I've seen many Python interfaces in my career ( ). You can quickly spot an ugly one by its size. Below are some recipes on how to make a neat one! as in API, not UI Interfaces in Python An "interface" is a nebulous concept that might be initially hard to grasp. It is a blueprint of interactions with an object (reading a few answers is not going to hurt). here Do you need interfaces in Python at all? There are several good posts about it: Chelsea Troy Stack Overflow (please read several answers!) Diego Barba I’m going to assume that you read all that and decided to go with interfaces.
I think are the best way to create interfaces in Python. This is what we are going to use here. Protocols Here, we are going to discuss what makes a interface. good An interface has to be small You’re designing a Zoo simulator and made an interface for "a generic animal": class Animal(Protocol):
   def current_weight(self) -> float: ...
   def price(self) -> float: ...
   def sleep(self, hours): ...
   def eat(self, food): ...
   def draw(self, context): ...
   def look_for_food(self): ...
   def hunger_level(self) -> float: ...
   def is_asleep(self) -> bool: ...
   def is_awake(self) -> bool: ...
   def current_position() -> Tuple[float, float, float]: ...
   def current_orientation() -> RotationMatrix: ...
   def current_transform3d() -> HomogeneousMatrix: ... You should be alarmed when you see an interface with more than 4-5 methods. Chances are that it was not well-designed, and the project it is used in will be overly convoluted: this interface will be used in completely unrelated parts of the software. It will couple them together there will be extensive use of class hierarchies interface implementations are going to be overly complicated it will be hard to document and confusing to use. You might think: “Clearly, animals do tons of different things, so it's justified to have many methods.” But you can come up with ten more methods to add to a “generic animal,” and there is never going to be an end to it. The art is to model a complicated thing with a set of small decoupled interfaces. What are the recipes for reducing an interface's size? Semantic overlap Sometimes there could be some obvious duplication methods (e.g., vs. ). But more often you'll find methods that somewhat overlap in semantics. After a bit of thought, it's possible to remove some of them. get_weights current_weight In the example above: def current_position() -> Tuple[float, float, float]:
       pass
 
   def current_orientation() -> RotationMatrix:
       pass
  
   def current_transform3d() -> HomogeneousMatrix:
       pass The user extract position and orientation from the returned by . The other two getters could be replaced by . HomogeneousMatrix current_transform3d utility functions A similar situation is probably happening with: def is_asleep(self) -> bool:
       pass
 
   def is_awake(self) -> bool:
       pass Is it true that ? If yes, then you better remove one of them. animal.is_asleep() == not animal.is_awake() Decoupling interfaces After removing duplicates, you should try to split the interface into independent parts.
Most likely, you don’t use features in every part of your software: all Animal there could be a function that handles the drawing of animals that uses only and : 1. current_transform3d draw def draw_entity(animal: Animal):
    t = animal.current_transform3d()
    c = some_drawing_context(t)
    animal.draw(c) there could be an animal life cycle algorithm: 2. def life_management(animal: Animal):
    eating_logic(
      animal.hunger_level(), animal.look_for_food(), 
      animal.eat())
    sleeping_logic(animal.is_awake(), animal.sleep()) and a Zoo management system 3. def purchase_decision(animal: Animal, budget: float) -> bool:
   w = animal.current_weight()
   p = animal.price()
   decide_to_buy(p, w, budget) The “generic animal” is a collection of quite different interfaces that could be disentangled: class VisualEntity(Protocol):
   def current_transform3d() -> HomogeneousMatrix: ...
   def draw(self, context): ...
 
class BehavingAgent:
   def sleep(self, hours): ...
   def eat(self, food): ...
   def look_for_food(self): ...
   def hunger_level(self) -> float: ...
   def is_awake(self) -> bool: ...

