, work with different data types, and maintain proper variable accessibility.

Function Parameters and Arguments

Function arguments and parameters

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• Parameters are variables defined in the function definition that receive values when the function is called
  • Specified within parentheses after the function name (name, age)
  • Act as placeholders for actual values passed to the function
  • Also known as formal parameters
• Arguments are actual values passed to a function when it is called
  • Provided within parentheses when calling the function (25, "John")
  • Number and order of arguments must match number and order of parameters in function definition
• When function is called with arguments, values of arguments are assigned to corresponding parameters
  • Allows function to work with values passed as arguments
• Parameters can have default values specified in function definition
  • If argument not provided for parameter with default value, default value is used
  • Default values specified using

    =

    operator after parameter name (age=18)

Multiple parameters in functions

• Function can have multiple parameters defined in its definition
  • Multiple parameters separated by commas within parentheses (name, age, city)
  • Each parameter assigned a value from corresponding argument when function is called
• Order of arguments passed when calling function must match order of parameters in function definition
• Example function definition with multiple parameters:

  [def](https://www.fiveableKeyTerm:def) greet(name, age):
      print(f"Hello, {name}! You are {age} years old.")
  

• When calling function, provide arguments in same order as parameters:

  greet("Alice", 25)
  

• Keyword arguments can be used to pass arguments to parameters in any order
  • Keyword arguments specified using parameter name followed by

    =

    operator and argument value (age=30, name="Bob")
  • Example using keyword arguments:

    greet(age=30, name="Bob")
    

Object mutability and function behavior

• Object mutability refers to whether object can be changed (mutable) or not (immutable) after creation
• Mutable objects (lists, dictionaries) can be modified within function, changes persist outside function
  • When mutable object passed as argument to function, function receives reference to original object (pass by reference)
  • Modifications made to object inside function affect original object
• Immutable objects (numbers, strings, tuples) cannot be modified within function
  • When immutable object passed as argument to function, function receives copy of object's value (pass by value)
  • Modifications made to object inside function do not affect original object
• Example demonstrating impact of mutability:

  def modify_list(lst):
      lst.append(4)
  
  my_list = [1, 2, 3]
  modify_list(my_list)
  print(my_list)  # Output: [1, 2, 3, 4]
  

  • In this example, list

    my_list

    is modified inside function, changes persist outside function
• Understanding object mutability is important for writing functions that behave as expected and avoiding unintended side effects

Function scope and variable-length arguments

• Function scope refers to the visibility and accessibility of variables within a function
  • Variables defined inside a function are only accessible within that function
• Variable-length arguments allow functions to accept a varying number of arguments
  • *args: Used to pass a variable number of non-keyword arguments
  • **kwargs: Used to pass a variable number of keyword arguments