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Python's str and repr built-in methods are similar, but not the same. Use str to print nice-looking strings for end users and use repr for debugging purposes. Similarly, in your classes you should implement the __str__ and __repr__ dunder methods with these two use cases in mind.

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A Python code snippet with a custom class and stubs for the dunder methods `str` and `repr`.

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str and repr

Python has two built-in mechanisms that allow you to convert an object to a string, so that you can look at it and print it. I am talking about the str class and the built-in repr function.

There is often confusion as to what the differences between these two built-ins are, but the difference is simple and clear. The str class is used when you want to convert something to the string type, and is also used when you need a readable representation of your object. On the other hand, the repr function is used to create an unambiguous representation of its argument.

End users generally use str because they want to print readable and good looking text, whereas developers may use repr because they need to debug code and need to make sure they know what they are looking at. For example, take a look at the following interactive session:

>>> print(3)
>>> print("3")
>>> 3
>>> "3"

The print function calls str on its argument and then displays it, so both the integer 3 and the string "3" get printed the same way: you have no way to tell if the original object is an integer or a string. After that, you see that simply writing the integer 3 and the string "3" in the REPL returns an unambiguous representation of the object: you can tell integers and strings apart, because the REPL is using repr under the hood to show objects. repr is also used when your object is inside a container, like a list or a dictionary, because containers usually defer their str behaviour to repr, as you can see by looking at PEP 3140 and at the following session:

>>> [3, "3"]
[3, '3']
>>> print([3, "3"]) 
[3, '3']
>>> str([3, "3"]) == repr([3, "3"])

The __str__ and __repr__ dunder methods

When you are defining your own classes in Python you will probably want to specify how your objects should look when printed, given that the default behaviour in Python is not very helpful:

>>> class A:
...     pass
>>> a = A()
>>> print(a)
<__main__.A object at 0x012DF640>
>>> a
<__main__.A object at 0x012DF640>

If you want to display your objects properly, you will want to implement the __str__ and __repr__ dunder methods (dunder stands for double underscore), and the implementations should follow the use case of str and repr outlined above: the implementation of __str__ should provide a nice, readable representation of your object and __repr__ should represent unambiguously your object, preferably by providing an expression that could be used to rebuild the object.

If you are not acquainted with Python's dunder methods, you may want to subscribe to the Pydon't newsletter, I will write more about them later. Until then, you may want to have a look at the Python 3 Docs and what they say about the data model.

When implementing custom classes, I suggest you start by implementing __repr__, as __str__ will default to calling __repr__ if no custom implementation is given, but only implementing __str__ still leaves you with rather unhelpful representations of your objects.

If you just implement __str__:

>>> class A:
...     def __str__(self):
...             return "A"
>>> a = A()
>>> a
<__main__.A object at 0x01600760>
>>> print(a)

if you just implement __repr__:

>>> class A:
...     def __repr__(self):
...             return "A"
>>> a = A()
>>> a
>>> print(a)

Examples in code


Python's datetime module supplies classes for manipulating dates and times. A simple date could be created like so:

>>> import datetime
>>> date = datetime.datetime(2021, 2, 2)

Now that we have your date object of type datetime.datetime, we can see what its repr looks like and compare it to its str version:

>>> print(repr(date))
datetime.datetime(2021, 2, 2, 0, 0)
>>> print(str(date))
2021-02-02 00:00:00

We can see that repr(date) could be used to create the same exact object:

>>> date == datetime.datetime(2021, 2, 2, 0, 0)
>>> date == eval(repr(date))

Whereas str(date) creates a nice-looking representation of the date in question. Notice that from its str we can't even tell that we were dealing with a datetime.datetime object.

2D point

An example custom usage of the __str__ and __repr__ dunder methods could come into play if you were to implement a simple class that represents 2D points, for example because you have to deal with images or a game or maps, or whatever your use case is.

Ignoring all other methods you would certainly implement, your class could look like this:

class Point2D:
    """A class to represent points in a 2D space."""

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

    def __str__(self):
        """Provide a good-looking representation of the object."""
        return f"({self.x}, {self.y})"

    def __repr__(self):
        """Provide an unambiguous way of rebuilding this object."""
        return f"Point2D({repr(self.x)}, {repr(self.y)})"

p = Point2D(0, 0) # the origin.
print(f"To build the point {p} in your code, try writing {repr(p)}.")

Running this code prints To build the point (0, 0) in your code, try writing Point2D(0, 0). to your console. Your end user may be accustomed to 2D points, and thus they may need nothing more than the standard (x, y) representation of a 2D point. During debugging, the Point2D prefix is useful because it helps you distinguish between a tuple and a custom Point2D instance.


When implementing custom classes you will probably want to give a custom implementation of the __repr__ dunder method, and also a __str__ if you need your instances to look good when printed to the end user. __str__ and str are used when you need good looking strings, while the purpose of __repr__ and repr is to create unambiguous representations of your objects.

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Online references last consulted on the 2nd of February of 2021.

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