Alex summarized well but, surprisingly, was too succinct.
First, let me reiterate the main points in Alex’s post:
The default implementation is useless (it’s hard to think of one which wouldn’t be, but yeah)
__repr__ goal is to be unambiguous
__str__ goal is to be readable
Container’s __str__ uses contained objects’ __repr__
Default implementation is useless
This is mostly a surprise because Python’s defaults tend to be fairly useful. However, in this case, having a default for __repr__
which would act like:
return "%s(%r)" % (self.__class__, self.__dict__)
would have been too dangerous (for example, too easy to get into infinite recursion if objects reference each other). So Python cops out. Note that there is one default which is true: if __repr__
is defined, and __str__
is not, the object will behave as though __str__=__repr__
.
This means, in simple terms: almost every object you implement should have a functional __repr__
that’s usable for understanding the object. Implementing __str__
is optional: do that if you need a “pretty print” functionality (for example, used by a report generator).
The goal of __repr__
is to be unambiguous
Let me come right out and say it — I do not believe in debuggers. I don’t really know how to use any debugger, and have never used one seriously. Furthermore, I believe that the big fault in debuggers is their basic nature — most failures I debug happened a long long time ago, in a galaxy far far away. This means that I do believe, with religious fervor, in logging. Logging is the lifeblood of any decent fire-and-forget server system. Python makes it easy to log: with maybe some project specific wrappers, all you need is a
log(INFO, "I am in the weird function and a is", a, "and b is", b, "but I got a null C — using default", default_c)
But you have to do the last step — make sure every object you implement has a useful repr, so code like that can just work. This is why the “eval” thing comes up: if you have enough information so eval(repr(c))==c
, that means you know everything there is to know about c
. If that’s easy enough, at least in a fuzzy way, do it. If not, make sure you have enough information about c
anyway. I usually use an eval-like format: "MyClass(this=%r,that=%r)" % (self.this,self.that)
. It does not mean that you can actually construct MyClass, or that those are the right constructor arguments — but it is a useful form to express “this is everything you need to know about this instance”.
Note: I used %r
above, not %s
. You always want to use repr()
[or %r
formatting character, equivalently] inside __repr__
implementation, or you’re defeating the goal of repr. You want to be able to differentiate MyClass(3)
and MyClass("3")
.
The goal of __str__
is to be readable
Specifically, it is not intended to be unambiguous — notice that str(3)==str("3")
. Likewise, if you implement an IP abstraction, having the str of it look like 192.168.1.1 is just fine. When implementing a date/time abstraction, the str can be "2010/4/12 15:35:22", etc. The goal is to represent it in a way that a user, not a programmer, would want to read it. Chop off useless digits, pretend to be some other class — as long is it supports readability, it is an improvement.
Container’s __str__
uses contained objects’ __repr__
This seems surprising, doesn’t it? It is a little, but how readable would it be if it used their __str__
?
[moshe is, 3, hello
world, this is a list, oh I don't know, containing just 4 elements]
Not very. Specifically, the strings in a container would find it way too easy to disturb its string representation. In the face of ambiguity, remember, Python resists the temptation to guess. If you want the above behavior when you’re printing a list, just
print("[" + ", ".join(l) + "]")
(you can probably also figure out what to do about dictionaries.
Summary
Implement __repr__
for any class you implement. This should be second nature. Implement __str__
if you think it would be useful to have a string version which errs on the side of readability.
My rule of thumb: __repr__
is for developers, __str__
is for customers.
__str__
so normal developers have readable object. On the other hand, __repr__
is for the SDK developers themselves.
Unless you specifically act to ensure otherwise, most classes don't have helpful results for either:
>>> class Sic(object): pass
...
>>> print(str(Sic()))
<__main__.Sic object at 0x8b7d0>
>>> print(repr(Sic()))
<__main__.Sic object at 0x8b7d0>
>>>
As you see -- no difference, and no info beyond the class and object's id
. If you only override one of the two...:
>>> class Sic(object):
... def __repr__(self): return 'foo'
...
>>> print(str(Sic()))
foo
>>> print(repr(Sic()))
foo
>>> class Sic(object):
... def __str__(self): return 'foo'
...
>>> print(str(Sic()))
foo
>>> print(repr(Sic()))
<__main__.Sic object at 0x2617f0>
>>>
as you see, if you override __repr__
, that's ALSO used for __str__
, but not vice versa.
