Tutorial Playlist
200 Lessons1. Introduction to Python
2. Features of Python
3. How to install python in windows
4. How to Install Python on macOS
5. Install Python on Linux
6. Hello World Program in Python
7. Python Variables
8. Global Variable in Python
9. Python Keywords and Identifiers
10. Assert Keyword in Python
11. Comments in Python
12. Escape Sequence in Python
13. Print In Python
14. Python-if-else-statement
15. Python for Loop
16. Nested for loop in Python
17. While Loop in Python
18. Python’s do-while Loop
19. Break in Python
20. Break Pass and Continue Statement in Python
21. Python Try Except
22. Data Types in Python
23. Float in Python
24. String Methods Python
25. List in Python
26. List Methods in Python
27. Tuples in Python
28. Dictionary in Python
29. Set in Python
30. Operators in Python
31. Boolean Operators in Python
32. Arithmetic Operators in Python
33. Assignment Operator in Python
34. Bitwise operators in Python
35. Identity Operator in Python
36. Operator Precedence in Python
37. Functions in Python
38. Lambda and Anonymous Function in Python
39. Range Function in Python
40. len() Function in Python
41. How to Use Lambda Functions in Python?
42. Random Function in Python
43. Python __init__() Function
44. String Split function in Python
45. Round function in Python
46. Find Function in Python
47. How to Call a Function in Python?
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48. Python Functions Scope
49. Method Overloading in Python
50. Method Overriding in Python
51. Static Method in Python
52. Python List Index Method
53. Python Modules
54. Math Module in Python
55. Module and Package in Python
56. OS module in Python
57. Python Packages
58. OOPs Concepts in Python
59. Class in Python
60. Abstract Class in Python
61. Object in Python
62. Constructor in Python
63. Inheritance in Python
64. Multiple Inheritance in Python
65. Encapsulation in Python
66. Data Abstraction in Python
67. Opening and closing files in Python
68. How to open JSON file in Python
69. Read CSV Files in Python
70. How to Read a File in Python
71. How to Open a File in Python?
72. Python Write to File
73. JSON Python
74. Python JSON – How to Convert a String to JSON
75. Python JSON Encoding and Decoding
76. Exception Handling in Python
77. Recursion in Python
78. Python Decorators
79. Python Threading
80. Multithreading in Python
81. Multiprocеssing in Python
82. Python Regular Expressions
83. Enumerate() in Python
84. Map in Python
85. Filter in Python
86. Eval in Python
87. Difference Between List, Tuple, Set, and Dictionary in Python
88. List to String in Python
89. Linked List in Python
90. Length of list in Python
91. Reverse a List in Python
92. Python List remove() Method
93. How to Add Elements in a List in Python
94. How to Reverse a List in Python?
95. Difference Between List and Tuple in Python
96. List Slicing in Python
97. Sort in Python
98. Merge Sort in Python
99. Selection Sort in Python
100. Sort Array in Python
101. Sort Dictionary by Value in Python
102. Datetime Python
103. Random Number in Python
104. 2D Array in Python
105. Abs in Python
106. Advantages of Python
107. Anagram Program in Python
108. Append in Python
109. Applications of Python
110. Armstrong Number in Python
111. Assert in Python
112. Binary Search in Python
113. Binary to Decimal in Python
114. Bool in Python
115. Calculator Program in Python
116. chr in Python
117. Control Flow Statements in Python
118. Convert String to Datetime Python
119. Count in python
120. Counter in Python
121. Data Visualization in Python
122. Datetime in Python
123. Extend in Python
124. F-string in Python
125. Fibonacci Series in Python
126. Format in Python
127. GCD of Two Numbers in Python
128. How to Become a Python Developer
129. How to Run Python Program
130. In Which Year Was the Python Language Developed?
131. Indentation in Python
132. Index in Python
133. Interface in Python
134. Is Python Case Sensitive?
135. Isalpha in Python
136. Isinstance() in Python
137. Iterator in Python
138. Join in Python
139. Leap Year Program in Python
140. Lexicographical Order in Python
141. Literals in Python
142. Matplotlib
143. Matrix Multiplication in Python
144. Memory Management in Python
145. Modulus in Python
146. Mutable and Immutable in Python
147. Namespace and Scope in Python
148. OpenCV Python
149. Operator Overloading in Python
150. ord in Python
151. Palindrome in Python
152. Pass in Python
153. Pattern Program in Python
154. Perfect Number in Python
155. Permutation and Combination in Python
156. Prime Number Program in Python
157. Python Arrays
