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
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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?
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
Comments in Python are essential for code documentation, readability, and collaboration. They provide valuable insights into the purpose, functionality, and logic of your code, enhancing its comprehensibility for both developers and maintainers. If you are wondering about how to comment in Python, this guide is for you. In this tutorial, we'll explore the advantages of using comments and the various types of comments available in Python.
In this tutorial, we will delve into the world of comments in Python, exploring their diverse advantages. We will also touch upon how comments serve as crucial documentation tools, enhancing code readability, aiding in debugging, promoting collaboration, and ensuring future maintainability. The tutorial will also examine different types of comments and their practical applications within Python code.
Comments in Python are textual annotations within the code that are used to provide explanations, descriptions, or notes about the code. These comments are ignored by the Python interpreter and serve only as documentation for programmers reading the code.
Python supports two types of comments. Let us check out the two types of comments in python with examples.
Example:
# This is a single-line comment
Example:
'''
This is a multi-line comment or docstring.
It provides detailed information about a function or class.
'''
Here are some reasons why comments are extremely important:
Here is how we can use comments:
Example:
Example:
Let us delve deeper into writing good comments in Python and learn how to effectively use comments while programming:
Comments should be crystal clear and concise, aiming to convey information effectively. Avoid jargon, overly technical terms, or ambiguous language. Think of your comments as a bridge between code and human understanding. Consider the following:
# Bad comment
x = x + 1 # Increment x by 1
# Good comment
x += 1 # Increment x by 1
In the "good comment" example, the purpose of the code is clear without unnecessary redundancy.
Correct grammar and punctuation enhance the readability of your comments. Write comments as complete sentences with appropriate capitalization and punctuation. This practice contributes to professionalism and clarity:
# Bad comment
calculate average # Missing subject and punctuation
# Good comment
# Calculate the average. # Complete sentence with punctuation
Besides explaining what the code does, focus on why it's necessary. Provide context or reasons for specific implementations. This helps readers understand the motivation behind the code:
# Bad comment
result = complex_calculation() # Calculate result
# Good comment
# Perform a complex calculation to obtain the result needed for financial reporting.
result = complex_calculation()
The "good comment" explains the purpose behind the calculation.
As code evolves, comments must evolve with it. Whenever you make changes, remember to update the associated comments. Outdated comments can mislead readers and create confusion:
# Old comment
x = 5 # Initialize x to 5
# After code update
x = 10 # Initialize x to 10
Maintaining up-to-date comments ensures that the code's documentation remains reliable.
Resist the temptation to duplicate information that's already evident from the code itself. Comments should provide additional context or insights that aren't immediately apparent:
# Bad comment
total = price + tax # Calculate the total price
# Good comment
total = price + tax # Add tax to the price to determine the total cost
In the "good comment," the explanation adds value by describing the purpose of the calculation.
Choose variable and function names that convey their purpose. Well-named entities reduce the need for extensive comments. Your code becomes self-documenting:
# Bad comment
a = calculate_total(orders) # Calculate the total of all orders
# Good comment (with meaningful names)
total_orders = calculate_total(order_list)
In the "good comment," meaningful variable and function names make the comment almost unnecessary.
Detail how the code handles edge cases, exceptions, or unusual scenarios. This ensures that readers understand the code's robustness and behavior in various situations:
# Bad comment
# Handle errors
# Good comment
# Handle potential division by zero errors when calculating the average.
The "good comment" clarifies what errors are being handled.
Consistency is essential, especially in team projects. Adhere to the coding style guidelines of your organization or community. Consistent commenting style includes using consistent comment symbols (# for single-line comments, triple quotes for docstrings) and indentation:
# Bad comment (inconsistent indentation)
def my_function():
# Do something
# Good comment (consistent indentation)
def my_function():
# Do something
Leverage docstrings for documenting functions, classes, and modules. Docstrings provide a structured way to explain functionality, parameters, and return values:
def calculate_total(order_list):
'''
Calculate the total cost of a list of orders.
Parameters:
order_list (list): A list of order amounts.
Returns:
float: The total cost of all orders.
'''
total = sum(order_list)
return total
Docstrings offer in-depth documentation and can be accessed using tools like help() and Sphinx for generating documentation.
Always write comments with the assumption that someone else, or even your future self, will read and understand the code. Aim for clarity and comprehensibility. Your comments should be a helpful guide to deciphering the code, even years after its initial creation.