Other crucial tidbits to know: __str__
on a built-on container uses the __repr__
, NOT the __str__
, for the items it contains. And, despite the words on the subject found in typical docs, hardly anybody bothers making the __repr__
of objects be a string that eval
may use to build an equal object (it's just too hard, AND not knowing how the relevant module was actually imported makes it actually flat out impossible).
So, my advice: focus on making __str__
reasonably human-readable, and __repr__
as unambiguous as you possibly can, even if that interferes with the fuzzy unattainable goal of making __repr__
's returned value acceptable as input to __eval__
!
eval(repr(foo))
evaluates to an object equal to foo
. You're right that it won't work outside of my test cases since I don't know how the module is imported, but this at least ensures that it works in some predictable context. I think this a good way of evaluating if the result of __repr__
is explicit enough. Doing this in a unit test also helps ensure that __repr__
follows changes to the class.
eval(repr(spam)) == spam
(at least in the right context), or eval(repr(spam))
raises a SyntaxError
. That way you avoid confusion. (And that's almost true for the builtins and most of the stdlib, except for, e.g., recursive lists, where a=[]; a.append(a); print(eval(repr(a)))
gives you [[Ellipses]]
…) Of course I don't do that to actually use eval(repr(spam))
, except as a sanity check in unit tests… but I do sometimes copy and paste repr(spam)
into an interactive session.
__str__
for each element instead of __repr__
? Seems plain wrong to me, as I implemented a readable __str__
in my object and when it is part of a list I see the uglier __repr__
instead.
eval(repr(x))
fails even for builtin types: class A(str, Enum): X = 'x'
will raise SyntaxError on eval(repr(A.X))
. It's sad, but understandable. BTW, eval(str(A.X))
actually works, but of course only if class A
is in scope -- so it's probably not very useful.
class Spam
, eval(repr(spam)) == spam
would require Spam.__eq__
to be implemented as well, right? By default object.__eq__
uses is
(docs).
__repr__
: representation of python object usually eval will convert it back to that object
__str__
: is whatever you think is that object in text form
e.g.
>>> s="""w'o"w"""
>>> repr(s)
'\'w\\\'o"w\''
>>> str(s)
'w\'o"w'
>>> eval(str(s))==s
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<string>", line 1
w'o"w
^
SyntaxError: EOL while scanning single-quoted string
>>> eval(repr(s))==s
True
In short, the goal of __repr__ is to be unambiguous and __str__ is to be readable.
Here is a good example:
>>> import datetime
>>> today = datetime.datetime.now()
>>> str(today)
'2012-03-14 09:21:58.130922'
>>> repr(today)
'datetime.datetime(2012, 3, 14, 9, 21, 58, 130922)'
Read this documentation for repr:
repr(object) Return a string containing a printable representation of an object. This is the same value yielded by conversions (reverse quotes). It is sometimes useful to be able to access this operation as an ordinary function. For many types, this function makes an attempt to return a string that would yield an object with the same value when passed to eval(), otherwise the representation is a string enclosed in angle brackets that contains the name of the type of the object together with additional information often including the name and address of the object. A class can control what this function returns for its instances by defining a __repr__() method.
Here is the documentation for str:
str(object='') Return a string containing a nicely printable representation of an object. For strings, this returns the string itself. The difference with repr(object) is that str(object) does not always attempt to return a string that is acceptable to eval(); its goal is to return a printable string. If no argument is given, returns the empty string, ''.
What is the difference between __str__ and __repr__ in Python?
__str__
(read as "dunder (double-underscore) string") and __repr__
(read as "dunder-repper" (for "representation")) are both special methods that return strings based on the state of the object.
__repr__
provides backup behavior if __str__
is missing.
So one should first write a __repr__
that allows you to reinstantiate an equivalent object from the string it returns e.g. using eval
or by typing it in character-for-character in a Python shell.
At any time later, one can write a __str__
for a user-readable string representation of the instance, when one believes it to be necessary.
__str__
If you print an object, or pass it to format
, str.format
, or str
, then if a __str__
method is defined, that method will be called, otherwise, __repr__
will be used.
__repr__
The __repr__
method is called by the builtin function repr
and is what is echoed on your python shell when it evaluates an expression that returns an object.
Since it provides a backup for __str__
, if you can only write one, start with __repr__
Here's the builtin help on repr
:
repr(...)
repr(object) -> string
Return the canonical string representation of the object.
For most object types, eval(repr(object)) == object.
That is, for most objects, if you type in what is printed by repr
, you should be able to create an equivalent object. But this is not the default implementation.
