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Understanding the "is" operator [duplicate]
(11 answers)
Why does comparing strings using either '==' or 'is' sometimes produce a different result?
(15 answers)
Closed 1 year ago.
Why is this:
x = str(input("Enter a string: ")) #input "cat"
y = str(input("Enter another string: ")) #input "cat"
print(x is y) #Outputs False
Not the same as this:
x = "cat"
y = "cat"
print(x is y) #Outputs True
From this Real Python article:
The == operator compares the value or equality of two objects, whereas the Python is operator checks whether two variables point to the same object in memory. In the vast majority of cases, this means you should use the equality operators == and !=, except when you’re comparing to None.
>>> x = None
>>> y = None
>>> id(x); id(y)
4389651888
4389651888
>>> x is y
True
== calls the __eq__ method of an object, is checks whether the id() of two objects is equal (memory address).
The rest of the article I linked is really informative; it talks about how Python will give the same id to small integers by default, and that you can use the sys.intern() method to ensure string variables point to the same object in memory as well.
The is operator in python is used to check if two objects point to the same memory location.
In the second case, when python runs, for optimization purposes both x and y point to the same memory location. However, in the first case, x and y are not defined until the user inputs a value during run time. So, they're both allocated memory in different locations.
Related
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identifying objects, why does the returned value from id(...) change?
(7 answers)
Python integer caching
(2 answers)
Closed 6 years ago.
In Python I created integer and list objects as follows:
a = 10
b = 10
x = []
y = []
Then I get the following results while comparing the id of a and b, and the id of x and y
id(a)==id(b) returns True
id(x)==id(y) returns False
Somewhere I read that assignment in Python never copies data. My question is why x and y do not have the same id?
You must know that python integers ar cached and inmutable, that means that both a and b are labeling the same 10. Lists are objects and they are allocated separetly, thats why their ids are diferent from the beggining
Lists are mutable, if the same object was used, when you add an item to one of the list, you'd see the change on the other one as well.
Identity of integers is implementation dependent, and it is usually valid only for small numbers; good reading here.
By the way, == is the equality operator. A shortest (and cleaner) way for id(a)==id(b) is to use the identity operator is. In your case: a is b.
x = [] is a shorthand for instantiating a new list, which means a new object with a new object ID. Even though x and y are assigned as empty lists, they are simply references to memory locations allocated for the respective lists. If id(x) == id(y) then x and y would share the same object ID, which would effectively mean they share a memory location, or are references to the same object (so any changes made to one would apply to the other).
On the other hand, id(a) == id(b) because they are both integers, which are primitive data types.
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Why empty string is on every string? [duplicate]
(2 answers)
Closed 7 years ago.
This might be a very elementary question and I should know this but how does the following line evaluate to true?
>>> '' in 'spam'
True
Why/How is the empty string/character in a non-empty string? I tried this in Idle for Python 2.7 and it's evaluating to true. I found this from the link to Automate the Boring Stuff chapter 6
Because the in operator is to test membership, and by that notion, the empty set is a subset of all other sets. To be consistent in that regard, the in operator was deliberately designed to act accordingly.
5.9 Comparisons
The operators in and not in test for collection membership. x in s evaluates to true if x is a member of the collection s, and false otherwise. x not in s returns the negation of x in s. The collection membership test has traditionally been bound to sequences; an object is a member of a collection if the collection is a sequence and contains an element equal to that object. However, it make sense for many other object types to support membership tests without being a sequence. In particular, dictionaries (for keys) and sets support membership testing.
For the list and tuple types, x in y is true if and only if there exists an index i such that x == y[i] is true.
For the Unicode and string types, x in y is true if and only if x is a substring of y. An equivalent test is y.find(x) != -1. Note, x and y need not be the same type; consequently, u'ab' in 'abc' will return True. Empty strings are always considered to be a substring of any other string, so "" in "abc" will return True.
This question already has answers here:
How is the 'is' keyword implemented in Python?
(11 answers)
Closed 8 years ago.
s="wall"
d="WALL".lower()
s is d returns False.
s and d are having the same string. But Why it returned False?
== tests for equality. a == b tests whether a and b have the same value.
is tests for identity — that is, a is b tests whether a and b are in fact the same object. Just don't use it except to test for is None.
You seem to be misunderstanding the is operator. This operator returns true if the two variables in question are located at the same memory location. In this instance, although you have two variables both storing the value "wall", they are still both distinct in that each has its own copy of the word.
In order to properly check String equality, you should use the == operator, which is value equality checking.
"is" keyword compares the objects IDs, not just whether the value is equal.
It's not the same as '===' operator in many other languages.
'is' is equivalent to:
id(s) == id(d)
There are some even more interesting cases. For example (in CPython):`
a = 5
b = 5
a is b # equals to True
but:
c = 1200
d = 1200
c is d # equals to False
The conclusion is: don't use 'is' to compare values as it can lead to confusion.