158. Python Automation Projects Ideas
159. Python Frameworks
160. Python Graphical User Interface GUI
161. Python IDE
162. Python input and output
163. Python Installation on Windows
164. Python Object-Oriented Programming
165. Python PIP
166. Python Seaborn
167. Python Slicing
168. type() function in Python
169. Queue in Python
170. Replace in Python
171. Reverse a Number in Python
172. Reverse a string in Python
173. Reverse String in Python
174. Stack in Python
175. scikit-learn
176. Selenium with Python
177. Self in Python
178. Sleep in Python
179. Speech Recognition in Python
180. Split in Python
181. Square Root in Python
182. String Comparison in Python
183. String Formatting in Python
184. String Slicing in Python
185. Strip in Python
186. Subprocess in Python
187. Substring in Python
188. Sum of Digits of a Number in Python
189. Sum of n Natural Numbers in Python
190. Sum of Prime Numbers in Python
191. Switch Case in Python
192. Python Program to Transpose a Matrix
193. Type Casting in Python
194. What are Lists in Python?
195. Ways to Define a Block of Code
196. What is Pygame
197. Why Python is Interpreted Language?
198. XOR in Python
199. Yield in Python
200. Zip in Python
Functions are a fundamental concept in Python, allowing you to encapsulate and reuse code blocks. In this comprehensive guide, we will explore how to call a function in Python various aspects of functions, from their features and declaration to advanced concepts like nested functions and first-class functions.
Functions are a fundamental concept in Python, serving as the building blocks for code organization, reusability, and abstraction. This comprehensive guide explores the core features of functions, from their ability to encapsulate and reuse code to their role in modularity and parameter flexibility. It covers the rules for defining functions and provides examples of creating, calling, and nesting functions. This how to call a function in Python guide delves into advanced concepts, such as treating functions as first-class objects, which enables dynamic code customization and functional programming techniques.
Functions in Python possess several key features:
Reusability: Functions allow you to define a block of code that can be executed multiple times throughout your program. This promotes code reusability and reduces redundancy.
Return function Python code
def greet(name):
return f"Hello, {name}!"
Modularity: Functions break down complex tasks into smaller, more manageable units. Each function focuses on a specific aspect of a problem, making the code easier to understand and maintain.
def function in Python code
def calculate_area(length, width):
return length * width
Abstraction: Functions abstract the implementation details. Users of a function don't need to know how it works internally; they only need to understand its purpose and how to use it.
Python code
def get_average(numbers):
total = sum(numbers)
return total / len(numbers)
Return Values: Functions can return values using the return statement. This allows functions to provide results or data back to the caller.
Python code
def add(a, b):
return a b
Parameters: Functions can accept input data through parameters, allowing them to work with different values based on the Python function arguments provided during function calls.
Python code
def greet(name):
return f"Hello, {name}!"
Scoping: Functions have their own scope, which means that variables declared inside a function are local to that function. This scope isolation prevents variable name conflicts.
def function in Python code
def calculate_area(length, width):
area = length * width
return area
Documentation (Docstrings): Functions can be documented using docstrings, which provide information about the function's purpose, parameters, and return values. This documentation is accessible using the help() function.
Python code
def calculate_area(length, width):
"""
Calculate the area of a rectangle.
Args:
length (float): The length of the rectangle.
width (float): The width of the rectangle.
Returns:
float: The area of the rectangle.
"""
return length * width
Nested Functions: Functions can be defined within other functions, creating nested functions. This allows you to encapsulate logic and maintain encapsulation.
def function in Python code
def outer_function(x):
def inner_function(y):
return x * y
return inner_function
How to define a function in Python involves several steps:
Step 1: Use the def keyword to define the function.
def function_name(parameters):
Step 2: Add a colon (:) to indicate the start of the function body.