class ZooAsset:
   def current_weight(self) -> float: ...
   def price(self) -> float: ... Now you can see the advantages of many small interfaces over a single big one: You don’t need to decouple parts of your codebase and company workflows. A rendering team will not depend on Zoo management developers. No need to implement unnecessary methods for slight variations of “Animals.” Changing a price algorithm does not lead to a new species! You would be able to reuse small interfaces and utilities. You might find that the draw_entity and purchase_decision work for your Plant object. Now you can see the advantages of many small interfaces over a single big one. They decouple parts of your codebase (while the large ones have a high chance of coupling unrelated parts). This in turn decouples company workflows (e.g. teams don't break each other's stuff too much) You don't have to write many implementations when instantiating a short interface. This ripples through your design because now you more easily avoid base classes and class hierarchies. Which in turn promotes composition over inheritance (there are many resources on why it's a good idea, e.g. see here You would be able to reuse small interfaces in more places than large ones. This in turn makes the total surface area of APIs in your codebase smaller, easier to learn with simpler onboarding Recursive semantics Next, you should be alarmed if one function calls another in the same interface.
Continuing with the Zoo example: class BehavingAnimal(Protocol):
   def lifecycle(self):
       """ What happens during 24 hours period """
 
   def eat(self, food):
       """ What happens when the animal consumes food """
 
   def sleep(self, hours):
       """ What happens when the animal sleeps """ It is unlikely that an animal will spend a day without eating and sleeping. So there is a high chance that and will be called from the implementation. Such an interface couples together two levels of abstraction. These are two interfaces in one, similar to the previous section. eat sleep lifecycle A "lifecycle" part is used in some global application contexts, but and are probably used only locally inside it. eat sleep Let's split them apart: class ElementaryAnimal(Protocol):
   def eat(self, food): ...
   def sleep(self, hours): ...
 
class LifecycleManagement(Protocol):
   def lifecycle(self, animal: ElementaryAnimal): ... Notice that now takes as an argument.
This clearly states that a lifecycle depends on something that can eat and sleep. lifecycle ElementaryAnimal Too generic Yet another thing to avoid is an overly-generic interface: class Creature(Protocol):
   def act(self, *args, **kwargs) -> object:
       """ Do anything you want """

 def perform_action(creature: Creature):
     custom_args = ...
     creature.act(*custom_args) An interface is like a contract between two parties. But a contract that says “do whatever” is as good as no contract at all. It is too easy to make such interfaces in an optional/dynamic-typed language like Python, especially with its wildcard argument features. Unfortunately, such interfaces come up in some situations, but we can summarize it as “passing a black box around.” Passing “blackboxes” is typically worse than explicit components.
But if you have to do it, it’s better to acknowledge its "blackness" by passing
a functor and moving to a more functional design (here is an ): in-depth tutorial def perform_action(actor: Callable[..., Any]):
    custom_args = ...
    actor(*custom_args) Constructors in an interface Related bonus topic: have you noticed that is typically a part of any interface?
Why not? It seems like it is just another method you can have. __init__ not It goes back to C++, where constructors are not virtual. Bjarne Stroustrup on why it is so: gives an answer “A virtual call is a mechanism to get work done given partial information.
To create an object, you need complete information. Consequently, a "call to a constructor" cannot be virtual.” I like high-level reasoning more: a constructor is a function for making objects. It belongs to the “object-makers” realm. It just can’t belong to an already-made object: you shouldn't make an object out of itself and I'm not a fan of ). cloning A constructor could be viewed as a method of interface. In other words, a constructor and an object interface are yet another example of two coupled levels of abstraction. a factory Conclusion To summarize, a interface should: good be small and concise avoid semantic duplication avoid coupling several parts in one avoid mixing multiple abstraction levels be specific and not too generic not include __init__ At the same time, real life has many exceptions and complications. But those must be justified exceptions, not excuses to keep messy interfaces around. Thank you for reading! You can find me on or . Twitter LinkedIn Originally published at . here

Tread the Perils of Python's 'Side Effects' at Your Own Risk

Streamlining Python Interfaces: Tips for Concise and Clean Code

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

Negating 'Side Effects' in Python: A Guide (With Pictures!)

100 Days of AI Day 1: From Newsletter to Podcast, Leveraging AI for Audio Transformation

10 Threats to an Open API Ecosystem

10 Indications That You Should Invest in Automation Via APIs

10 Best Practices for Securing Your API

The Noonification: Getting Your API Into Production (10/28/2022)

Negating 'Side Effects' in Python: A Guide (With Pictures!)

100 Days of AI Day 1: From Newsletter to Podcast, Leveraging AI for Audio Transformation

10 Threats to an Open API Ecosystem

10 Indications That You Should Invest in Automation Via APIs

10 Best Practices for Securing Your API

The Noonification: Getting Your API Into Production (10/28/2022)

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps