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Python Interfaces: Object-Oriented Design Principles
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Interfaces play an important role in software engineering. As an application grows, updates and changes to the code base become more difficult to manage. More often than not, you wind up having classes that look very similar but are unrelated, which can lead to some confusion. In this tutorial, you’ll see how you can use aPython interface to help determine what class you should use to tackle the current problem.
In this tutorial, you’ll be able to:
abc.ABCMeta
and@abc.abstractmethod
to implement a formal Python interfaceInterfaces in Python are handled differently than in most other languages, and they can vary in their design complexity. By the end of this tutorial, you’ll have a better understanding of some aspects of Python’s data model, as well as how interfaces in Python compare to those in languages like Java, C++, and Go.
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Implementing an Interface in PythonIn this quiz, you'll test your understanding of Python interfaces and their role in software engineering. You'll learn how interfaces can help manage complexity in a growing application and how to implement them in Python.
At a high level, an interface acts as ablueprint for designing classes. Like classes, interfaces define methods. Unlike classes, these methods are abstract. Anabstract method is one that the interface simply defines. It doesn’t implement the methods. This is done by classes, which thenimplement the interface and give concrete meaning to the interface’s abstract methods.
Python’s approach to interface design is somewhat different when compared to languages likeJava, Go, andC++. These languages all have aninterface
keyword, while Python does not. Python further deviates from other languages in one other aspect. It doesn’t require the class that’s implementing the interface to define all of the interface’s abstract methods.
In certain circumstances, you may not need the strict rules of a formal Python interface. Python’s dynamic nature allows you to implement aninformal interface. An informal Python interface is a class that defines methods that can be overridden, but there’s no strict enforcement.
In the following example, you’ll take the perspective of adata engineer who needs to extract text from various different unstructured file types, like PDFs and emails. You’ll create an informal interface that defines the methods that will be in both thePdfParser
andEmlParser
concrete classes:
classInformalParserInterface:defload_data_source(self,path:str,file_name:str)->str:"""Load in the file for extracting text."""passdefextract_text(self,full_file_name:str)->dict:"""Extract text from the currently loaded file."""pass
InformalParserInterface
defines the two methods.load_data_source()
and.extract_text()
. These methods are defined but not implemented. The implementation will occur once you createconcrete classes that inherit fromInformalParserInterface
.
As you can see,InformalParserInterface
looks identical to a standardPython class. You rely onduck typing to inform users that this is an interface and should be used accordingly.
Note: Haven’t heard ofduck typing? This term says that if you have an object that looks like a duck, walks like a duck, and quacks like a duck, then it must be a duck! To learn more, check outDuck Typing.
With duck typing in mind, you define two classes that implement theInformalParserInterface
. To use your interface, you must create a concrete class. Aconcrete class is a subclass of the interface that provides an implementation of the interface’s methods. You’ll create two concrete classes to implement your interface. The first isPdfParser
, which you’ll use to parse the text fromPDF files:
classPdfParser(InformalParserInterface):"""Extract text from a PDF"""defload_data_source(self,path:str,file_name:str)->str:"""Overrides InformalParserInterface.load_data_source()"""passdefextract_text(self,full_file_path:str)->dict:"""Overrides InformalParserInterface.extract_text()"""pass
The concrete implementation ofInformalParserInterface
now allows you to extract text fromPDF files.
Note: The concrete implementation consists of apass
statement, which does nothing. The implementation of the methods is not the point of this tutorial: Instead, you should focus on the structure of the classes.
The second concrete class isEmlParser
, which you’ll use to parse the text from emails:
classEmlParser(InformalParserInterface):"""Extract text from an email"""defload_data_source(self,path:str,file_name:str)->str:"""Overrides InformalParserInterface.load_data_source()"""passdefextract_text_from_email(self,full_file_path:str)->dict:"""A method defined only in EmlParser. Does not override InformalParserInterface.extract_text() """pass
The concrete implementation ofInformalParserInterface
now allows you to extract text from email files.
So far, you’ve defined twoconcrete implementations of theInformalPythonInterface
. However, note thatEmlParser
fails to properly define.extract_text()
, instead it defines a different.extract_text_from_email()
. If you were to check whetherEmlParser
implementsInformalParserInterface
, then you’d get the following result:
>>># Check if both PdfParser and EmlParser implement InformalParserInterface>>>issubclass(PdfParser,InformalParserInterface)True>>>issubclass(EmlParser,InformalParserInterface)True
This would returnTrue
, which poses a bit of a problem since it violates the definition of an interface!
Now check themethod resolution order (MRO) ofPdfParser
andEmlParser
. This tells you the superclasses of the class in question, as well as the order in which they’re searched for executing a method. You can view a class’s MRO by using the dunder methodcls.__mro__
:
>>>PdfParser.__mro__(__main__.PdfParser, __main__.InformalParserInterface, object)>>>EmlParser.__mro__(__main__.EmlParser, __main__.InformalParserInterface, object)
Such informal interfaces are fine for small projects where only a few developers are working on the source code. However, as projects get larger and teams grow, this could lead to developers spending countless hours looking for hard-to-find logic errors in the codebase!
Ideally, you would wantissubclass(EmlParser, InformalParserInterface)
to returnFalse
when the implementing class doesn’t define all of the interface’s abstract methods. To do this, you’ll create ametaclass calledParserMeta
. You’ll be overriding twodunder methods:
.__instancecheck__()
.__subclasscheck__()
In the code block below, you create a class calledUpdatedInformalParserInterface
that builds from theParserMeta
metaclass:
classParserMeta(type):"""A Parser metaclass that will be used for parser class creation. """def__instancecheck__(cls,instance):returncls.__subclasscheck__(type(instance))def__subclasscheck__(cls,subclass):return(hasattr(subclass,'load_data_source')andcallable(subclass.load_data_source)andhasattr(subclass,'extract_text')andcallable(subclass.extract_text))classUpdatedInformalParserInterface(metaclass=ParserMeta):"""This interface is used for concrete classes to inherit from. There is no need to define the ParserMeta methods as any class as they are implicitly made available via .__subclasscheck__(). """pass
Now thatParserMeta
andUpdatedInformalParserInterface
have been created, you can create your concrete implementations.
First, create a new class for parsing PDFs calledPdfParserNew
:
classPdfParserNew:"""Extract text from a PDF."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides UpdatedInformalParserInterface.load_data_source()"""passdefextract_text(self,full_file_path:str)->dict:"""Overrides UpdatedInformalParserInterface.extract_text()"""pass
Here,PdfParserNew
overrides.load_data_source()
and.extract_text()
, soissubclass(PdfParserNew, UpdatedInformalParserInterface)
should returnTrue
.
In this next code block, you have a new implementation of the email parser calledEmlParserNew
:
classEmlParserNew:"""Extract text from an email."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides UpdatedInformalParserInterface.load_data_source()"""passdefextract_text_from_email(self,full_file_path:str)->dict:"""A method defined only in EmlParser. Does not override UpdatedInformalParserInterface.extract_text() """pass
Here, you have a metaclass that’s used to createUpdatedInformalParserInterface
. By using a metaclass, you don’t need to explicitly define the subclasses. Instead, the subclass mustdefine the required methods. If it doesn’t, thenissubclass(EmlParserNew, UpdatedInformalParserInterface)
will returnFalse
.
Runningissubclass()
on your concrete classes will produce the following:
>>>issubclass(PdfParserNew,UpdatedInformalParserInterface)True>>>issubclass(EmlParserNew,UpdatedInformalParserInterface)False
As expected,EmlParserNew
is not a subclass ofUpdatedInformalParserInterface
since.extract_text()
wasn’t defined inEmlParserNew
.
Now, let’s have a look at the MRO:
>>>PdfParserNew.__mro__(<class '__main__.PdfParserNew'>, <class 'object'>)
As you can see,UpdatedInformalParserInterface
is a superclass ofPdfParserNew
, but it doesn’t appear in the MRO. This unusual behavior is caused by the fact thatUpdatedInformalParserInterface
is avirtual base class ofPdfParserNew
.
In the previous example,issubclass(PdfParserNew, UpdatedInformalParserInterface)
returnedTrue
, even thoughUpdatedInformalParserInterface
did not appear in thePdfParserNew
MRO. That’s becauseUpdatedInformalParserInterface
is avirtual base class ofPdfParserNew
.
The key difference between these and standard subclasses is that virtual base classes use the.__subclasscheck__()
dunder method to implicitly check if a class is a virtual subclass of the superclass. Additionally, virtual base classes don’t appear in the subclass MRO.
Take a look at this code block:
classPersonMeta(type):"""A person metaclass"""def__instancecheck__(cls,instance):returncls.__subclasscheck__(type(instance))def__subclasscheck__(cls,subclass):return(hasattr(subclass,'name')andcallable(subclass.name)andhasattr(subclass,'age')andcallable(subclass.age))classPersonSuper:"""A person superclass"""defname(self)->str:passdefage(self)->int:passclassPerson(metaclass=PersonMeta):"""Person interface built from PersonMeta metaclass."""pass
Here, you have the setup for creating your virtual base classes:
PersonMeta
PersonSuper
Person
Now that the setup for creatingvirtual base classes is done you’ll define two concrete classes,Employee
andFriend
. TheEmployee
class inherits fromPersonSuper
, whileFriend
implicitly inherits fromPerson
:
# Inheriting subclassesclassEmployee(PersonSuper):"""Inherits from PersonSuper PersonSuper will appear in Employee.__mro__ """passclassFriend:"""Built implicitly from Person Friend is a virtual subclass of Person since both required methods exist. Person not in Friend.__mro__ """defname(self):passdefage(self):pass
AlthoughFriend
does not explicitly inherit fromPerson
, it implements.name()
and.age()
, soPerson
becomes avirtual base class ofFriend
. When you runissubclass(Friend, Person)
it should returnTrue
, meaning thatFriend
is a subclass ofPerson
.
The followingUML diagram shows what happens when you callissubclass()
on theFriend
class:
Taking a look atPersonMeta
, you’ll notice that there’s another dunder method called.__instancecheck__()
. This method is used to check if instances ofFriend
are created from thePerson
interface. Your code will call.__instancecheck__()
when you useisinstance(Friend, Person)
.
Informal interfaces can be useful for projects with a small code base and a limited number of programmers. However, informal interfaces would be the wrong approach for larger applications. In order to create aformal Python interface, you’ll need a few more tools from Python’sabc
module.
abc.ABCMeta
To enforce the subclass instantiation of abstract methods, you’ll utilize Python’s builtinABCMeta
from theabc
module. Going back to yourUpdatedInformalParserInterface
interface, you created your own metaclass,ParserMeta
, with the overridden dunder methods.__instancecheck__()
and.__subclasscheck__()
.
Rather than create your own metaclass, you’ll useabc.ABCMeta
as the metaclass. Then, you’ll overwrite.__subclasshook__()
in place of.__instancecheck__()
and.__subclasscheck__()
, as it creates a more reliable implementation of these dunder methods.
.__subclasshook__()
Here’s the implementation ofFormalParserInterface
usingabc.ABCMeta
as your metaclass:
importabcclassFormalParserInterface(metaclass=abc.ABCMeta):@classmethoddef__subclasshook__(cls,subclass):return(hasattr(subclass,'load_data_source')andcallable(subclass.load_data_source)andhasattr(subclass,'extract_text')andcallable(subclass.extract_text))classPdfParserNew:"""Extract text from a PDF."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides FormalParserInterface.load_data_source()"""passdefextract_text(self,full_file_path:str)->dict:"""Overrides FormalParserInterface.extract_text()"""passclassEmlParserNew:"""Extract text from an email."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides FormalParserInterface.load_data_source()"""passdefextract_text_from_email(self,full_file_path:str)->dict:"""A method defined only in EmlParser. Does not override FormalParserInterface.extract_text() """pass
If you runissubclass()
onPdfParserNew
andEmlParserNew
, thenissubclass()
will returnTrue
andFalse
, respectively.
abc
to Register a Virtual SubclassOnce you’ve imported theabc
module, you can directlyregister a virtual subclass by using the.register()
metamethod. In the next example, you register the interfaceDouble
as a virtual base class of the built-in__float__
class:
classDouble(metaclass=abc.ABCMeta):"""Double precision floating point number."""passDouble.register(float)
You can check out the effect of using.register()
:
>>>issubclass(float,Double)True>>>isinstance(1.2345,Double)True
By using the.register()
meta method, you’ve successfully registeredDouble
as a virtual subclass offloat
.
Once you’ve registeredDouble
, you can use it as classdecorator to set the decorated class as a virtual subclass:
@Double.registerclassDouble64:"""A 64-bit double-precision floating-point number."""passprint(issubclass(Double64,Double))# True
The decorator register method helps you to create a hierarchy of custom virtual class inheritance.
You must be careful when you’re combining.__subclasshook__()
with.register()
, as.__subclasshook__()
takes precedence over virtual subclass registration. To ensure that the registered virtual subclasses are taken into consideration, you must addNotImplemented
to the.__subclasshook__()
dunder method. TheFormalParserInterface
would be updated to the following:
classFormalParserInterface(metaclass=abc.ABCMeta):@classmethoddef__subclasshook__(cls,subclass):return(hasattr(subclass,'load_data_source')andcallable(subclass.load_data_source)andhasattr(subclass,'extract_text')andcallable(subclass.extract_text)orNotImplemented)classPdfParserNew:"""Extract text from a PDF."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides FormalParserInterface.load_data_source()"""passdefextract_text(self,full_file_path:str)->dict:"""Overrides FormalParserInterface.extract_text()"""pass@FormalParserInterface.registerclassEmlParserNew:"""Extract text from an email."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides FormalParserInterface.load_data_source()"""passdefextract_text_from_email(self,full_file_path:str)->dict:"""A method defined only in EmlParser. Does not override FormalParserInterface.extract_text() """passprint(issubclass(PdfParserNew,FormalParserInterface))# Trueprint(issubclass(EmlParserNew,FormalParserInterface))# True
Since you’ve used registration, you can see thatEmlParserNew
is considered a virtual subclass of yourFormalParserInterface
interface. This is not what you wanted sinceEmlParserNew
doesn’t override.extract_text()
.Please use caution with virtual subclass registration!
Anabstract method is a method that’s declared by the Python interface, but it may not have a useful implementation. The abstract method must be overridden by the concrete class that implements the interface in question.
To create abstract methods in Python, you add the@abc.abstractmethod
decorator to the interface’s methods. In the next example, you update theFormalParserInterface
to include the abstract methods.load_data_source()
and.extract_text()
:
classFormalParserInterface(metaclass=abc.ABCMeta):@classmethoddef__subclasshook__(cls,subclass):return(hasattr(subclass,'load_data_source')andcallable(subclass.load_data_source)andhasattr(subclass,'extract_text')andcallable(subclass.extract_text)orNotImplemented)@abc.abstractmethoddefload_data_source(self,path:str,file_name:str):"""Load in the data set"""raiseNotImplementedError@abc.abstractmethoddefextract_text(self,full_file_path:str):"""Extract text from the data set"""raiseNotImplementedErrorclassPdfParserNew(FormalParserInterface):"""Extract text from a PDF."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides FormalParserInterface.load_data_source()"""passdefextract_text(self,full_file_path:str)->dict:"""Overrides FormalParserInterface.extract_text()"""passclassEmlParserNew(FormalParserInterface):"""Extract text from an email."""defload_data_source(self,path:str,file_name:str)->str:"""Overrides FormalParserInterface.load_data_source()"""passdefextract_text_from_email(self,full_file_path:str)->dict:"""A method defined only in EmlParser. Does not override FormalParserInterface.extract_text() """pass
In the above example, you’ve finally created a formal interface that will raise errors when the abstract methods aren’t overridden. ThePdfParserNew
instance,pdf_parser
, won’t raise any errors, asPdfParserNew
is correctly overriding theFormalParserInterface
abstract methods. However,EmlParserNew
will raise an error:
>>>pdf_parser=PdfParserNew()>>>eml_parser=EmlParserNew()Traceback (most recent call last):...TypeError:Can't instantiate abstract class EmlParserNew with abstract methods extract_text
As you can see, thetraceback message tells you that you haven’t overridden all the abstract methods. This is the behavior you expect when building a formal Python interface.
Interfaces appear in many programming languages, and their implementation varies greatly from language to language. In the next few sections, you’ll compare interfaces in Python to Java, C++, and Go.
Unlike Python,Java contains aninterface
keyword. Keeping with the file parser example, you declare an interface in Java like so:
publicinterfaceFileParserInterface{// Static fields, and abstract methods go here ...publicvoidloadDataSource();publicvoidextractText();}
Now you’ll create two concrete classes,PdfParser
andEmlParser
, to implement theFileParserInterface
. To do so, you must use theimplements
keyword in the class definition, like so:
publicclassEmlParserimplementsFileParserInterface{publicvoidloadDataSource(){// Code to load the data set}publicvoidextractText(){// Code to extract the text}}
Continuing with your file parsing example, a fully-functional Java interface would look something like this:
importjava.util.*;importjava.io.*;publicclassFileParser{publicstaticvoidmain(String[]args)throwsIOException{// The main entry point}publicinterfaceFileParserInterface{HashMap<String,ArrayList<String>>file_contents=null;publicvoidloadDataSource();publicvoidextractText();}publicclassPdfParserimplementsFileParserInterface{publicvoidloadDataSource(){// Code to load the data set}publicvoidextractText(){// Code to extract the text}}publicclassEmlParserimplementsFileParserInterface{publicvoidloadDataSource(){// Code to load the data set}publicvoidextractText(){// Code to extract the text}}}
As you can see, a Python interface gives you much more flexibility during creation than a Java interface does.
Like Python, C++ uses abstract base classes to create interfaces. When defining an interface in C++, you use the keywordvirtual
to describe a method that should be overwritten in the concrete class:
classFileParserInterface{public:virtualvoidloadDataSource(std::stringpath,std::stringfile_name);virtualvoidextractText(std::stringfull_file_name);};
When you want to implement the interface, you’ll give the concrete class name, followed by a colon (:
), and then the name of the interface. The following example demonstrates C++ interface implementation:
classPdfParser:FileParserInterface{public:voidloadDataSource(std::stringpath,std::stringfile_name);voidextractText(std::stringfull_file_name);};classEmlParser:FileParserInterface{public:voidloadDataSource(std::stringpath,std::stringfile_name);voidextractText(std::stringfull_file_name);};
A Python interface and a C++ interface have some similarities in that they both make use of abstract base classes to simulate interfaces.
Although Go’s syntax is reminiscent of Python, the Go programming language contains aninterface
keyword, like Java. Let’s create thefileParserInterface
in Go:
typefileParserInterfaceinterface{loadDataSet(pathstring,filenamestring)extractText(full_file_pathstring)}
A big difference between Python and Go is that Go doesn’t have classes. Rather, Go is similar toC in that it uses thestruct
keyword to create structures. Astructure is similar to a class in that a structure contains data and methods. However, unlike a class, all of the data and methods are publicly accessed. The concrete structs in Go will be used to implement thefileParserInterface
.
Here’s an example of how Go uses interfaces:
packagemaintypefileParserInterfaceinterface{loadDataSet(pathstring,filenamestring)extractText(full_file_pathstring)}typepdfParserstruct{// Data goes here ...}typeemlParserstruct{// Data goes here ...}func(ppdfParser)loadDataSet(){// Method definition ...}func(ppdfParser)extractText(){// Method definition ...}func(eemlParser)loadDataSet(){// Method definition ...}func(eemlParser)extractText(){// Method definition ...}funcmain(){// Main entrypoint}
Unlike a Python interface, a Go interface is created using structs and the explicit keywordinterface
.
Python offers great flexibility when you’re creating interfaces. An informal Python interface is useful for small projects where you’re less likely to get confused as to what the return types of the methods are. As a project grows, the need for aformal Python interface becomes more important as it becomes more difficult to infer return types. This ensures that the concrete class, which implements the interface, overwrites the abstract methods.
Now you can:
Now that you’ve become familiar with how to create a Python interface, add a Python interface to your next project to see its usefulness in action!
Take the Quiz: Test your knowledge with our interactive “Implementing an Interface in Python” quiz. You’ll receive a score upon completion to help you track your learning progress:
Interactive Quiz
Implementing an Interface in PythonIn this quiz, you'll test your understanding of Python interfaces and their role in software engineering. You'll learn how interfaces can help manage complexity in a growing application and how to implement them in Python.
Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding:Python Interfaces: Object-Oriented Design Principles
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AboutWilliam Murphy
William has been working with Python for over 6 years, working in roles such as data scientist, machine learning engineer, data engineer, and dev ops engineer. He is currently a senior software engineering consultant at ModernDay Productions.
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