Step 3: Indent the function body.
Step 4: Write the code that the function will execute.
Here are the examples of how to define a function in Python:
Example 1: Simple Function Declaration
Python code
def say_hello(name):
return f"Hello, {name}!"
message = say_hello("Alice")
print(message) # Output: "Hello, Alice!"
Example 2: Function with Multiple Parameters
Python code
def calculate_area(length, width):
return length * width
area = calculate_area(5, 3)
print(area) # Output: 15
Python function Example 3: Function with No Parameters
Python code
def greet():
return "Hello, World!"
message = greet()
print(message) # Output: "Hello, World!"
Example 4: Function with Default Parameter Value
Python code
def repeat_message(message, times=3):
return message * times
result = repeat_message("Python ")
print(result) # Output: "Python Python Python "
When defining functions in Python, it's essential to adhere to certain rules:
Python code
def calculate_rectangle_area(length, width):
return length * width
area = calculate_rectangle_area(5, 3)
print(area) # Output: 15
Python code
def calculate_3_times(x):
return x * 3
result = calculate_3_times(7)
print(result) # Output: 21
Python code
def def_function(x):
return x * 2
result = def_function(4)
print(result) # Output: 8
Python code
def greet(name):
return f"Hello, {name}!"
message = greet("Bob")
print(message) # Output: "Hello, Bob!"
Creating a function in Python involves the following how to call a function in a function python steps:
Step 1: Use the def keyword to define the function.
def function_name(parameters):
Step 2: Add a colon (:) to indicate the start of the function body.
Step 3: Indent the function body.
Step 4: Write the code that the function will execute.
Here are examples of how to call a function in a function Python:
Example 1: Simple Function
Python code
def say_hello(name):
return f"Hello, {name}!"
message = say_hello("Alice")
print(message) # Output: "Hello, Alice!"
Example 2: Function with Mathematical Calculation
Python code
def calculate_area(length, width):
return length * width
area = calculate_area(5, 3)
print(area) # Output: 15
Python function Example 3: Function with Conditional Logic
Python code
def get_grade(score):
if score >= 90:
return "A"
elif score >= 80:
return "B"
else:
return "C"
grade = get_grade(85)
print(grade) # Output: "B"
Example 4: Function with List Processing
Python code
def find_max(numbers):
return max(numbers)
max_value = find_max([12, 45, 78, 32, 56])
print(max_value) # Output: 78
Calling a function in Python involves the following steps:
Step 1: Write the function name.
function_name
Step 2: Add parentheses () to enclose any required Python function arguments.
function_name(arguments)
Step 3: Capture the return value if the function returns one.
Here are four examples of calling functions with their respective outputs:
Example 1: Simple Function Calling
Python code
def say_hello(name):
return f"Hello, {name}!"
message = say_hello("Bob")
print(message) # Output: "Hello, Bob!"
Example 2: Function with Return Value
Python code
def calculate_area(length, width):
return length * width
area = calculate_area(4, 6)
print(area) # Output: 24
Example 3: Function with Arguments
Python code
def greet(title, name):
return f"Hello, {title} {name}!"
message = greet("Mr.", "Smith")
print(message) # Output: "Hello, Mr. Smith!"
Example 4: Function Calling Within an Expression
Python code
def add(a, b):
return a b
result = add(3, 4) add(1, 2)
print(result) # Output: 10
Calling a nested function in Python involves several steps:
Step 1: Define an outer function.
Step 2: Define an inner function within the outer function.
Step 3: Call the inner function within the outer function.
Step 4: Call the outer function to initiate the process.
Here are four examples of calling nested functions with their respective outputs:
Example 1: Simple Nested Function
Python code
def outer_function():
print("This is the outer function.")
def inner_function():
print("This is the inner function.")
inner_function()
outer_function()
Output:
This is the outer function.
This is the inner function.
Example 2: Returning a Nested Function
Python code
def parent_function():
print("In parent function.")
def child_function():
print("In child function.")
return child_function
child = parent_function()
child()
Output:
In parent function.
