Fixing Inheritance With Classmethod In Textcase

Aug 13, 2025 by Marta Kowalska 48 views

Fixing Boundary.from_delimiter as Classmethod for Inheritance in Textcase

Hey guys! Today, we're diving into a fascinating issue I encountered while working with the textcase library. Specifically, we're going to explore why the Boundary.from_delimiter method needs a little tweak to function perfectly with inheritance. Let's get started!

The Issue: `staticmethod` vs. `classmethod`

So, the heart of the matter lies in how the Boundary.from_delimiter method is currently implemented. It's marked as a @staticmethod, which, in this context, isn't quite the right choice. To really understand why, we need to dig into what these decorators mean and how they affect inheritance.

Currently, the method signature looks like this:

@staticmethod
def from_delimiter(delimiter: str) -> "Boundary":

This setup causes a problem when you try to create a subclass of Boundary. Imagine you have a CustomBoundary class that inherits from Boundary. When you call CustomBoundary.from_delimiter, you'd expect it to return an instance of CustomBoundary, right? Well, because it's a staticmethod, it doesn't! It returns a plain old Boundary instance, which isn't what we want. This is where the magic of @classmethod comes in.

Why `staticmethod` Falls Short

staticmethod essentially means the method is just a regular function that happens to live inside a class. It doesn't know anything about the class it's in, meaning it can't create instances of subclasses. Think of it like a tool sitting in a toolbox; it’s related to the toolbox, but it doesn’t know anything about the specific tools inside.

The Power of `classmethod`

On the other hand, classmethod gets the class itself as the first argument (usually named cls). This means it can create instances of the class it's called on, including subclasses! It’s like the toolbox knowing how to build more of itself, even with slight modifications. This is crucial for maintaining proper inheritance behavior, ensuring polymorphism works as expected. The method should return an instance of the calling class, not just the base class.

Demonstrating the Problem

Let’s look at some code to really drive this home. Here’s a simple example that shows the issue in action:

First, install textcase version 0.4.3:
```
pip install textcase==0.4.3
```

Now, create a file named main.py with the following content:

from textcase import Boundary


class CustomBoundary(Boundary):
    pass


print(type(CustomBoundary.from_delimiter(".")))

Run the script:
```
python main.py
```
You'll see this output:
```
<class 'textcase.Boundary'>
```

See? It's creating a Boundary object, not a CustomBoundary object! This isn't ideal, especially when you're relying on the specific behaviors of your subclasses. We expect the CustomBoundary.from_delimiter method to return an instance of CustomBoundary, but it's giving us an instance of the parent class, Boundary.

Expected Behavior: Polymorphism in Action

So, what’s the ideal scenario here? When we create a subclass like CustomBoundary, we expect that calling CustomBoundary.from_delimiter should return a CustomBoundary instance. This is a fundamental principle of object-oriented programming known as polymorphism – the ability of a method to behave differently depending on the class it's called on.

In our case, polymorphism should ensure that each subclass can create instances of its own type using the from_delimiter method. This allows subclasses to maintain their unique properties and behaviors, making our code more flexible and maintainable.

When we invoke CustomBoundary.from_delimiter, the expected behavior is that it returns an instance of CustomBoundary. This maintains the integrity of our class hierarchy and ensures that the objects we create are of the correct type, preserving any custom behavior or attributes we've added in the subclass.

The Correct Output

In the above example, instead of getting <class 'textcase.Boundary'>, we should see:

<class '__main__.CustomBoundary'>

This indicates that the method is correctly returning an instance of the subclass, as expected. Achieving this correct behavior is crucial for leveraging the full power of inheritance in Python.

The Solution: Embrace `classmethod` and Generics

Alright, so how do we fix this? The solution involves two key steps: switching from @staticmethod to @classmethod and using generics to ensure correct type hinting. Let's break this down.

Step 1: The `classmethod` Conversion

The first part is simple: we change the decorator. Instead of @staticmethod, we use @classmethod. This makes the method aware of its class, allowing it to create instances of the correct type.

Step 2: Generics for Type Safety

Now, the type hinting part is a bit more involved. We want our type checker (like MyPy or Pyright) to understand that CustomBoundary.from_delimiter returns a CustomBoundary. To do this, we use generics. Generics allow us to define type variables that represent the class itself. Here’s the code:

from typing import TypeVar, Type

TBoundary = TypeVar("TBoundary", bound="Boundary")


class Boundary:
    @classmethod  # NOTE: staticmethod -> classmethod
    def from_delimiter(cls: Type[TBoundary], delimiter: str) -> TBoundary:
        return cls()  # actual implementation


class CustomBoundary(Boundary):
    pass


print(type(CustomBoundary.from_delimiter(delimiter=".")))

