1. Python Programming Comments

Python comments play a vital role in writing clean, readable, and well-documented code in our projects. For every Python developer, this is also of equal importance to know various comment types and when to use them effectively alongside code blocks. This comprehensive tutorial aims to provide a deep cognition of the complexities of Python comments, covering their significance, usage, different comment types, and some best practices and also covering detailed analysis of single-line or inline, multi-line comments, and docstrings. By the end of this guide, you will understand the comments enough to wield them effectively in your Python projects.

1.1. What are Comments in Python Programming?

In coding, we often use Python comments to explain our code blocks or for other purposes. These Comment lines are bits of text that are ignored by the Python interpreter, so they don't affect how the code runs.

Instead, the Python language developers easily understand the code logic behind each code block just by reading the comments above each block. For example, if we write a comment above a block of code, it helps us and other developers understand the logic behind that code.

Moreover, these comment blocks remain in the code until we choose to delete or change them. They're like little notes that stick around to guide us through the code.

The Below Python programming example depicts the usage of a Python comment inside the code.

Comment Example

# This is a block-type Python Comment.
print('Hello World!')

2. Comment Types in Python Language

Python offers a diverse set of comment styles or types to meet different programming needs. There are three distinct types of comments in Python programming, which we can include in our code.

  1. Block Comment
  2. Single-Line or Inline Comment
  3. Multi-Line Comment or Docstrings

2.1. Block Comments

  • A block comment is a variation or sibling of the inline or single-line Python comment and is similar to PHP # comments.
  • We use the # symbol and a space to start writing block comments in our code.
  • Except, we use consecutive # symbols for Python comments that span multiple lines, which is why we term them as a block.
  • Moreover, we separate paragraphs inside a block comment separated by a line, which contains only a single # symbol.

Block Comment

# This is a block comment and it spans multiple lines.
# Provides additional context or explanation.
y = 20
The block Python comment is indented in this example.
def calculate_area(a, b):
# The 'a' variable stores the rectangle length.
# The 'b' variable stores the rectangle width.
# Multiply 'a' and 'b' to get the area of a rectangle.
area = a * b
return area

2.2. Single-Line or Inline Comments

  • We can add single-line comments in our code using a hash # symbol.
  • It is a variation of the Python block-type comment.
  • Everything that is after a # symbol is considered a Python inline comment.
  • Also, we need to add at least two spaces after the Python statement and then include our inline comment.
  • A single line or inline # comment has a span of only a single line till its end.
  • We can include several single-line or inline comments in Python programming code, as desired.

Sngle Line Comment

Single-line comment above the code.
# This is a single-line comment.
print('Hello World!')
Inline comment on the same line of the code.
print('Hello World!') # This is an inline or single-line comment.
Comment out the code statement
# print('Hello Infinity!')
print('Hello World!')
An inline Python comment is ideal to include short annotations on a single line. However, avoid overuse of this type of comment as they may clutter the code.

2.3. Multi-line Comments or Docstrings

  • Python programming allows us to add several lines of text as a comment which are termed as multi-line comments or docstrings.
  • To add a multi-line comment, we can use triple quotation marks either """ or ''' before and after the text block.
  • Each line of text between the triple quotes will become a docstring or multi-line Python comment.
  • Moreover, docstrings are a more formal way of documenting Python code.
  • These docstrings are accessible with the help of the Python help() function.
  • Hence, we can learn the purpose of Python modules, functions, classes, or methods through docstrings within these entities.

Docstrings or Multi-line Comment

This function calculates the factorial of a number.
It uses a recursive approach to achieve this.
def factorial(n):
if n == 0:
return 1
return n * factorial(n-1)
fact = factorial(3)
print(fact) ''' Print the factorial of number 3.'''

3. Understanding the Importance of Python Comments

Let's learn why writing comments is important for Python language developers and when is the best time to include a comment effectively.

3.1. Why are Comments Important in Python Programming?

  • Versatile: Comments matter a lot in every programming language from PHP to ASP, Kotlin to JAVA, Python to JavaScript.
  • A Bridge: A comment is not merely an annotation or text line, it builds a communication channel among developers.
  • Code Clarity: To explain your code logic, intention, or other peculiarities, you have to write collaborative and accessible Python code, which is only attainable by employing the power of comments.
  • Relaxed Revisions: Effectively implementing comments in your programming projects can help you in future revisions.
  • Documentation: Purposeful comments create wonderful documentation of the code project.
  • Productivity: Thus, it is ultimately that writing productive comments is a significant component of a robust codebase.

3.2. When to Use Comments in Python Code?

The logical implementation of comments in your code project is of vital importance. Below are the situations when you should consider adding a comment.

  • Complex Logic: We use a comment to explain intricate or complex logic in our Python code.
  • TODOs: Indicate the areas of the code that require future attention or modification by simply placing TODO tags in the comments.
  • Documentation: To list the purpose, and parameters, and return values of functions and methods inside docstrings.
  • Variable Descriptions: Describe the intention of using variables and their names if they are not very descriptive.
  • Algorithm or Design Explanation: Use comments to describe the overall algorithmic approach or design decisions.
  • Debugging: You can also write the debugging information, such as workarounds or specific debugging configurations inside Python docstrings.
  • Code Rules: Define code rules or domain-specific knowledge inside the docstrings.
  • Dependencies: To enlist the dependencies, libraries, or Python APIs used in the code, multi-line docstrings are helpful in each scenario.
  • Coding Conventions and Style: Try adding a comment to highlight deviations from coding conventions or styles.
  • Conditional Statements: Clarify the purpose of conditional statements, especially if the logic is not immediately apparent.
  • Code Reviews: Provide feedback and purpose inside the comments during code reviews to address specific concerns.

4. Best Practices for Writing Python Comments

  • Follow the language standards to implement the correct Python comment syntax across your projects.
  • Write concise and to-the-point comments.
  • Adhere to PEP8 guidelines while incorporating comments.
  • When it's obvious to understand, avoid adding a comment.
  • Explain only the Why and How not the What part of logic.
  • Keep track of the closing or ending part of the docstrings to avoid explicit exceptions or errors.
  • Keep updating your comment blocks as well alongside your code.

5. Concluding Python Comments Use

We have achieved an in-depth and comprehensive understanding of using all types of Python comments. Now we can conclude that effective commenting is a valuable skill for any Python programmer. Whether you're writing a single-line or inline comment, multi-line or block comments, or docstrings, the goal is to provide clarity and context to your code. By following best practices and perception of comment importance, we can contribute to creating maintainable and coherent Python code.

Give Us Your Feedback
If You Need Any Help!
Contact Us