Python Docstrings: Anto Writing Effective Documentation
Python is a popular programming language loved by many developers for its simplicity and versatility. It’s an open-source language that can be used for various purposes, such as web development, data analysis, and machine learning.
The beauty of Python is that it’s easy to learn and read, even for beginners.
However, writing effective Python code involves more than just knowing the language’s syntax and semantics.
It’s essential to write well-documented code that is easy to read and understand. This is where Python docstrings come in!
What are Python Docstrings?
Python Docstrings are a documentation string or comment that is placed at the beginning of a module, function, class, or method to explain what it does. Docstrings can be considered as a form of documentation that provides useful information about the code.
They are enclosed in triple double-quotes (“””) and can include a brief summary or a detailed explanation of the purpose of the code, any parameters that are passed, and what the code will return.
The primary purpose of docstrings is to make the code more understandable to other developers who might be working on the same project or maintain it.
Docstrings also provide context for the code and explain how it should be used, which saves time and helps to avoid confusion when trying to understand the code later.
How to Write Python Docstrings?
Writing docstrings is simple and easy. When writing a docstring, it is important to keep the contents brief, succinct, and easy to read.
It should be written in clear and concise language and avoid using technical jargon or complicated language that might be difficult for other developers to understand.
Python docstrings can be either a single-line docstring or a multi-line docstring.
Single-line docstrings are used for functions that are small and don’t require a detailed explanation of what the code does. To write a single-line docstring, you simply enclose the comment in a pair of triple double-quotes like this:
“”” This function takes in one argument x and returns a value “””
Multi-line docstrings are used for more complex functions, classes, and methods that require a detailed explanation of what the code does.
The docstring should start with a summary line, followed by a blank line, and then detailed explanations of the code. Here’s an example of a multi-line docstring:
A simple class that does nothing.
age : int
A positive integer that represents the age of the object. name : str
A string that represents the name of the object.
get_age() -> int
This method returns the age of the object.
get_name() -> str
This method returns the name of the object.
How to Access Python Docstrings? To access Python docstrings, you simply use the __doc__ method.
The __doc__ method returns the docstring of a function, module, class, or method. Here’s an example:
This function takes in 1 argument x and returns a value “””
This function takes in 1 argument x and returns a value
In conclusion, Python docstrings are an excellent tool for documenting your code. Docstrings are essential to making your code more readable and understandable, and they provide essential information to other developers working on the same project.
Docstrings should be brief, concise, easy to read, and explain the purpose of the code. Always remember to use them in your Python projects, and your code will be more readable, understandable, and maintainable.
Python Docstring Best Practices: Guidelines for Writing Effective Documentation
Writing good Python code is important, but writing good documentation is equally essential. Python Docstrings are an excellent means of documenting your code and making it more understandable to other developers working on the same project.
In this article, we will discuss the best practices for writing Python docstrings. Guidelines for Python Docstrings:
Use Docstrings for all Scripts, Modules, Functions, and Classes
Documentation should be provided for all scripts, modules, classes, and functions in your Python code. This enables other developers to understand the purpose of the code, which types of input arguments it expects, and what kinds of return types it produces.
2. List Dependencies
It is also good practice to list any dependencies that your script, module, or function requires.
This ensures that other developers are aware of which packages or modules they need to install before using your code. 3.
Describe Function and Class Behavior
Adding a brief description of the function or class behavior in your docstrings is helpful. It explains what your code does and what the output you expect is.
You should also add an example or two to make it clear what kind of inputs the function or class expects and what format the output should be in. 4.
Define Input Arguments
The input arguments that a function or method accepts should be clearly defined in the docstring. The user needs to understand the type and format of the arguments so that they can adjust / refine queries based on their specific needs.
5. Define Return Types
Along with input arguments, it is also important to specify what the return type of a function or method is.
This information provides a useful reference for other developers who are using your code. 6.
Specify Possible Exceptions
Besides successful execution, it is important to specify any exceptions that may happen when using this code. Specifying them in the docstring even if none occur helps to prevent confusion.
7. Use Case-Sensitive
It is always important to use case-sensitive docstrings.
It makes them easily recognizable by other developers. 8.
Use Enum for Function Argument Names
Using Enum for function argument names provides a significant advantage. It makes sure that any error thrown is caught during development and leaves less room for typos/bugs and other conflicts.
