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(For more resources on Python 3, see here.)

Creating Python classes

We don’t have to write much Python code to realize that Python is a very “clean” language. When we want to do something, we just do it, without having to go through a lot of setup. The ubiquitous, “hello world” in Python, as you’ve likely seen, is only one line.

Similarly, the simplest class in Python 3 looks like this:

class MyFirstClass:

There’s our first object-oriented program! The class definition starts with the class keyword. This is followed by a name (of our choice) identifying the class, and is terminated with a colon.

The class name must follow standard Python variable naming rules (must start with a letter or underscore, can only be comprised of letters, underscores, or numbers). In addition, the Python style guide (search the web for “PEP 8”), recommends that classes should be named using CamelCase notation (start with a capital letter, any subsequent words should also start with a capital).


The class definition line is followed by the class contents, indented. As with other Python constructs, indentation is used to delimit the classes, rather than braces or brackets as many other languages use. Use four spaces for indentation unless you have a compelling reason not to (such as fitting in with somebody else’s code that uses tabs for indents). Any decent programming editor can be configured to insert four spaces whenever the Tab key is pressed.

Since our first class doesn’t actually do anything, we simply use the pass keyword on the second line to indicate that no further action needs to be taken.

We might think there isn’t much we can do with this most basic class, but it does allow us to instantiate objects of that class. We can load the class into the Python 3 interpreter so we can play with it interactively. To do this, save the class definition mentioned earlier into a file named first_class.py and then run the command python -i first_class.py. The -i argument tells Python to “run the code and then drop to the interactive interpreter”. The following interpreter session demonstrates basic interaction with this class:

>>> a = MyFirstClass()

>>> b = MyFirstClass()

>>> print(a)

<__main__.myfirstclass object at>

>>> print(b)

<__main__.myfirstclass object at>


This code instantiates two objects from the new class, named a and b. Creating an instance of a class is a simple matter of typing the class name followed by a pair of parentheses. It looks much like a normal function call, but Python knows we’re “calling” a class and not a function, so it understands that its job is to create a new object. When printed, the two objects tell us what class they are and what memory address they live at. Memory addresses aren’t used much in Python code, but here,it demonstrates that there are two distinctly different objects involved.

Adding attributes

Now, we have a basic class, but it’s fairly useless. It doesn’t contain any data, and it doesn’t do anything. What do we have to do to assign an attribute to a given object?

It turns out that we don’t have to do anything special in the class definition. We can set arbitrary attributes on an instantiated object using the dot notation:

class Point:

p1 = Point()
p2 = Point()

p1.x = 5
p1.y = 4

p2.x = 3
p2.y = 6

print(p1.x, p1.y)
print(p2.x, p2.y)

If we run this code, the two print statements at the end tell us the new attribute values on the two objects:

5 4
3 6

This code creates an empty Point class with no data or behaviors. Then it creates two instances of that class and assigns each of those instances x and y coordinates to identify a point in two dimensions. All we need to do to assign a value to an attribute on an object is use the syntax .=. This is sometimes referred to as dot notation. The value can be anything: a Python primitive, a built-in data type, another object. It can even be a function or another class!

Making it do something

Now, having objects with attributes is great, but object-oriented programming is really about the interaction between objects. We’re interested in invoking actions that cause things to happen to those attributes. It is time to add behaviors to our classes.

Let’s model a couple of actions on our Point class. We can start with a method called reset that moves the point to the origin (the origin is the point where x and y are both zero). This is a good introductory action because it doesn’t require any parameters:

class Point:
def reset(self):
self.x = 0
self.y = 0

p = Point()
print(p.x, p.y)

That print statement shows us the two zeros on the attributes:

0 0

A method in Python is identical to defining a function. It starts with the keyword def followed by a space and the name of the method. This is followed by a set of parentheses containing the parameter list (we’ll discuss the self parameter in just a moment), and terminated with a colon. The next line is indented to contain the statements inside the method. These statements can be arbitrary Python code operating on the object itself and any parameters passed in as the method sees fit.