Default Implementation of __repr__
The default object __repr__
is (C Python source) something like:
def __repr__(self):
return '<{0}.{1} object at {2}>'.format(
type(self).__module__, type(self).__qualname__, hex(id(self)))
That means by default you'll print the module the object is from, the class name, and the hexadecimal representation of its location in memory - for example:
<__main__.Foo object at 0x7f80665abdd0>
This information isn't very useful, but there's no way to derive how one might accurately create a canonical representation of any given instance, and it's better than nothing, at least telling us how we might uniquely identify it in memory.
How can __repr__ be useful?
Let's look at how useful it can be, using the Python shell and datetime
objects. First we need to import the datetime
module:
import datetime
If we call datetime.now
in the shell, we'll see everything we need to recreate an equivalent datetime object. This is created by the datetime __repr__
:
>>> datetime.datetime.now()
datetime.datetime(2015, 1, 24, 20, 5, 36, 491180)
If we print a datetime object, we see a nice human readable (in fact, ISO) format. This is implemented by datetime's __str__
:
>>> print(datetime.datetime.now())
2015-01-24 20:05:44.977951
It is a simple matter to recreate the object we lost because we didn't assign it to a variable by copying and pasting from the __repr__
output, and then printing it, and we get it in the same human readable output as the other object:
>>> the_past = datetime.datetime(2015, 1, 24, 20, 5, 36, 491180)
>>> print(the_past)
2015-01-24 20:05:36.491180
#How do I implement them?
As you're developing, you'll want to be able to reproduce objects in the same state, if possible. This, for example, is how the datetime object defines __repr__
(Python source). It is fairly complex, because of all of the attributes needed to reproduce such an object:
def __repr__(self):
"""Convert to formal string, for repr()."""
L = [self._year, self._month, self._day, # These are never zero
self._hour, self._minute, self._second, self._microsecond]
if L[-1] == 0:
del L[-1]
if L[-1] == 0:
del L[-1]
s = "%s.%s(%s)" % (self.__class__.__module__,
self.__class__.__qualname__,
", ".join(map(str, L)))
if self._tzinfo is not None:
assert s[-1:] == ")"
s = s[:-1] + ", tzinfo=%r" % self._tzinfo + ")"
if self._fold:
assert s[-1:] == ")"
s = s[:-1] + ", fold=1)"
return s
If you want your object to have a more human readable representation, you can implement __str__
next. Here's how the datetime object (Python source) implements __str__
, which it easily does because it already has a function to display it in ISO format:
def __str__(self):
"Convert to string, for str()."
return self.isoformat(sep=' ')
Set __repr__ = __str__?
This is a critique of another answer here that suggests setting __repr__ = __str__
.
Setting __repr__ = __str__
is silly - __repr__
is a fallback for __str__
and a __repr__
, written for developers usage in debugging, should be written before you write a __str__
.
You need a __str__
only when you need a textual representation of the object.
Conclusion
Define __repr__
for objects you write so you and other developers have a reproducible example when using it as you develop. Define __str__
when you need a human readable string representation of it.
type(obj).__qualname__
?
self.__module__
to type(self).__module__
(since for exemple 3
has no __module__
) and type(self).__name__
to type(self).__qualname__
(since for instance with class A: class B: pass
that is what repr(A.B())
returns).
On page 358 of the book Python scripting for computational science by Hans Petter Langtangen, it clearly states that
The __repr__ aims at a complete string representation of the object;
The __str__ is to return a nice string for printing.
So, I prefer to understand them as
repr = reproduce
str = string (representation)
from the user's point of view although this is a misunderstanding I made when learning python.
A small but good example is also given on the same page as follows:
Example
In [38]: str('s')
Out[38]: 's'
In [39]: repr('s')
Out[39]: "'s'"
In [40]: eval(str('s'))
Traceback (most recent call last):
File "<ipython-input-40-abd46c0c43e7>", line 1, in <module>
eval(str('s'))
File "<string>", line 1, in <module>
NameError: name 's' is not defined
In [41]: eval(repr('s'))
Out[41]: 's'
repr
as reproduce. It is better to think of it as represent.
Apart from all the answers given, I would like to add few points :-
1) __repr__()
is invoked when you simply write object's name on interactive python console and press enter.
2) __str__()
is invoked when you use object with print statement.
3) In case, if __str__
is missing, then print and any function using str()
invokes __repr__()
of object.
4) __str__()
of containers, when invoked will execute __repr__()
method of its contained elements.
5) str()
called within __str__()
could potentially recurse without a base case, and error on maximum recursion depth.
6) __repr__()
can call repr()
which will attempt to avoid infinite recursion automatically, replacing an already represented object with ...
.
(2020 entry)
Q: What's the difference between __str__()
and __repr__()
?
https://i.stack.imgur.com/cpqeK.png
LONG
This question has been around a long time, and there are a variety of answers of which most are correct (not to mention from several Python community legends[!]). However when it comes down to the nitty-gritty, this question is analogous to asking the difference between the str()
and repr()
built-in functions. I'm going to describe the differences in my own words (which means I may be "borrowing" liberally from Core Python Programming so pls forgive me).
Both str()
and repr()
have the same basic job: their goal is to return a string representation of a Python object. What kind of string representation is what differentiates them.
str() & __str__() return a printable string representation of an object... something human-readable/for human consumption
repr() & __repr__() return a string representation of an object that is a valid Python expression, an object you can pass to eval() or type into the Python shell without getting an error.
For example, let's assign a string to x
and an int
to y
, and simply showing human-readable string versions of each:
>>> x, y = 'foo', 123
>>> str(x), str(y)
('foo', '123')
Can we take what is inside the quotes in both cases and enter them verbatim into the Python interpreter? Let's give it a try:
>>> 123
123
>>> foo
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'foo' is not defined
Clearly you can for an int
but not necessarily for a str
. Similarly, while I can pass '123'
to eval()
, that doesn't work for 'foo'
:
>>> eval('123')
123
>>> eval('foo')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<string>", line 1, in <module>
NameError: name 'foo' is not defined
So this tells you the Python shell just eval()
s what you give it. Got it? Now, let's repr()
both expressions and see what we get. More specifically, take its output and dump those out in the interpreter (there's a point to this which we'll address afterwards):
>>> repr(x), repr(y)
("'foo'", '123')
>>> 123
123
>>> 'foo'
'foo'
Wow, they both work? That's because 'foo'
, while a printable string representation of that string, it's not evaluatable, but "'foo'"
is. 123
is a valid Python int
called by either str()
or repr()
. What happens when we call eval()
with these?
>>> eval('123')
123
>>> eval("'foo'")
'foo'
It works because 123
and 'foo'
are valid Python objects. Another key takeaway is that while sometimes both return the same thing (the same string representation), that's not always the case. (And yes, yes, I can go create a variable foo
where the eval()
works, but that's not the point.)
More factoids about both pairs
Sometimes, str() and repr() are called implicitly, meaning they're called on behalf of users: when users execute print (Py1/Py2) or call print() (Py3+), even if users don't call str() explicitly, such a call is made on their behalf before the object is displayed. In the Python shell (interactive interpreter), if you enter a variable at the >>> prompt and press RETURN, the interpreter displays the results of repr() implicitly called on that object. To connect str() and repr() to __str__() and __repr__(), realize that calls to the built-in functions, i.e., str(x) or repr(y) result in calling their object's corresponding special methods: x.__str__() or y.__repr()__ By implementing __str__() and __repr__() for your Python classes, you overload the built-in functions (str() and repr()), allowing instances of your classes to be passed in to str() and repr(). When such calls are made, they turn around and call the class' __str__() and __repr__() (per #3).
To put it simply:
__str__
is used in to show a string representation of your object to be read easily by others.
__repr__
is used to show a string representation of the object.
Let's say I want to create a Fraction
class where the string representation of a fraction is '(1/2)' and the object (Fraction class) is to be represented as 'Fraction (1,2)'
So we can create a simple Fraction class:
class Fraction:
def __init__(self, num, den):
self.__num = num
self.__den = den
def __str__(self):
return '(' + str(self.__num) + '/' + str(self.__den) + ')'
def __repr__(self):
return 'Fraction (' + str(self.__num) + ',' + str(self.__den) + ')'
f = Fraction(1,2)
print('I want to represent the Fraction STRING as ' + str(f)) # (1/2)
print('I want to represent the Fraction OBJECT as ', repr(f)) # Fraction (1,2)
From an (An Unofficial) Python Reference Wiki (archive copy) by effbot:
__str__
"computes the "informal" string representation of an object. This differs from __repr__
in that it does not have to be a valid Python expression: a more convenient or concise representation may be used instead."
__repr__
is by no means required to return a vaild Python expression.
In all honesty, eval(repr(obj))
is never used. If you find yourself using it, you should stop, because eval
is dangerous, and strings are a very inefficient way to serialize your objects (use pickle
instead).
