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In the previous post we have:
So, some decisions are taken care of. We have some of the tools and have decided what the repository will look like.
This is one of the things that I love about Polylith: it doesn't matter what you're coding or how big your organization is, all the repositories will look the same - if you need more than one.
Your repository structure is consistent, whether you're using FastAPI, Flask, or Django, building single or multiple libraries, or running background tasks with Celery.
One of the key advantages is the streamlined onboarding process for new developers. Assuming they have a grasp of Polylith, they'll quickly become familiar with the project structure: reusable components are in the components folder, entry points are in the bases folder, demo scripts are in the development folder, and so on.
From Uncle Bob "The Clean Architecture" entities are the cornerstone of our architecture, they are the most inner layer of our architecture. So we need to start with them, in Polylith entities should live as components.
How many components?
I believe the number of components depends on the size and complexity of your solution. However, I recommend starting with a single polylith component for entities. This approach helps maintain a clear and focused architecture, especially for smaller projects.
Why a single component for entities?
Avoid third-party dependencies.
To minimize external dependencies and enhance architectural flexibility, strive to use Python's standard library for representing entities. This includes leveraging data structures like dict, list, enum, functions, classes and more recently dataclasses.
Why avoid third-party libraries like Pydantic or Django Models?
By adhering to these principles, you can create a robust and maintainable architecture that is resilient to future changes.
Our example is straightforward, with the core entity being the "todo item" for Gordon. We can add a new component to our repository, but choosing the right name is crucial.
While it might be tempting to use generic names like "core" or "main," it's essential to select names that are meaningful within the domain context. Ideally, these names should align with the terminology used by the client or product owner. By using domain-specific names, we enhance code readability and maintainability, making it easier for both developers and stakeholders to understand the project's structure.
The repository workspace name is defined as todo. Consequently, all our imports will follow the format:
from todo.XYZ import ... import todo.XYZ
For simplicity in this example, we'll use entities as the component name. However, in real-world scenarios, consider naming conventions that reflect your domain. For instance, if your application revolves around document recovery, a component named recovery would be appropriate. Similarly, a gaming application might use tournaments_entities for clarity.
Creating the component with Python Polylith is simple:
poetry poly create component --name=entities poetry poly sync poetry install # it may be necessary
This will add a python package in the components folder, this are the new entries in the source tree:
./components └── todo └── entities ├── __init__.py └── core.py ./test/components └── todo └── entities ├── __init__.py └── test_core.py
The python-polylith tool will generate test examples for us, which is a nice feature. This behavior can be changed in the workspace.toml file by setting the enabled = true value to false in the [tool.polylith.test] section.
In the new entities component, two files are added: __init__.py and core.py. You can rename the core.py module to better suit your needs. The common practice is to expose the public API of the package through __init__.py, while maintaining internal organization within other modules like core.py.
From the requirements, we has, at the moment, only one entity, the ToDo item:
@dataclass class TodoItem: owner: str title: str description: str is_done: bool = False due_date: Optional[date] = None
Testing such a simple entity might seem unnecessary, but I prefer to test at least the presence of all fields. While this may not seem crucial in smaller projects with fewer contributors, it can prevent significant issues in larger projects with many developers. Removing a single field from the entity can inadvertently break various parts of the application.
In the pull request for this part, you will see that i have added some basic tests for this entity.
With some tests already defined, I took the opportunity to add a GitHub workflow to automatically run the tests for each pull request.
What is next: Let's talk about persistence
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