Docstrings In Python

Docstrings in Python are special text used to describe what a function, class, or module does in your Python code. They are written inside triple quotes and after the definition. Docstrings help you understand the purpose of the Python code without the need to read every line. Unlike regular comments, docstrings can be accessed using the help() function. Using the docstrings makes the code clean and readable. In this blog, you will learn the implementation, formatting, and application of docstrings in detail with examples.

Table of Contents:

• What are Docstrings in Python?
• Why Should You Use Docstrings in Python Code?
• How Docstrings Work Internally in Python?
• Different Types of Docstrings in Python
  • What Is a Module-Level Docstring in Python?
  • How to Write Function and Method Docstrings in Python?
  • How to Document Classes Using Docstrings in Python?
• Accessing Python Docstrings Using help() and doc
• Key Features and Advantages of Python Docstrings
• Benefits of Using Python Docstrings for Collaboration
• Docstrings vs Comments in Python: A Detailed Comparison
• Real-World Use Cases for Python Docstrings
• Best Practices to Write Effective Python Docstrings
• Conclusion

What are Docstrings in Python?

In this section, you will be introduced to docstrings and how they differ from your general Python comments. Docstrings, or documentation strings, are literal strings that are kept as the first statement in a function, class, or module. Comments are completely ignored when the program runs, but docstrings are saved inside a special attribute called __doc__ and can be used in the program.

For Example:

Output:

Explanation: The function will print a greeting and return its documentation through the __doc__. This shows us that Python stores the docstrings for accessing and usage later. 

Ready to code but not sure where to begin?

Join our free Python fundamentals course

Explore Program

Why Should You Use Docstrings in Python Code?

Docstrings in Python help you understand what every component of your code performs without going into the implementation. They will provide metadata for the tools for documentation and powerful IDE features, for example, hover-to-view help. It will also integrate seamless tools such as help() and pydoc.

Example:

Output:

Explanation: Here, the Python help function returns and displays the docstring along with the structured documentation without reading the source code.

How Docstrings Work Internally in Python?

Docstrings in Python aren’t just comments, they are stored as metadata within Python objects like functions, classes, and modules. When you place a string right after a definition, Python saves it in a special attribute called __doc__. This allows you to access it later using object.__doc__ or the help() function, unlike regular comments, which are ignored at runtime.

Internally, Python compiles your code and stores docstrings in the co_consts attribute of the object’s code object, making the docstring the first constant in that list. This design lets tools and IDEs retrieve documentation dynamically. Python doesn’t treat triple quotes any differently than single-line strings in memory—they’re just a convenient way to write multi-line, structured text.

Overall, docstrings function as part of Python’s introspection system, helping with documentation, collaboration, and readability across codebases.

Different Types of Docstrings in Python

In this section, you will be informed regarding the various types of docstrings that the Python language supports for modules, functions, and classes.

1. What Is a Module-Level Docstring in Python?

The module-level docstring in Python describes the functionality provided by a Python file.

Example:

Explanation: Here, Docstrings at the module level summarize the file’s purpose and are typically placed at the very top of the .py file. They can be accessed using the code import math_utils, and in the next line, write print(math_utils.__doc__).

2. How to Write Function and Method Docstrings in Python?

The function in Docstrings defines what the function does, expected parameters, return values, and exceptions.

For example:

Output:

Explanation: Here, the function would include a properly formatted docstring with detailed inputs, outputs, and the function’s core purpose.

3. How to Document Classes Using Docstrings in Python?

The class docstrings in Python help to describe the role and the capabilities of the class.

Example:

Output:

Explanation: Here, the class and the method docstrings both can be retrieved, giving context at both structural levels.

Accessing Python Docstrings Using help() and doc

Python provides two primary ways to access docstrings at runtime: the help() function and the __doc__ attribute. Both are essential tools for understanding code behavior without needing to read the entire source. They offer clean, structured insights—making them invaluable in collaborative projects, code reviews, and when working with third-party libraries.

The help() function in Python:

The help() function is Python’s built-in interactive documentation system. It’s essentially a wrapper that formats and presents the information found in the __doc__ attributes of Python objects like classes, modules, and functions.
When you type help(object_name), Python fetches and formats the docstring of that object and displays it to you in a readable manner.

