In this article, I will guide you step by step to create dynamic and interactive visual documentation using Diagram-as-Code tools. Instead of static images, we will generate diagrams programmatically, ensuring they are always up-to-date and easy to maintain.
Diagram as Code is an approach that allows you to create diagrams through code instead of traditional graphic tools. Instead of manually building diagrams, you can write code in a text file to define the structure, components, and connections of your diagrams.
This code is then translated into graphical images, making it easier to integrate and document in software projects, where it is especially useful for creating and updating architectural and flow diagrams programmatically.
Diagrams is a ?Python library that implements the Diagram as Code approach, enabling you to create architectural infrastructure diagrams and other types of diagrams through code. With Diagrams, you can easily define cloud infrastructure components (such as AWS, Azure, and GCP), network elements, software services, and more, all with just a few lines of code.
I was currently using version '0.23.4' for this tutorial.
!pip install diagrams=='0.23.4'
The library allows you to create architectural diagrams programmatically, using nodes to represent different infrastructure components and services.
Nodes in Diagrams represent components from different cloud service providers as well as other architectural elements. Here are the main categories of available nodes:
The Diagrams library allows you to use different nodes to represent various programming languages. These nodes are helpful for indicating in your diagrams if any part of your architecture utilizes scripts or components developed in a specific programming language.
Below, we will showcase all the available languages in the library. If any language is missing, you can add custom nodes by uploading the corresponding logo into a specific folder.
!pip install diagrams=='0.23.4'
We can use Amazon nodes, which are organized into several categories, such as:
Next, we will represent one of these categories to visualize the available nodes within aws.database.
!pip install diagrams=='0.23.4'
Now, let's create a simple blueprint that corresponds to importing a dataset and training a machine learning model on AWS.
# Create the diagram object
with diagrams.Diagram("Programming Languages", show=False, filename="languages"):
# Get all the languages available in this library
languages = [item for item in dir(diagrams.programming.language) if item[0] != '_']
# Divide the representation in two lines
mid_index = len(languages) // 2
first_line = languages[:mid_index]
second_line = languages[mid_index:]
# Add nodes in the first row
prev_node = None
for language in first_line:
current_node = eval(f"diagrams.programming.language.{language}(language)")
if prev_node is not None:
prev_node >> current_node
prev_node = current_node
# Add nodes in the second row
prev_node = None
for language in second_line:
current_node = eval(f"diagrams.programming.language.{language}(language)")
if prev_node is not None:
prev_node >> current_node
prev_node = current_node
Image("languages.png")
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diagram-as-code
Diagram as Code is an approach that allows you to create diagrams through code instead of traditional graphic tools. Instead of manually building diagrams, you can write code in a text file to define the structure, components, and connections of your diagrams.
This code is then translated into graphical images, making it easier to integrate and document in software projects, where it is especially useful for creating and updating architectural and flow diagrams programmatically.
Diagrams is a ?Python library that implements the Diagram as Code approach, enabling you to create architectural infrastructure diagrams and other types of diagrams through code. With Diagrams, you can easily define cloud infrastructure components (such as AWS, Azure, and GCP), network elements, software services, and more, all with just a few lines of code.
If you want to see how to implement a documentation site using this pipeline you can read the article I published in the following link
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