Introduction to MkDocs and Building Documentation
Building robust, user-friendly software is one of the top priorities of any development team. A vital component of achieving this is through good documentation that helps the users understand your software better.
MkDocs is a powerful documentation generation tool that can help you build beautiful and easy-to-use documentation. Building on top of this, mkdocstrings is an extension that allows you to automate your documentation generation process using Python Docstrings.
In this tutorial, we’ll explore the benefits of good documentation and provide you with a comprehensive guide to setting up an environment to build documentation using MkDocs and mkdocstrings.
Importance of Good Documentation and Ditaxis Documentation Framework
Good documentation is essential, not only for users to understand how to use your software effectively, but also for developers to maintain and improve upon it. Documentation acts as a guide for users, providing them with instructions on how best to use your product.
It helps to clarify any misunderstandings that may arise and prevent users from making costly mistakes. For developers, documentation summarizes the purpose and the functionality of the software, making it easier to maintain and debug.
The more comprehensive the documentation, the easier it will be for future developers to understand and build on the original code. The Ditaxis documentation framework is an excellent tool that assists developers in creating thorough and easy-to-use documentation for their software projects.
Whether you’re a developer or a user, Ditaxis documentation framework makes it easy for anyone to understand how to use software products effectively.
Prerequisites for the Tutorial
Before diving into the actual tutorial, there are a few prerequisites that you should have in place. First and foremost, you will need to have Python version 3.6 or higher installed on your machine.
If you don’t have it installed, you can download the latest version from the official Python website. Secondly, you will need pip installed to manage your Python packages.
Pip is a package installer that makes it easy to install packages for Python. To install pip, you can follow the official Python documentation on how to install pip.
Lastly, you will need to have a text editor installed on your machine. Some popular options include Visual Studio Code, PyCharm, and Sublime Text.
Setting Up Environment for Building Documentation
With the prerequisites in place, we can start setting up the environment for building documentation using MkDocs and mkdocstrings.
Creating Project Folder and Virtual Environment
Start by creating a new folder where you will store your project files. Open up your preferred terminal and navigate to your chosen directory.
Now, create a new folder using the mkdir command followed by the name of your new project folder. $ mkdir my-project
With your project folder created, navigate into it using the cd command.
$ cd my-project
Next, create a new virtual environment using the virtualenv command. This will keep your projects dependency separate from your systems global Python installation, which is beneficial when working on multiple projects.
$ virtualenv venv
Activate the virtual environment using the source command. $ source venv/bin/activate
Installing Necessary Packages
The next step is to install the necessary packages we need to set up our environment. First, install the mkdocs package using pip.
$ pip install mkdocs
Next, install the mkdocs-material package, a theme used to customize the documentations design and look. $ pip install mkdocs-material
Finally, install the mkdocstrings package, which will automate the documentation generation process using Python Docstrings.
$ pip install mkdocstrings
Confirm Installation Worked
To confirm that everything has been installed correctly, execute the pip list command, which will display a list of currently installed Python packages. $ pip list
You should see mkdocs, mkdocs-material, and mkdocstrings among the packages installed.
If you don’t see any of these, carefully follow the preceding steps again.
Conclusion
In conclusion, setting up an environment for building documentation using MkDocs and mkdocstrings is easy enough with the right set of instructions. Make sure you have the prerequisites in place before you begin, and you will be up and running in no time.
Remember to put time and effort into your documentation, as it can ultimately determine whether your project is understood and adopted successfully or not. Develop a clear and concise documentation and demonstrate with examples for users.
With MkDocs and mkdocstrings, creating powerful, easy-to-use documentation is within reach, even for those new to the process of documentation generation.
3) Writing and Formatting Docstrings
In Python, docstrings are a string literal that are used to describe modules, functions, classes, and methods. Docstrings are an essential part of any Python project as they help to document the purpose, arguments, and return values of a function or module.
They are traditionally enclosed in triple quotes and appear at the beginning of the Python object they describe.