The one difference between methods and normal functions is that all methods have one required argument. This argument is conventionally named self; I’ve never seen a programmer use any other name for this variable (convention is a very powerful thing). There’s nothing stopping you, however, from calling it this or even Martha.

The self argument to a method is simply a reference to the object that the method is being invoked on. We can access attributes and methods of that object as if it were any other object. This is exactly what we do inside the reset method when we set the x and y attributes of the self object.

Notice that when we call the p.reset() method, we do not have to pass the self argument into it. Python automatically takes care of this for us. It knows we’re calling a method on the p object, so it automatically passes that object to the method.

However, the method really is just a function that happens to be on a class. Instead of calling the method on the object, we could invoke the function on the class, explicitly passing our object as the self argument:

p = Point()
print(p.x, p.y)

The output is the same as the previous example because, internally, the exact same process has occurred.

What happens if we forget to include the self argument in our class definition? Python will bail with an error message:

>>> class Point:
… def reset():
… pass

>>> p = Point()
>>> p.reset()
Traceback (most recent call last):
File “”, line 1, in
TypeError: reset() takes no arguments (1 given)

The error message is not as clear as it could be (“You silly fool, you forgot the self argument” would be more informative). Just remember that when you see an error message that indicates missing arguments, the first thing to check is whether you forgot self in the method definition.

So how do we pass multiple arguments to a method? Let’s add a new method that allows us to move a point to an arbitrary position, not just the origin. We can also include one that accepts another Point object as input and returns the distance between them:

import math

class Point:
def move(self, x, y):
self.x = x
self.y = y

def reset(self):
self.move(0, 0)

def calculate_distance(self, other_point):
return math.sqrt((self.x – other_point.x)**2 +(self.y – other_point.y)


# how to use it:
point1 = Point()
point2 = Point()

assert (point2.calculate_distance(point1) ==

The print statements at the end give us the following output:


A lot has happened here. The class now has three methods. The move method accepts two arguments, x and y, and sets the values on the self object, much like the old reset method from the previous example. The old reset method now calls move, since a reset is just a move to a specific known location.

The calculate_distance method uses the not-too-complex Pythagorean Theorem to calculate the distance between two points. I hope you understand the math (** means squared, and math.sqrt calculates a square root), but it’s not a requirement for our current focus: learning how to write methods.

The example code at the end shows how to call a method with arguments; simply include the arguments inside the parentheses, and use the same dot notation to access the method. I just picked some random positions to test the methods. The test code calls each method and prints the results on the console. The assert function is a simple test tool; the program will bail if the statement after assert is False (or zero, empty, or None). In this case, we use it to ensure that the distance is the same regardless of which point called the other point’s calculate_distance method.

Initializing the object

If we don’t explicitly set the x and y positions on our Point object, either using move or by accessing them directly, we have a broken point with no real position. What will happen when we try to access it?

Well, let’s just try it and see. “Try it and see” is an extremely useful tool for Python study. Open up your interactive interpreter and type away. The following interactive session shows what happens if we try to access a missing attribute. If you saved the previous example as a file or are using the examples distributed in this article, you can load it into the Python interpreter with the command python -i filename.py.

>>> point = Point()
>>> point.x = 5
>>> print(point.x)
>>> print(point.y)
Traceback (most recent call last):
File “”, line 1, in
AttributeError: ‘Point’ object has no attribute ‘y’

Well, at least it threw a useful exception. You’ve probably seen them before (especially the ubiquitous SyntaxError, which means you typed something incorrectly!). At this point, simply be aware that it means something went wrong.

The output is useful for debugging. In the interactive interpreter it tells us the error occurred at line 1, which is only partially true (in an interactive session, only one line is executed at a time). If we were running a script in a file, it would tell us the exact line number, making it easy to find the offending code. In addition, it tells us the error is an AttributeError, and gives a helpful message telling us what that error means.

We can catch and recover from this error, but in this case, it feels like we should have specified some sort of default value. Perhaps every new object should be reset() by default or maybe it would be nice if we could force the user to tell us what those positions should be when they create the object.

