The blog post "Frankenstein's __init__" explores the complexities and potential pitfalls of Python's __init__ method, particularly when dealing with inheritance. It argues against placing complex logic or side effects within __init__, as this can lead to unpredictable behavior and violate the principle of least astonishment, especially in scenarios involving inheritance and multiple inheritance. The author advocates for using factory functions or a separate post_init method for such logic, leading to more transparent, testable, and maintainable code. This approach decouples object creation from initialization logic, allowing for greater flexibility and avoiding unexpected interactions between parent and child class initializers.
The blog post "Frankenstein's __init__" delves into the intricacies and potential pitfalls of object initialization in Python, focusing specifically on the __init__ method. The author begins by establishing the common understanding of __init__ as a constructor, responsible for creating and initializing new objects. However, the post quickly challenges this simplistic view, highlighting the subtle yet crucial distinction between object creation and initialization.
In Python, object creation actually occurs before __init__ is called. The __new__ method is the true constructor, responsible for allocating memory and returning a new, barebones instance of the class. The __init__ method is then invoked on this newly created instance, allowing for the initialization of its attributes. This separation of creation and initialization is often overlooked, leading to potential confusion and errors, especially when dealing with inheritance and metaclasses.
The author uses the analogy of Frankenstein's monster to illustrate this point. Just as Dr. Frankenstein first assembled the creature's body (__new__) and then imbued it with life (__init__), Python first creates an empty object and then populates it with attributes within __init__.
The post proceeds to explore the implications of this two-stage process, particularly in the context of inheritance. When a subclass overrides the __init__ method, it's crucial to ensure that the superclass's __init__ is also called. Failing to do so can lead to unexpected behavior and incomplete initialization. The author provides detailed examples demonstrating the correct way to call the superclass's __init__ using super(), emphasizing the importance of passing along all necessary arguments.
Furthermore, the post touches upon the scenario where a subclass's __new__ method returns an instance of a different class. In this somewhat advanced case, the __init__ method of the returned instance's class will be called, potentially leading to surprising results if not carefully considered.
Finally, the author briefly discusses the role of metaclasses in object creation and initialization, noting that they further complicate the picture but ultimately provide powerful tools for customizing object behavior. The post concludes by reinforcing the importance of understanding the nuanced relationship between __new__ and __init__ for writing robust and predictable Python code. It emphasizes the need to recognize __init__'s role not as the object creator, but rather the object initializer, thereby promoting a more accurate mental model of the object creation process.
Summary of Comments ( 24 )
https://news.ycombinator.com/item?id=43735724
HN users largely discuss the impracticality and contrived nature of the example in the article, which explores creating an object through a Frankensteinian assembly of
__init__components. Several commenters find the exploration interesting but ultimately useless, highlighting how it obfuscates code and introduces unnecessary complexity. The prevailing sentiment is that while conceptually intriguing, such a method is counterproductive to writing clear, maintainable code and would likely never be used in a real-world scenario. Some find the exploration of metaprogramming and the inner workings of Python mildly interesting, but the overall consensus leans towards viewing the article's content as a clever but impractical exercise.The Hacker News post titled "Frankenstein's
__init__" sparked a discussion with several insightful comments revolving around the complexities and potential pitfalls of inheritance in object-oriented programming, specifically in Python. The conversation largely agrees with the author's premise about the awkwardness of large, complex__init__methods often necessitated by inheritance.Several commenters highlight the tension between adhering to Liskov's Substitution Principle and the practical challenges of designing class hierarchies. One commenter points out the difficulties encountered when subclasses require different initialization parameters than their parent class, leading to unwieldy
**kwargsusage and obscure error handling. This resonates with the article's concerns about the "Frankenstein" nature of such constructors. They further argue that forcing conformance to a rigid structure through inheritance can be detrimental to code clarity and maintainability, suggesting composition as a more flexible alternative.Another commenter emphasizes the importance of careful consideration when designing class hierarchies and choosing between inheritance and composition. They propose that simpler designs are often preferable and that the need for complex inheritance structures might indicate a flaw in the overall design. They also caution against overusing inheritance solely for code reuse, reiterating the benefits of composition in such scenarios.
The idea of "role interfaces" is brought up as a potential solution to the inheritance dilemma. This approach involves defining smaller, more focused interfaces that classes can implement, allowing for greater flexibility and composability. This is presented as a way to avoid the rigid constraints of traditional inheritance while still maintaining a degree of structure and ensuring substitutability.
One commenter, focusing on the specific example in the original article, questions whether abstract base classes would be a suitable solution to address the initialization challenges. This sparks a brief discussion about the nuances of abstract methods and their role in enforcing certain behaviors within a class hierarchy.
Finally, a recurring theme in the comments is the preference for simplicity and avoiding over-engineering. Several commenters express the view that complex inheritance hierarchies often add unnecessary complexity and advocate for keeping designs as simple as possible. This aligns with the overall sentiment that Frankensteinian
__init__methods are a symptom of a deeper design issue.