Therefore, I would recommend setting __repr__ = __str__
. The reason is that str(list)
calls repr
on the elements (I consider this to be one of the biggest design flaws of Python that was not addressed by Python 3). An actual repr
will probably not be very helpful as the output of print([your, objects])
.
To qualify this, in my experience, the most useful use case of the repr
function is to put a string inside another string (using string formatting). This way, you don't have to worry about escaping quotes or anything. But note that there is no eval
happening here.
eval(repr(obj))
is a sanity test and a rule of thumb - if this recreates the original object correctly then you have a decent __repr__
implementation. It's not intended that you actually serialize objects this way.
eval
is not inherently dangerous. Is not more dangerous than unlink
, open
, or writing to files. Should we stop writing to files because perhaps a malicious attack could use an arbitrary file path to put content inside? Everything is dangerous if dumbly used by dumb people. Idiocy is dangerous. Dunning-Kruger effects are dangerous. eval
is just a function.
str
- Creates a new string object from the given object.
repr
- Returns the canonical string representation of the object.
The differences:
str():
makes object readable
generates output for end-user
repr():
needs code that reproduces object
generates output for developer
One aspect that is missing in other answers. It's true that in general the pattern is:
Goal of __str__: human-readable
Goal of __repr__: unambiguous, possibly machine-readable via eval
Unfortunately, this differentiation is flawed, because the Python REPL and also IPython use __repr__
for printing objects in a REPL console (see related questions for Python and IPython). Thus, projects which are targeted for interactive console work (e.g., Numpy or Pandas) have started to ignore above rules and provide a human-readable __repr__
implementation instead.
From the book Fluent Python:
A basic requirement for a Python object is to provide usable string representations of itself, one used for debugging and logging, another for presentation to end users. That is why the special methods __repr__ and __str__ exist in the data model.
You can get some insight from this code:
class Foo():
def __repr__(self):
return("repr")
def __str__(self):
return("str")
foo = Foo()
foo #repr
print(foo) #str
__str__
can be invoked on an object by calling str(obj)
and should return a human readable string.
__repr__
can be invoked on an object by calling repr(obj)
and should return internal object (object fields/attributes)
This example may help:
class C1:pass
class C2:
def __str__(self):
return str(f"{self.__class__.__name__} class str ")
class C3:
def __repr__(self):
return str(f"{self.__class__.__name__} class repr")
class C4:
def __str__(self):
return str(f"{self.__class__.__name__} class str ")
def __repr__(self):
return str(f"{self.__class__.__name__} class repr")
ci1 = C1()
ci2 = C2()
ci3 = C3()
ci4 = C4()
print(ci1) #<__main__.C1 object at 0x0000024C44A80C18>
print(str(ci1)) #<__main__.C1 object at 0x0000024C44A80C18>
print(repr(ci1)) #<__main__.C1 object at 0x0000024C44A80C18>
print(ci2) #C2 class str
print(str(ci2)) #C2 class str
print(repr(ci2)) #<__main__.C2 object at 0x0000024C44AE12E8>
print(ci3) #C3 class repr
print(str(ci3)) #C3 class repr
print(repr(ci3)) #C3 class repr
print(ci4) #C4 class str
print(str(ci4)) #C4 class str
print(repr(ci4)) #C4 class repr
Excellent answers already cover the difference between __str__
and __repr__
, which for me boils down to the former being readable even by an end user, and the latter being as useful as possible to developers. Given that, I find that the default implementation of __repr__
often fails to achieve this goal because it omits information useful to developers.
For this reason, if I have a simple enough __str__
, I generally just try to get the best of both worlds with something like:
def __repr__(self):
return '{0} ({1})'.format(object.__repr__(self), str(self))
>>> print(decimal.Decimal(23) / decimal.Decimal("1.05"))
21.90476190476190476190476190
>>> decimal.Decimal(23) / decimal.Decimal("1.05")
Decimal('21.90476190476190476190476190')
When print()
is called on the result of decimal.Decimal(23) / decimal.Decimal("1.05")
the raw number is printed; this output is in string form which can be achieved with __str__()
. If we simply enter the expression we get a decimal.Decimal
output — this output is in representational form which can be achieved with __repr__()
. All Python objects have two output forms. String form is designed to be human-readable. The representational form is designed to produce output that if fed to a Python interpreter would (when possible) reproduce the represented object.
One important thing to keep in mind is that container's __str__ uses contained objects' __repr__.