Explanation of Python Docstrings and Their Structure
Python docstrings have a specific structure to follow. They typically have three parts: a one-line summary, an optional extended description, and descriptions of the parameters and return values.
The summary should describe the purpose of the object, while the extended description can provide more detail. Parameters should be described using the following format: parameter_name (type): description.
The return value should be described in a similar manner. Here’s an example of a well-structured docstring for a function that adds two numbers:
def add_numbers(num1: int, num2: int) -> int:
"""
Adds two numbers together and returns the result.
Args:
num1 (int): The first number to add.
num2 (int): The second number to add.
Returns:
The sum of num1 and num2.
"""
return num1 + num2
Adding Function Docstrings to Python Project
When writing Python projects, it’s essential to add docstrings to your functions. Adding docstrings ensures that your code is self-explanatory and that future modifications can be made without altering the original intention.
To add a docstring to a function, simply wrap the description in triple quotes immediately following the function signature. When documentation is generated, the docstring will appear as the function’s documentation.
Adding Examples and Using Doctest to Test Them
A great way to make your documentation more user-friendly is by including examples. Including examples makes it easier for developers to understand how to use your code’s functionality.
One way to test these examples is by using doctest. Doctest is a testing tool built into Python’s unittest module that makes it easy to test docstrings.
For example, suppose we have added an example to our add_numbers() function:
def add_numbers(num1: int, num2: int) -> int:
"""
Add two numbers together and return the result.
Args:
num1 (int): The first number to add.
num2 (int): The second number to add.
Returns:
The sum of num1 and num2.
Example:
>>> add_numbers(2, 3)
5
>>> add_numbers(0, 0)
0
"""
return num1 + num2
We can use doctest to test these examples by running:
python -m doctest -v my_module.py
This will run all the examples in the docstring and automatically check the output to ensure that it’s correct.
Using Type Hints to Provide Automatic Type Information
Type hints are another way to make your code more self-explanatory. Type hints provide information about the type of data that should be passed to a function or class.
Type hints make it easier for other developers to understand what kind of input the function is expecting and what kind of output it will return. Here’s an example of a function with type hints:
def add_numbers(num1: int, num2: int) -> int:
"""
Add two numbers together and return the result.
Args:
num1 (int): The first number to add.
num2 (int): The second number to add.
Returns:
The sum of num1 and num2.
"""
return num1 + num2
Adding Module and Package Docstrings
In addition to adding docstrings to individual functions, it’s also essential to add docstrings to modules and packages. A module docstring should provide a high-level overview of what the module contains.
A package docstring should describe what the package contains and what its purpose is. Here’s an example of a module docstring:
"""
This module contains functions for working with numbers.
"""
def add_numbers(num1: int, num2: int) -> int:
"""
Add two numbers together and return the result.
Args:
num1 (int): The first number to add.
num2 (int): The second number to add.
Returns:
The sum of num1 and num2.
"""
return num1 + num2
Here’s an example of a package docstring:
"""
This package contains functions for working with numbers.
Modules:
add_numbers: A function for adding two numbers.
"""
4) Preparing Documentation with MkDocs
MkDocs is a simple, easy-to-use documentation generator that is well-suited for projects of all sizes. MkDocs takes written documentation in Markdown format and outputs it as a beautiful, organized website.
Here’s how to prepare documentation using MkDocs.
Creating MkDocs Project Structure
To start, we need to create an MkDocs project. Create a new directory for your project and use the MkDocs command-line tool to initialize the project.
$ mkdir my_docs
$ cd my_docs
$ mkdocs new .
This will create a new MkDocs project with a default file structure.
Adapting Project Settings File
The next step is to adapt the project’s settings file. This file contains configuration options that control how the documentation is generated.
To open the project’s settings file, navigate to the root of your project directory and open the file called ‘mkdocs.yml’ in a text editor. In the settings file, you can specify the name of your project, configure the theme, and set the location of the documentation files, among other things.