In child function.
Python function Example 3: Passing Arguments to Nested Functions
The main function in python
def outer_function(prefix):
print(f"This is the {prefix} outer function.")
def inner_function(suffix):
print(f"This is the {suffix} inner function.")
inner_function("nested")
outer_function("main")
Output:
This is the main outer function.
This is the nested inner function.
Example 4: Nested Functions with Logic
Python code
def outer_function(x):
def inner_function(y):
if y > 0:
return x * y
else:
return "Invalid"
return inner_function
multiply_by_3 = outer_function(3)
result = multiply_by_3(5)
print(result) # Output: 15
In Python, functions are first-class objects, which means they can be treated like any other data type. Here are the steps and examples:
Step 1: Assign a function to a variable.
function_variable = function_name
Step 2: Pass functions as arguments to other functions.
def higher_order_function(func, arg):
Step 3: Return functions from functions.
def return_function():
Step 4: Use functions within data structures (lists, dictionaries, etc.).
Here are four examples of treating functions as first-class objects:
Example 1: Assigning Functions to Variables
Python code
def square(x):
return x ** 2
power = square
result = power(4)
print(result) # Output: 16
Example 2: Passing Functions as Arguments
Python code
def apply(func, x):
return func(x)
def cube(number):
return number ** 3
result = apply(cube, 3)
print(result) # Output: 27
Example 3: Returning Functions from Functions
Python code
def get_multiplier(factor):
def multiplier(x):
return x * factor
return multiplier
times_two = get_multiplier(2)
result = times_two(5)
print(result) # Output: 10
Example 4: Using Functions with Lists
Python code
def filter_numbers(func, numbers):
return [num for num in numbers if func(num)]
def is_even(x):
return x % 2 == 0
numbers = [1, 2, 3, 4, 5, 6]
even_numbers = filter_numbers(is_even, numbers)
print(even_numbers) # Output: [2, 4, 6]
Python functions as first-class objects exhibit several properties:
Assigning to Variables: You can assign functions to variables, allowing you to reference and call functions using those variables.
Python code
def greet(name):
return f"Hello, {name}!"
greeting_function = greet
message = greeting_function("Alice")
Passing as Arguments: Functions can be passed as arguments to other functions. This enables higher-order functions, which take functions as parameters, enhancing code flexibility and reusability.
Python code
def apply(func, x):
return func(x)
def square(number):
return number ** 2
result = apply(square, 4)
Returning from Functions: Functions can return other functions. This feature is particularly useful when creating and customizing functions dynamically.
Python code
def get_multiplier(factor):
def multiplier(x):
return x * factor
return multiplier
times_two = get_multiplier(2)
result = times_two(5)
Storing in Data Structures: Functions can be stored in data structures like lists or dictionaries, enabling the creation of data-driven code structures.
Python code
def is_even(x):
return x % 2 == 0
functions = [is_even, lambda x: x % 3 == 0]
results = [func(6) for func in functions]
Independence from Name: Functions can exist and be used independently of their names. This means you can call an anonymous (unnamed) function, such as a lambda function.
Python code
square = lambda x: x ** 2
result = square(5)
Functions are essential in Python for code organization and reusability. This guide has covered how to call a function in Python, fundamental concepts, and advanced topics like nested functions and first-class functions, empowering you to write more efficient and maintainable code.
1. What is a Python function?
A Python function is a reusable block of code that performs a specific task. It can take input, process it, and optionally return a result.
2. How do I declare a function in Python?
To declare a function, you use the def keyword followed by the function name and parameters. For example, def my_function(param1, param2):.
3. Can a function return multiple values in Python?
Yes, a function can return multiple values in Python by using data structures like tuples, lists, or dictionaries.
4. What are closures in Python functions?
Closures occur when a function accesses variables from its containing (enclosing) function. These variables are "remembered" even if the outer function has completed execution.
5. How can I handle exceptions in functions?
You can use try and except blocks to catch and handle exceptions within a function. Additionally, you can specify exception types in the except block.
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upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enr...