Static types are a powerful concept in programming. They provide a layer of safety whenever the programmer calls into outside functions or objects.

Consider the following code snippet

class User : def __init__ ( self , name : str , email : str ) : self . name = name self . email = email jack = User ( name = "jack" , email = [email protected]" ) jimbo = User ( name = "jimbo" , email = 123 )

Python has a loose type system - this code will happily run despite the obvious error with jimbo 's email. However, we can still get some mileage from using Python 3's type annotation. In this case it's easy to tell that there's an issue with jimbo 's email. Good IDEs like PyCharm will probably add a couple red lines to alert you to the issue.

This isn't quite complete though. Not every valid str is also a valid email address. At the very least, an email address should contain an '@' character.

In practice, most programmers will get around this by using Python properties and getters + setters:

class User : def __init__ ( self , name : str , email : str ) : self . name = name self . email = email @ property def email ( self ) : return self . _email @email . setter def email ( self , value ) : if '@' not in value : raise ValueError ( "Bad email!" ) self . _email = value

Much better! The following code will rightfully raise an exception:

In [ 1 ] : User ( name = "Jimbo" , email = "test" ) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Exception Traceback ( most recent call last ) < ipython - input - 5 - 525947c92af3 > in < module > ( ) - - - - > 1 User ( name = "Jimbo" , email = "test" ) < ipython - input - 4 - 271bcdf13daf > in __init__ ( self , name , email ) 2 def __init__ ( self , name , email ) : 3 self . name = name - - - - > 4 self . email = email 5 @ property 6 def email ( self ) : < ipython - input - 4 - 271bcdf13daf > in email ( self , value ) 9 def email ( self , value ) : 10 if '@' not in value : - - - > 11 raise ValueError ( "Bad email!" ) 12 self . _email = value 13 Exception : Bad email!

Unfortunately, we're not out of the woods yet. We might want to write a function that uses an email address - say to send emails. That function will also have to validate that the email address is correct.

def send_email ( address : str ) : if '@' not in address : raise Exception ( "Bad email again!" ) . . .

Any time we want to use or set an email address, we're going to have to remember to validate the email address. There's also a subtle issue that it's not immediately obvious what the type of address should be - we already know str isn't specific enough.

That's where the idea of smart constructors come in.

class EmailAddress ( str ) : def __new__ ( cls , address : str ) : if '@' not in address : raise ValueError ( "Bad email!" ) return super ( ) . __new__ ( cls , address )

This defines an EmailAddress class whose constructor will fail if the provided value fails validation.

The idea behind smart constructors is to enforce the notion that illegal states are unrepresentable (to quote Yaron Minsky). There's no need to check for bad email addresses, if you can't construct a bad email address!

In [ 25 ] : valid = EmailAddress ( [email protected]" ) In [ 26 ] : invalid = EmailAddress ( "bad" ) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ValueError Traceback ( most recent call last ) < ipython - input - 26 - ba21088ca252 > in < module > ( ) - - - - > 1 invalid = EmailAddress ( "bad" ) < ipython - input - 22 - 2c9b4a6c24a1 > in __new__ ( cls , address ) 2 def __new__ ( cls , address ) : 3 if '@' not in address : - - - - > 4 raise ValueError ( "Bad email!" ) 5 return super ( ) . __new__ ( cls , address ) 6 ValueError : Bad email!

Since EmailAddress is immutable, being a subclass of the immutable str type, you know that if you have an instance of EmailAddress , its value is very likely to be compliant (barring some Python type magic). Being a subclass of str also means that any instance of EmailAddress will behave like a string:

In [ 23 ] : valid = EmailAddress ( [email protected]" ) In [ 24 ] : valid . startswith ( "t" ) Out [ 24 ] : True

By representing email addresses with its own class, we can thus remove the validation checks from the previous examples:

class User : def __init__ ( self , name : str , email : EmailAddress ) : assert isinstance ( email , EmailAddress ) self . name = name self . email = email def send_email ( address : EmailAddress ) : assert isinstance ( address , EmailAddress ) . . .

The important thing to note is that for smart constructors to be robust, they need to be immutable, otherwise you have less of a guarantee that the validations hold true. Thus they work best when subclassing an immutable value type, like str , tuple or NamedTuple (from Python 3.6+)

In summary, smart constructors are an incredibly valuable pattern to use, and is useful in just about any language, even those with an already strong type system (smart constructors are a Haskell term, after all).