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Learn how to create a Python generic type that implements protocols to ensure type safety while filtering objects with specific attributes.
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How to Combine Generics and Protocols in Python for Type-Safe Filtering

In the world of Python programming, the advent of type hints and protocols has fundamentally changed how we approach type safety and design patterns. In this guide, we will explore a common problem faced when filtering lists of objects that share a certain attribute, and how to implement a solution that uses both generics and protocols effectively.

The Problem: Ensuring Type Safety While Filtering

Imagine you have a list of various objects, each with a namespace attribute. You want to create a function that filters these objects based on certain values of the namespace attribute. Here’s a simplified version of the function you might start with:

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This function works fine, but it has a significant flaw: it allows passing in objects of type X that do not have the namespace attribute, leading to runtime errors. To mitigate this issue, you decided to create a protocol, defining an object that must include the namespace attribute.

The Attempted Solution: Using Protocols

You created a protocol like this:

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And changed your filter function to use this protocol:

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At this point, you successfully ensured that any object passed into the filter function must adhere to the Namespaced protocol. However, you encountered another problem: your function now returns a list of type Namespaced instead of the original type T.

The Solution: Leveraging Bound Type Variables

To solve this issue, you need to use a bound type variable. This can be achieved by stating that your type variable T is bound to the Namespaced protocol. Here’s how you can implement that:

Step 1: Define the Type Variable with a Bound

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Step 2: Refactor the Concrete Example

Now, let’s create concrete classes that implement the namespace attribute:

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Step 3: Implement the filter Function

Your filter function can now be implemented as follows:

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Step 4: Test the Function

You can test the function using objects of type Foo and Bar:

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By running a type checker like mypy, you’ll see that your function now returns a list of the expected types:

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Expected Output

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Conclusion

Combining generics and protocols allows us to ensure type safety without sacrificing the flexibility and usability of our functions. By binding our type variables to specific protocols, we can create type-safe filters that work seamlessly with various object types. This approach is a powerful tool in the Python programmer's toolkit, enhancing both code robustness and maintainability. Happy coding!