Example:

Output:

Explanation: This gives you a neatly formatted overview of the function and its documentation.

Using the help() Function to Read Docstrings
The power of help() lies in its ability to recursively dive into the object’s properties. For modules and classes, help() also explores method docstrings and attribute documentation. This is incredibly helpful when exploring unfamiliar code or libraries.

Example:

Output:

Explanation: You’ll see both the class-level and method-level docstrings presented, which is great for understanding what the class is for and how to use its methods.

Key Features and Advantages of Python Docstrings

This section outlines the capabilities of utilizing docstrings and the advantages of using docstrings over traditional comments in Python.

• Multiline and Structured: Triple quotes allow line breaks, giving freedom to write detailed explanations.

• Runtime Accessibility: Docstrings are stored in __doc__ and can be retrieved using introspection tools.

• Documentation Tool Integration: Tools in Python, with the likes of Sphinx, pdoc, and help(), can parse and display docstrings.

• Support for Formatting Styles: Formats like Google style, NumPy style, and reStructuredText provide consistency.

• Useful in IDEs: Most modern IDEs show docstrings in tooltips, making them immediately useful during development.

Benefits of Using Python Docstrings for Collaboration

1. Improves Team Communication: Well-written docstrings in Python clearly explain the purpose of code, helping teammates, reviewers, and new developers understand it without digging through every line.
2. Reduces Onboarding Time: New contributors can quickly grasp what functions and classes do just by reading their docstrings—no need to analyze all logic manually.
3. Enhances Code Review Efficiency: During reviews, Python docstrings help assess whether the logic aligns with the intended functionality. This speeds up the process and reduces back-and-forth.
4. Supports Documentation Tools: Consistent formatting (e.g., Google or NumPy style) makes it easier to auto-generate docs with tools like Sphinx, pdoc, and IDE integrations.
5. Boosts IDE Support: Most IDEs show docstrings as tooltips during development, making coding faster and more intuitive.
6. Ensures Long-Term Maintainability: Structured Python documentation allows for easier updates, bug fixes, and reuse across projects.

Docstrings vs Comments in Python: A Detailed Comparison

The difference between comments and docstrings in Python is explained below:

Feature	Docstrings	Comments
Purpose	Used to define the functionality of modules, functions, and classes in a structured format.	Used to define logic or leave notes in code without affecting execution.
Syntax	Enclosed in triple quotes like """Docstring"""	Starts with a # symbol.
Scope	Associated with functions, classes, and modules; accessible programmatically at runtime using __doc__.	Inline only; not accessible during program execution.
Tooling Support	Used by help(), IDEs, and documentation generators like Sphinx or pdoc.	Ignored by documentation tools and IDEs.
Best For	Documenting “what and why” in a user-facing and maintainable way, aligning with Python coding standards.	Clarifying internal logic, adding TODOs, or implementation-specific notes.
Real-World Application in Projects	Used in collaborative environments for clean and consistent Python documentation, accessible via __doc__ and help(); supports tools and onboarding. (Python doc attribute, examples of Python docstrings)	Helpful for internal developer notes, debugging, or future reminders, but not visible to tools or contributors outside the source code. (Python comments)

This table helps developers decide when to use Python docstrings vs comments in their projects, making code both functional and developer-friendly.

Real-World Use Cases for Python Docstrings

In the section below, you will be shown examples of Python docstrings to implement in your coding sessions:

Use case 1 (To document a data validation utility):

We can utilize docstrings in utility functions that get reused often. Here’s an example of such validation that checks if an input is a valid email.

Example:

Python

Copy Code

Code Copied!

Close Code

Output:

Explanation: You use the docstring here to describe input expectations (a string), and output type (bool), and even provide testable examples. This helps both manual readers and auto-generated documentation tools understand the utility instantly.

Use case 2 (Defining a custom class for logging)

Attempting to define a class that is meant to be reused (e.g., a logger), and having structured docstrings at the class and method level can ensure clarity on how you can use it and what each method does.

Example:

Python

Copy Code

Code Copied!

Close Code

Output:

Explanation: 

Here, the use case shows you how docstrings can help guide you to instantiate a class, what parameters you are meant to pass, and how to implement each method. Docstrings also explain internal attributes for both the class and its methods, which can be useful for advanced usage or extension.

Use of docstring in this use case:

The main utility of docstrings in this case is to outline class attributes, construct parameters, and method behaviors, making it quite easy for someone to adopt it with minimal effort.

Best Practices to Write Effective Python Docstrings

Try to be clear and concise: It is better to begin with a summary in a single line, which is followed by more details if necessary.

Utilize triple quotes for multiline docstrings: Even in the case of the string being short, stick to the triple quotes for consistency and clarity.

Keep following a style guide: Better to pick a format like Google or NumPy style and use it across your codebase.

Keep documentation of parameters and return types: It makes your code self-document by stating the expected input/output explicitly.

Try to include examples when useful: Keep in mind to add usage examples to the docstring.

Want to fast-track your career or ace your next coding interview?

Our Premium Python Course includes real-world projects, 1-on-1 mentorship, and certification to prove your skills.

Explore Program

Conclusion

Docstrings are an essential part of Python that allows you to add readable text to your code. They describe what a function, class, or module does, which helps in making your code easier to understand. Unlike comments, docstrings are saved in memory and work with tools like help() and pydoc. Docstrings are very helpful when a group of people is working and modifying the same code. Proper docstrings make your code better, help avoid mistakes, and make it easier for others, including you, to understand and use.

Further, upgrade your Python skills by visiting a Python certification course, and get ready to excel in your career with Basic Python interview questions prepared by experts.

Boost your coding skills by exploring file operations and modules under Python Basics–

How to Parse a String to a Float or Int in Python – Here’s a quick guide on how to parse a string into a float or int in Python.
Python Arithmetic Operators – To understand Python arithmetic operators quickly, this reference provides clear examples.
Python Comparison Operators – When working with Python comparison operators, this quick reference can help you get started.
Python Assignment Operator – For a fast overview of Python assignment operators, this guide covers the essentials.
Python Bitwise Operators – If you need to use Python bitwise operators, this quick reference outlines the basics.
Python Membership and Identity Operators – To learn about Python membership and identity operators efficiently, this resource is helpful.
Python Docstrings – When documenting your Python code, this quick guide explains how to use docstrings effectively.
Access Environment Variable Values in Python – For accessing environment variable values in Python, this quick reference offers practical tips.
Python: How to Get the Last Element of List – To retrieve the last element of a list in Python, this guide provides a simple and fast approach.
Access Index Using For Loop in Python – When iterating over list indices with a for loop in Python, this quick reference shows how to do it correctly.

Docstrings In Python-FAQs

Q1. What if we use docstrings for the single-line documentation in the Python language?

Yes, we would have to ensure it is enclosed in triple quotes, which in turn will ensure compatibility with tools and standardization.

Q2. Are docstrings capable of affecting my performance?

The Docstrings are stored once per function/module/class and can only be accessed if it is explicitly requested. Hence, they do not affect performance.

Q3. When working in Python, are docstrings usually mandatory?

Language might not need them, but it is still best practice, considering production code and libraries.

Q4. How do IDEs use Python docstrings?

Most modern IDEs display docstrings as pop-up documentation during coding. Tools like help() also show them in interactive shells.  

Q5. How to write docstrings in Python?

Use triple quotes right after defining a function or class to describe its purpose and behavior.

Q6. What is a docstring in Python with example?

A docstring is a string literal used to document a function, class, or module. e.g., def add(x, y): “””Return the sum.””” return x + y.

Q7. What is the difference between docstring and comment in Python?

Docstrings are stored and accessible at runtime via __doc__, while comments (using #) are ignored by the interpreter.

Q8. How do you access a docstring in Python?

Use object.__doc__ or help(object) to retrieve the docstring of a function, class, or module.

Q9. Do docstrings affect runtime performance?

No, docstrings have negligible impact on performance unless the code is run with -OO optimization which strips them.

Q10. When to use docstrings in Python?

Use docstrings to document functions, classes, and modules—place them right after the definition using triple quotes. They’re ideal for making your code self-explanatory and accessible via help() or __doc__.