Most object-oriented programming languages have the concept of a constructor, a special method that creates and initializes the object when it is created. Python is a little different; it has a constructor and an initializer. Normally, the constructor function is rarely ever used unless you’re doing something exotic. So we’ll start our discussion with the initialization method.

The Python initialization method is the same as any other method, except it has a special name: __init__. The leading and trailing double underscores mean, “this is a special method that the Python interpreter will treat as a special case”. Never name a function of your own with leading and trailing double underscores. It may mean nothing to Python, but there’s always the possibility that the designers of Python will add a function that has a special purpose with that name in the future, and when they do, your code will break.

Let’s start with an initialization function on our Point class that requires the user to supply x and y coordinates when the Point object is instantiated:

class Point:
def __init__(self, x, y):
self.move(x, y)

def move(self, x, y):
self.x = x
self.y = y

def reset(self):
self.move(0, 0)

# Constructing a Point
point = Point(3, 5)
print(point.x, point.y)

Now, our point can never go without a y coordinate! If we try to construct a point without including the proper initialization parameters, it will fail with a not enough arguments error similar to the one we received earlier when we forgot the self argument.

What if we don’t want to make those two arguments required? Well then we can use the same syntax Python functions use to provide default arguments. The keyword argument syntax appends an equals sign after each variable name. If the calling object does not provide that argument, then the default argument is used instead; the variables will still be available to the function, but they will have the values specified in the argument list. Here’s an example:

class Point:
def __init__(self, x=0, y=0):
self.move(x, y)

Most of the time, we put our initialization statements in an __init__ function. But as mentioned earlier, Python has a constructor in addition to its initialization function. You may never need to use the other Python constructor, but it helps to know it exists, so we’ll cover it briefly.

The constructor function is called __new__ as opposed to __init__, and accepts exactly one argument, the class that is being constructed (it is called before the object is constructed, so there is no self argument). It also has to return the newly created object. This has interesting possibilities when it comes to the complicated art of meta-programming, but is not very useful in day-to-day programming. In practice, you will rarely, if ever, need to use __new__, and __init__ will be sufficient.

Explaining yourself

Python is an extremely easy-to-read programming language; some might say it is self-documenting. However, when doing object-oriented programming, it is important to write API documentation that clearly summarizes what each object and method does. Keeping documentation up-to-date is difficult; the best way to do it is to write it right into our code.

Python supports this through the use of docstrings. Each class, function, or method header can have a standard Python string as the first line following the definition (the line that ends in a colon). This line should be indented the same as the following code.

Docstrings are simply Python strings enclosed with apostrophe (‘) or quote (“) characters. Often, docstrings are quite long and span multiple lines (the style guide suggests that line-length should not exceed 80 characters), which can be formatted as multi-line strings, enclosed in matching triple apostrophe (”’) or triple quote (“””) characters.

A docstring should clearly and concisely summarize the purpose of the class or method it is describing. It should explain any parameters whose usage is not immediately obvious, and is also a good place to include short examples of how to use the API. Any caveats or problems an unsuspecting user of the API should be aware of should also be noted.

To illustrate the use of docstrings, we will end this part with our completely documented Point class:

import math

class Point:
‘Represents a point in two-dimensional geometric coordinates’

def __init__(self, x=0, y=0):
”’Initialize the position of a new point. The x and y
coordinates can be specified. If they are not, the point
defaults to the origin.”’
self.move(x, y)

def move(self, x, y):
“Move the point to a new location in two-dimensional space.”
self.x = x
self.y = y

def reset(self):
‘Reset the point back to the geometric origin: 0, 0’
self.move(0, 0)

def calculate_distance(self, other_point):
“””Calculate the distance from this point to a second point
passed as a parameter.

This function uses the Pythagorean Theorem to calculate
the distance between the two points. The distance is returned
as a float.”””

return math.sqrt(

(self.x – other_point.x)**2 +

(self.y – other_point.y)**2)

Try typing or loading (remember, it’s python -i filename.py) this file into the interactive interpreter. Then enter help(Point) at the Python prompt. You should see nicely formatted documentation for the class, as shown in the following screenshot:

Objects in Python


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