By using is your are comparing their identities, if you try print s == d, which compares their values, you will get true.
Check this post for more details: String comparison in Python: is vs. ==
Use == to compare objects for equality. Use is to check if two variables reference the exact same objects. Here s and d refer to two distinct string objects with identical contents, so == is the correct operator to use.
This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Python “is” operator behaves unexpectedly with integers
I'm learning Python, and am curious as to why:
x = 500
x is 500
returns False, but:
y = 100
y is 100
returns True?
Python reuses small integers. That is, all 1s (for example) are the same 1 object. The range is -5 to 255, if I remember correctly, though this is a CPython implementation detail that should not be relied upon. I am pretty sure Jython and IronPython, for example, handle this differently.
The reason this works out fine is that ints are immutable. That is, you can't change a 4 to a 5 in-place. if a has a value of 4, a = 5 is actually pointing a to a different object, not changing the value a contains. Python doesn't share any mutable types (such as lists) where unexpectedly having multiple references to the same object might cause problems.
You should use == for comparing most things. is is for checking to see whether two references point to the same object; it is roughly equivalent to id(x) == id(y).
is tests for identity - x is y asks if they are the same object, not if they are simply 'equivalent'. So you also have, eg:
>>> x = []
>>> y = []
>>> z = x
>>> x is y
False
>>> x is z
True
For equivalence, you want to test equality:
>>> x = 500
>>> x == 500
True
Python (or, at least, cpython - the major implementation) does some optimisations so that certain immutable objects only exist once throughout the lifetime of the interpreter. So, every 5 throughout your program will be the same integer object. The same thing happens with string literals, for example.
"is" compare objects IDs and "==" will compare object values. So, if you need to compare values, go with "==" and if you whant to compare objects, go with "is".
As in Python everything is an object, is compares objects IDs, it's faster, but some times unpredictable. You need to be very sure of what you are doing to use "is" for simple comparsion.
About the situation above, I found here: http://docs.python.org/c-api/int.html the following remark:
The current implementation keeps an array of integer objects for all
integers between -5 and 256, when you create an int in that range you
actually just get back a reference to the existing object. So it
should be possible to change the value of 1. I suspect the behaviour
of Python in this case is undefined. :-)
So, you can do the following test and see this behaviour:
>>> a = 256
>>> id(a)
19707932
>>> id(256)
19707932
>>> a = 257
>>> id(a)
26286076
>>> id(257)
26286064
So, for integers above 256, "is" will not work. Be careful using "is" for comparsion.
This question already has answers here:
Closed 12 years ago.
Possible Duplicates:
Types for which “is” keyword may be equivalent to equality operator in Python
Python “is” operator behaves unexpectedly with integers
Hi.
I have a question which perhaps might enlighten me on more than what I am asking.
Consider this:
>>> x = 'Hello'
>>> y = 'Hello'
>>> x == y
True
>>> x is y
True
I have always used the comparison operator. Also I read that is compares the memory address and hence in this case, returns True
So my question is, is this another way to compare variables in Python? If yes, then why is this not used?
Also I noticed that in C++, if the variables have the same value, their memory addresses are different.
{ int x = 40; int y = 40; cout << &x, &y; }
0xbfe89638, 0xbfe89634
What is the reason for Python having the same memory addresses?
This is an implementation detail and absolutely not to be relied upon. is compares identities, not values. Short strings are interned, so they map to the same memory address, but this doesn't mean you should compare them with is. Stick to ==.
There are two ways to check for equality in Python: == and is. == will check the value, while is will check the identity. In almost every case, if is is true, then == must be true.
Sometimes, Python (specifically, CPython) will optimize values together so that they have the same identity. This is especially true for short strings. Python realizes that 'Hello' is the same as 'Hello' and since strings are immutable, they become the same through string interning / string pooling.
See a related question: Python: Why does ("hello" is "hello") evaluate as True?
This is because of a Python feature called String interning which is a method of storing only one copy of each distinct string value.
In Python both strings and integers are immutable therefore you can cache them. Integers in the range of ´-5´ to ´256´ and small strings(don't know the exact size atm) get cached, therefore they are the same object. x and y are only names that refer to these objects.
Also == compares for equals values, while is compares for object identity. None True and False are global objects, for example you can rebind False to True.
The following shows that not every thing is being cached:
x = 'Test' * 2000
y = 'Test' * 2000
>>> x == y
True
>>> x is y
False
>>> x = 10000000000000
>>> y = 10000000000000
>>> x == y
True
>>> x is y
False
In Python, variables are just names that point to some object (and they can point to the same object). In C++, variables also define the actual memory that is reserved for them; this is why they have distinct memory addresses.
About Python string interning and differences between the two comparison operators, see carl's response.