In Python, string literals enclosed in single or double quotes can also serve as comments, although they are not true comments. These string literals are typically used for documentation purposes. While they don't affect the code's functionality, they can be accessed as attributes of functions, classes, and modules:
Example:
def load_data():
"""Load data from a CSV file into a DataFrame."""
# Actual code for loading data here
String literals can be accessed programmatically, making them useful for generating documentation using tools like Sphinx.
Docstrings are a special form of string literal used for documenting functions, classes, and modules. They are more structured than regular comments and are accessed using the help() function or tools like Sphinx for documentation generation. Docstrings are typically enclosed in triple quotes and provide information about the purpose, parameters, return values, and usage of the code entity.
Example:
def calculate_discounted_price(original_price, discount):
'''
Calculate the discounted price of a product.
Parameters:
original_price (float): The original price of the product.
discount (float): The discount percentage (e.g., 20 for 20% off).
Returns:
float: The discounted price.
Example:
>>> calculate_discounted_price(100.0, 20.0)
80.0
'''
discounted_price = original_price - (original_price * (discount / 100))
return discounted_price
Docstrings are considered the most formal and informative way to document Python code, especially for functions and classes.
Let us discuss the advantages of using comments in Python in detail:
1. Code Explanation: Comments provide a means to explain the purpose and functionality of code. They act as documentation within the code itself, helping developers and collaborators understand what the code does. Code can be complex, and comments simplify it by breaking down the logic into understandable segments. This is especially important when dealing with intricate algorithms or business logic.
2. Enhancing Readability: Well-placed comments enhance code readability. Code is not just for the machine; it's also for human developers who need to understand and modify it. Comments label sections of code, making it easier to navigate and locate specific functionality or variables. This is valuable in large projects where codebases can be extensive.
3. Debugging and Troubleshooting: Comments can help in debugging and troubleshooting by providing insights into the code's expected behavior. Developers can compare actual behavior with the comments to identify discrepancies. When errors occur, comments can pinpoint potential issues, making it quicker to isolate and fix problems.
4. Collaboration and Knowledge Sharing: In team projects, comments serve as a communication tool. They allow team members to share information about code segments, making it easier to collaborate effectively. Comments also facilitate knowledge transfer between team members. New developers joining a project can quickly grasp the code's functionality with well-documented comments.
5. Future Maintenance: Code is rarely static; it often undergoes updates and maintenance. Comments help future maintainers understand the original author's intentions and design choices. Developers can confidently modify and extend code without the fear of unintentional side effects because they have a clear understanding of what each part does.
6. Compliance and Best Practices: In regulated industries or projects with coding standards, comments may be required to comply with documentation and quality assurance rules. Following best practices, such as including comments, promotes code quality and consistency across projects.
7. Documentation Generation: Comments, especially docstrings, can be automatically extracted to generate documentation. Tools like Sphinx can create professional documentation from well-structured comments. This documentation can be crucial for project users, API consumers, and other stakeholders.
8. Code Review Assistance: During code reviews, comments can guide reviewers by providing context and explanations. This streamlines the review process and ensures that the code aligns with project requirements and standards.
Comments in Python are not just annotations; they are a fundamental aspect of code development. They serve as a bridge between the code and its human readers, facilitating understanding, collaboration, maintenance, and adherence to best practices and standards. Well-crafted comments contribute to the overall quality and sustainability of software projects.
Python offers several ways to include comments and documentation in your code. Single-line comments (#) are suitable for brief notes, while multi-line comments (using triple-quoted strings) can provide more extensive explanations. String literals can serve as comments but are often used for documentation. However, docstrings are the most structured and recommended way to document functions, classes, and modules, providing detailed information for code users and maintainers.
If you wish to learn more about programming in Python, you can check out the various programs offered by upGrad.
1. What is comment in Python?
Comments are a way of documenting your code. Comments make it easier to troubleshoot and maintain code.
2. How to add comment in Python?
Comments can be added in Python with the help of hash symbol (#) for single-line comments and triple quotes (''' or """) for multi-line comments.
3. Are comments important?
Comments are very important and they increase the readability of your code and help users or other team members debug the code easily.
PAVAN VADAPALLI
Director of Engineering
Director of Engineering @ upGrad. Motivated to leverage technology to solve problems. Seasoned leader for startups and fast moving orgs. Working …Read More
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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...