Python Docstring Format:
Python Docstrings can be written in plain text or following standard documentation syntax, such as Epytext, reStructuredText, or PEP-287. Python developers can choose which format they prefer to use.
The reStructuredText (reST) format is the most commonly used documentation syntax for Python Docstrings. It is also the recommended format for Python official documentation.
Here is an example of a reST docstring:
def add_numbers(a, b):
This function takes two numbers and returns the sum of them. :param a: The first number to add
:type a: int
:param b: The second number to add
:type b: int
:return: The sum of a and b
return a + b
In this docstring example, we have used the reST format to add a description of the function behavior, input arguments, and return types.
The parameters are listed with a description after them in colon-separated style. Another popular option for generating documentation is Sphinx.
Developed by the Python community, Sphinx is used for general-purpose documentation and serves as a base for the official Python documentation.
PyCharm Docstring Shortcut:
PyCharm is an Integrated Development Environment (IDE) that has a built-in feature to auto-generate docstrings.
Pycharm makes it easy for a developer to create reST formatted docstrings for their Python methods. When typing a method, put your cursor on the first line of the function.
Then press (Shift + Alt + Enter) to generate a docstring. PyCharm does the rest, auto-populating all the parameter inputs, return types, and descriptions.
In conclusion, Python Docstrings are essential to making your code more understandable, readable, and maintainable by other developers. When written effectively, they provide context for your code to include a brief summary of what the code does.
We have discussed the guidelines for writing good Python Docstrings, the different types of documentation syntax, and the PyCharm shortcut for generating Docstrings. By following these best practices, you can significantly improve the quality of your code documentation.
Why You Should Follow Python Docstring Guidelines: Importance of Code Documentation
Python Docstrings are an essential part of writing code in Python. They provide a way to document and explain the code in a way that is easily understandable to other developers.
However, simply adding comments to your code is not enough. Guidelines have been laid out in PEP-257 that provide best practices and standards for writing effective Python Docstrings.
In this article, we will discuss why you should follow these guidelines and their importance. Accessing Docstrings:
Python Docstrings are used to document your code so other developers can easily understand it and use it.
Python provides a way to access docstrings using the __doc__ method. With this method, you can access the docstring of variables, modules, functions, and classes.
This is a docstring example. “””
In the example above, we have written a function called “func” and provided a docstring.
When we call the __doc__ method on the function, it returns the docstring. Without a docstring, understanding the purpose of this code is much more difficult.
System to Parse and Generate Documentation:
Python docstrings not only make your code more understandable through the use of comments, but they also provide an automated way to generate documentation for your projects. Docstrings provide the necessary information for automated systems to parse your code and generate documentation.
Documentation of Modules, Classes, and Functions:
Python Docstrings can be used to document your entire project, including your modules, classes, and functions. This documentation enables other developers to understand the functionality and purpose of each module, class, or function.
A well-written docstring should describe the inputs and outputs of functions and methods, as well as any errors or exceptions that may occur. Preventing Abuse of Multiline Comments:
Before the standardization of Python docstrings, developers would use multiline comments to document their code.
However, this was not an ideal solution because Python parsing tools would often include these comments in error messages. To prevent this abuse, Python Docstrings were introduced as a recommended way to document code.
Using the Hash Character for Docstrings:
The hash character (#) has been used in Python programming for writing single-line comments. However, the hash character is not recommended for writing docstrings because it does not effectively communicate the purpose and functionality of the code.
It is important to use quotes for your docstrings to follow the PEP-257 guidelines. Summary:
In summary, Python Docstrings are essential to writing effective code in Python.
They provide a way to document and explain the code, making it more understandable to other developers who may use or maintain your code. The PEP-257 guidelines provide best practices and standards for writing effective Python Docstrings, which should be followed to ensure the quality of code documentation.
By doing so, you reduce the overall cognitive load on the developer ensuring a better development experience. Python Docstrings are an essential part of code documentation that provide developers with useful information about the code in a way that is easily understandable and maintainable.
Following the guidelines laid out in PEP-257 ensures the quality of code documentation and disables the abuse of multiline comments to describe the code. By following these guidelines, code documentation can be automatically parsed to generate documentation for projects, and Python developers can easily access documentation using the __doc__ method.
The importance of Python Docstrings is immense and can significantly improve the overall quality of your Python code.