>>> from datetime import datetime
>>> from decimal import Decimal
>>> print (Decimal('52'), datetime.now())
(Decimal('52'), datetime.datetime(2015, 11, 16, 10, 51, 26, 185000))
>>> str((Decimal('52'), datetime.now()))
"(Decimal('52'), datetime.datetime(2015, 11, 16, 10, 52, 22, 176000))"
Python favors 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.
__repr__
when it (__str__
) is not defined! So, you are wrong.
In a nutshell:
class Demo:
def __repr__(self):
return 'repr'
def __str__(self):
return 'str'
demo = Demo()
print(demo) # use __str__, output 'str' to stdout
s = str(demo) # __str__ is used, return 'str'
r = repr(demo) # __repr__ is used, return 'repr'
import logging
logger = logging.getLogger(logging.INFO)
logger.info(demo) # use __str__, output 'str' to stdout
from pprint import pprint, pformat
pprint(demo) # use __repr__, output 'repr' to stdout
result = pformat(demo) # use __repr__, result is string which value is 'str'
Understand __str__
and __repr__
intuitively and permanently distinguish them at all.
__str__
return the string disguised body of a given object for readable of eyes
__repr__
return the real flesh body of a given object (return itself) for unambiguity to identify.
See it in an example
In [30]: str(datetime.datetime.now())
Out[30]: '2017-12-07 15:41:14.002752'
Disguised in string form
As to __repr__
In [32]: datetime.datetime.now()
Out[32]: datetime.datetime(2017, 12, 7, 15, 43, 27, 297769)
Presence in real body which allows to be manipulated directly.
We can do arithmetic operation on __repr__
results conveniently.
In [33]: datetime.datetime.now()
Out[33]: datetime.datetime(2017, 12, 7, 15, 47, 9, 741521)
In [34]: datetime.datetime(2017, 12, 7, 15, 47, 9, 741521) - datetime.datetime(2
...: 017, 12, 7, 15, 43, 27, 297769)
Out[34]: datetime.timedelta(0, 222, 443752)
if apply the operation on __str__
In [35]: '2017-12-07 15:43:14.002752' - '2017-12-07 15:41:14.002752'
TypeError: unsupported operand type(s) for -: 'str' and 'str'
Returns nothing but error.
Another example.
In [36]: str('string_body')
Out[36]: 'string_body' # in string form
In [37]: repr('real_body')
Out[37]: "'real_body'" #its real body hide inside
Hope this help you build concrete grounds to explore more answers.
__str__ must return string object whereas __repr__ can return any python expression. If __str__ implementation is missing then __repr__ function is used as fallback. There is no fallback if __repr__ function implementation is missing. If __repr__ function is returning String representation of the object, we can skip implementation of __str__ function.
Source: https://www.journaldev.com/22460/python-str-repr-functions
__repr__
is used everywhere, except by print
and str
methods (when a __str__
is defined !)
Every object inherits __repr__
from the base class that all objects created.
class Person:
pass
p=Person()
if you call repr(p)
you will get this as default:
<__main__.Person object at 0x7fb2604f03a0>
But if you call str(p)
you will get the same output. it is because when __str__
does not exist, Python calls __repr__
Let's implement our own __str__
class Person:
def __init__(self,name,age):
self.name=name
self.age=age
def __repr__(self):
print("__repr__ called")
return f"Person(name='{self.name}',age={self.age})"
p=Person("ali",20)
print(p)
and str(p)
will return
__repr__ called
Person(name='ali',age=20)
let's add __str__()
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def __repr__(self):
print('__repr__ called')
return f"Person(name='{self.name}, age=self.age')"
def __str__(self):
print('__str__ called')
return self.name
p=Person("ali",20)
if we call print(p)
and str(p), it will call __str__()
so it will return
__str__ called
ali
repr(p)
will return
repr called "Person(name='ali, age=self.age')"
Let's omit __repr__
and just implement __str__
.
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def __str__(self):
print('__str__ called')
return self.name
p=Person('ali',20)
print(p)
will look for the __str__
and will return:
__str__ called
ali
NOTE= if we had __repr__
and __str__
defined, f'name is {p}'
would call __str__
Programmers with prior experience in languages with a toString method tend to implement __str__ and not __repr__. If you only implement one of these special methods in Python, choose __repr__.
From Fluent Python book, by Ramalho, Luciano.
Basically __str__
or str() is used for creating output that is human-readable are must be for end-users. On the other hand, repr() or __repr__
mainly returns canonical string representation of objects which serve the purpose of debugging and development helps the programmers.
Success story sharing
l
(lowercase letter "L") will be syntax error in python 4.0 ;)