Return check_password_hash(self.Sure, there are some projects out there that can help out.
Self.password_hash = generate_password_hash(password) Raise AttributeError('password is not a readable password(self, password): Username = db.Column(db.String(64), unique=True, index=True) Id = db.Column(db.Integer, primary_key=True)Įmail = db.Column(db.String(64), unique=True, index=True) You declare a model User in models.py: class User(UserMixin, db.Model): Why, actually, we have consider a Flask app where you use authentication system. I read all the posts here and realized that we may need a real life example.
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This is great, isn't it: You can start with the simplest implementation imaginable, and you are free to later migrate to a property version without having to change the interface! So properties are not just a replacement for getters and setters! Return (self.get_temperature() * 1.8) + 32 Let us assume that you decide to make a class that could store the temperature in degrees Celsius. Python has a great concept called property which makes the life of an object-oriented programmer much simpler. Yup, is basically a pythonic way to use getters and setters. These methods are, of course, the getter for retrieving the data and the setter for changing the data.Īccording to this principle, the attributes of a class are made private to hide and protect them from other code. Getters and setters are used in many object-oriented programming languages to ensure the principle of data encapsulation(which is seen as the bundling of data with the methods that operate on these data.) But before that, let's talk about some OOP principles. Let's go through everything with a case scenario. Python syntax for decorator def decorator_func(fun): Here, we can say that the decorator function modified our say_bye function and added some extra lines of code to it. # Wrapper function add something to the passed function and decorator Functions in Python are first-class objects which means that they can be referenced by a variable, added in the lists, passed as arguments to another function, etc.Ĭonsider the following code snippet. X = property(_x_get, doc="I'm the 'x' property.")Ī Python decorator is a function that helps to add some additional functionalities to an already defined function.
You can use also in abstract classes I give a minimal example here. > def setter(self, value): print('Set to cents.".format(money.dollars, money.cents)) The following sequence also creates a full-on property, by using those decorator methods.įirst we create some functions and a property object with just a getter: > def getter(self): print('Get!') Then when you use what you are doing is call that property().setter method I showed you above, which returns a new copy of the property, but this time with the setter function replaced with the decorated method. So foo the function is replaced by property(foo), which we saw above is a special object. Really means the same thing as def foo(self): return self._foo Remember, that the syntax is just syntactic sugar the syntax: foo(self): return self._foo That is a copy of the old object, but with one of the functions replaced. They return a new property object: > property().getter(None) It is this object that has extra methods: > property().getter The property() function returns a special descriptor object: > property()
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