# <class '__main__.CustomBoundary'>

Let’s break down what’s happening here:

We import TypeVar and Type from the typing module. These are essential for working with generics.
TBoundary = TypeVar("TBoundary", bound="Boundary") creates a type variable named TBoundary. The bound="Boundary" part means that TBoundary can be Boundary or any subclass of Boundary.
In the from_delimiter method, cls: Type[TBoundary] specifies that the first argument cls is the class itself, and it must be of the type TBoundary (i.e., Boundary or a subclass).
-> TBoundary indicates that the method returns an instance of the same type as the class it’s called on. This is the magic that makes inheritance work correctly.

Why Generics Matter

Using generics here is crucial for a couple of reasons:

Correct Return Type: Generics ensure that the return type of from_delimiter matches the calling class. Without generics, the type hint would simply be Boundary, which, as we've seen, isn't accurate for subclasses.
Type Checker Validation: Type checkers like MyPy and Pyright can now correctly validate the return type. If you try to use the result of CustomBoundary.from_delimiter in a way that’s specific to CustomBoundary, the type checker will understand that it’s safe to do so.

By using generics, we're not just fixing the runtime behavior; we're also making our code more robust and easier to reason about.

The Benefits: Why This Matters

So, we've walked through the problem and the solution. But let's take a moment to really appreciate why this fix matters. It’s not just about making the code “correct”; it’s about unlocking the full potential of inheritance and creating a more maintainable and predictable codebase.

1. Subclasses Get Their Own Type

The most immediate benefit is that subclasses now correctly return their own type from the from_delimiter method. This means that when you call CustomBoundary.from_delimiter, you get a CustomBoundary instance, not just a generic Boundary instance. This is fundamental to how inheritance is supposed to work.

Consider a scenario where CustomBoundary has additional attributes or methods. If from_delimiter returned a Boundary instance, you wouldn't be able to access those custom features directly. By returning the correct type, we ensure that all the subclass-specific functionality is available.

2. Type Checkers Validate Correct Usage

Type checkers like MyPy and Pyright play a crucial role in modern Python development. They help us catch errors early, prevent runtime surprises, and make our code more reliable. By using generics to annotate the return type of from_delimiter, we enable these type checkers to do their job effectively.

With the correct type hints in place, type checkers can verify that we're using the returned instances in a type-safe way. This is especially important in larger projects where the interactions between different classes and methods can become complex. A good type checker can catch subtle errors that might otherwise slip through testing.

3. Standard Library Only (Python 3.9+)

One of the nice things about this solution is that it relies solely on the standard typing module, which means we don't need to add any external dependencies. This is a big win for simplicity and maintainability.

Since our minimum target Python version is 3.9, we can use the typing features that are available in the standard library without needing to install typing-extensions. This keeps our project lean and avoids potential compatibility issues with external packages.

4. Aligns with PEP 673 Guidance

Finally, this fix aligns with PEP 673, which provides guidance on how to properly annotate class methods and factory functions. Following PEP 673 ensures that our code is consistent with best practices and that it behaves as expected in various situations.

PEP 673 specifically recommends using classmethod and generics for factory methods like from_delimiter. By adhering to this guidance, we're making our code more understandable to other developers and reducing the risk of unexpected behavior.

Additional Context: Python 3.9 and `typing.Self`

One thing to note is that our minimum target Python version (3.9) doesn't have the built-in typing.Self type (which was introduced in Python 3.11). typing.Self provides a more concise way to annotate methods that return an instance of the class. However, since we're targeting Python 3.9, we use TypeVar as a compatible alternative. This just shows that you need to consider compatibility when choosing tools and libraries.

Conclusion

Alright, guys, we've covered a lot in this article! We started with a bug in textcase, explored why it was happening, and then walked through a solution using classmethod and generics. We also highlighted why this fix is important for maintaining proper inheritance behavior and making our code more robust. Fixing the Boundary.from_delimiter method by changing it to a classmethod and using generics is essential for maintaining proper inheritance and type safety. This ensures that subclasses of Boundary correctly return instances of their own type, aligning with polymorphism principles and best practices.

By understanding these concepts, you'll be better equipped to write clean, maintainable Python code that leverages the power of inheritance. Keep coding, and I'll see you in the next one!