Creating Static Pages from Markdown
With the settings file configured, it’s time to create the actual documentation pages using Markdown. To create a new page, simply create a new Markdown file in the ‘docs’ folder of your MkDocs project.
Once you have created your Markdown file, you can add content using the Markdown syntax.
Inserting Information from Docstrings
One of the benefits of using MkDocs is that you can easily include the information from your Python docstrings in the documentation website. To do this, we’ll use the mkdocstrings extension.
First, you need to install the mkdocstrings package:
$ pip install mkdocstrings
Once the package is installed, add it to the list of MkDocs plugins in your project’s settings file. Here’s an example:
plugins:
- search
- mkdocstrings:
default_handler: python
With the mkdocstrings plugin set up, we can now add Python code snippets to our Markdown pages using the special syntax:
``` python
Python code here
```
When MkDocs generates the documentation website, it will automatically include the appropriate docstrings for each Python code snippet.
Conclusion
In conclusion, preparing documentation in Python using MkDocs and mkdocstrings is straightforward and essential to having well-documented code projects. By following the guidelines for writing Python docstrings and leveraging the power of MkDocs, you can create documentation that is both informative and easy to use.
With these tools in your arsenal, creating quality documentation has never been easier.
5) Building Documentation with MkDocs
Once you have created and prepared your documentation using MkDocs, it’s time to build the documentation website. Building documentation is a straightforward process with MkDocs.
To build the documentation, navigate to your project directory in your terminal/command prompt and run the following command:
$ mkdocs build
This will generate a new directory called ‘site’ that contains the static HTML files for your documentation website. You can now preview the site by entering mkdocs serve into the command line and opening up http://127.0.0.1:8000 in your browser.
You’ll see your documentation displayed as a local version on your computer. Once you have verified everything looks good, you can deploy your website to a web server or GitHub Pages.
6) Hosting Documentation on GitHub
Hosting your documentation on GitHub Pages makes it easy for others to find and use your documentation. To get started, you’ll need to create a new repository on GitHub for your documentation.
Creating a GitHub Repository
To create a new repository on GitHub:
- Sign in to your GitHub account and click the ‘New repository’ button on the left-hand corner.
- Name your repository and choose whether to make it public or private.
- After naming and setting the visibility options of your repository, click ‘Create repository.’
Deploying Documentation to GitHub
Once you have created the repository on GitHub, you can then deploy your documentation using the following command:
$ mkdocs gh-deploy
This command will build the documentation and deploy it to a new branch called gh-pages. The files in the gh-pages branch are automatically hosted by GitHub Pages, so you can now view the site by going to your repository’s page in your browser.
Keep in mind that depending on the size of your documentation, hosting on GitHub Pages for free may not be enough, and you’ll need to upgrade your account or use a different hosting service.
Conclusion
In this tutorial, we have covered everything you need to know about building documentation with MkDocs and hosting it on GitHub. From setting up your Python project with the necessary packages to generating documentation with MkDocs and deploying it to GitHub, you can now create professional-looking documentation that is easy to use and understand.
Using the tools we have covered in this tutorial can provide significant benefits to your development team, including the ability to onboard new developers more quickly and ensure that your codebase is well-documented and self-explanatory.
Next Steps
Now that you have learned the basics of building and hosting documentation, you can continue to improve your documentation using advanced features such as custom themes and plugins. Additionally, you can explore other documentation generators like Sphinx and Readthedocs to find the one that best fits your team’s needs.
With a bit of effort and practice, you can create high-quality auto-generated documentation that will help your team to maintain and improve its software projects more effectively. In this tutorial, we have covered the importance of good documentation and walked through the process of setting up an environment for building documentation using MkDocs and mkdocstrings.
We then discussed the best practices for writing and formatting docstrings, as well as creating and deploying documentation using MkDocs and hosting them on GitHub. The benefits of auto-generated documentation include easier onboarding for new developers, increased efficiency for maintaining and improving codebases, and a more user-friendly experience for users.
By following the steps we have outlined, you can create high-quality documentation that will benefit both your development team and your users.