### Purpose of __str__ and __repr__ in Python

Before we dive into the discussion, let’s check out the official documentation of Python about these two functions:

object.__repr__(self): called by the repr() built-in function and by string conversions (reverse quotes) to compute the “official” string representation of an object.
object.__str__(self): called by the str() build-in function and by the print statement to compute the “informal” string representation of an object.

Quote from Python’s Data Model

From the official documentation, we know that both __repr__ and __str__ are used to “represent” an object. __repr__ should be the “official” representation while __str__ is the “informal” representation.

So, what does Python’s default __repr__ and __str__ implementation of any object look like?

For example, let’s say we have a int x and a str y and we want to know the return value of __repr__ and __str__ of these two objects:

>>> x = 1
>>> repr(x)
'1'
>>> str(x)
'1'
>>> y = 'a string'
>>> repr(y)
"'a string'"
>>> str(y)
'a string'

While the return of repr() and str() are identical for int x, you should notice the difference between the return values for str y. It is important to realize the default implementation of __repr__ for a str object can be called as an argument to eval and the return value would be a valid str object:

>>> repr(y)
"'a string'"
>>> y2 = eval(repr(y))
>>> y == y2
True

While the return value of __str__ is not even a valid statement that can be executed by eval:

>>> str(y)
'a string'
>>> eval(str(y))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<string>", line 1
a string
^
SyntaxError: unexpected EOF while parsing

Therefore, a “formal” representation of an object should be callable by eval() and return the same object, if possible. If not possible, such as in the case where the object’s members are referring itself that leads to infinite circular reference, then __repr__ should be unambiguous and contain as much information as possible.

>>> class ClassA(object):
...     def __init__(self, b=None):
...         self.b = b
...
...     def __repr__(self):
...         return '%s(%r)' % (self.__class__, self.b)
...
>>>
>>> class ClassB(object):
...     def __init__(self, a=None):
...         self.a = a
...
...     def __repr__(self):
...         return "%s(%r)" % (self.__class__, self.a)
...
>>> a = ClassA()
>>> b = ClassB(a=a)
>>> a.b = b
>>> repr(b)
RuntimeError: maximum recursion depth exceeded while calling a Python object

Instead of literally following the requirement of __repr__ for ClassB which causes an infinite recursion problem where a.__repr__ calls b.__repr__ which calls a.__repr__ which calls b.__repr__, on and on forever, you could define ClassB.__repr__ in a different way. A way that shows as much information about an object as possible would be just as good as a valid eval-confined __repr__.

>>> class ClassB(object):
...     def __init__(self, a=None):
...         self.a = a
...
...     def __repr__(self):
...         return '%s(a=a)' % (self.__class__)
...

>>> a = ClassA()
>>> b = ClassB(a=a)
>>> a.b = b
>>> repr(a)
"<class '__main__.ClassA'>(<class '__main__.ClassB'>(a=a))"
>>> repr(b)
"<class '__main__.ClassB'>(a=a)"

Since __repr__ is the official representation for an object, you always want to call "repr(an_object)" to get the most comprehensive information about an object. However, sometimes __str__ is useful as well. Because __repr__ could be too complicated to inspect if the object in question is complex (imagine an object with a dozen attributes), __str__ is helpful to serve as a quick overview of complicated objects. For example, suppose you want to inspect a datetime object in the middle of a lengthy log file to find out why the datetime of a user’s photo is not correct:

>>> from datetime import datetime
>>> now = datetime.now()
>>> repr(now)
'datetime.datetime(2013, 2, 5, 4, 43, 11, 673075)'
>>> str(now)
'2013-02-05 04:43:11.673075'

The __str__ representation of now looks cleaner and easier to read than the formal representation generated from __repr__. Sometimes, being able to quickly grasp what’s stored in an object is valuable to grab the “big” picture of a complex program.

### Gotchas between __str__ and __repr__ in Python

One important catch to keep in mind is that container’s __str__ uses contained objects’ __repr__.

>>> from datetime import datetime
>>> from decimal import Decimal
>>> print((Decimal('42'), datetime.now()))
(Decimal('42'), datetime.datetime(2013, 2, 5, 4, 53, 32, 646185))
>>> str((Decimal('42'), datetime.now()))
"(Decimal('42'), datetime.datetime(2013, 2, 5, 4, 57, 2, 459596))"

Since Python favours unambiguity over readability, the __str__ call of a tuple calls the contained objects’ __repr__, the “formal” representation of an object. Although the formal representation is harder to read than an informal one, it is unambiguous and more robust against bugs.

### Tips and Suggestions between __str__ and __repr__ in Python

• Implement __repr__ for every class you implement. There should be no excuse.
• Implement __str__ for classes which you think readability is more important of non-ambiguity.