Detailed analysis of is and == in Python (with code)

This article brings you a detailed analysis of is and == in Python (with code). It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.

Everything in Python is an object.

The three basic elements contained in objects in Python are:

• id (identity identification)
• type (data type)
• value(value)

To compare whether objects are equal, you can use == or is.

is and == are both used to compare and judge objects, but the contents of object comparison and judgment are different. Let’s take a look at the specific difference?

is compares whether the id values ​​of the two objects are equal, that is, whether the two objects are the same instance object and point to the same memory address.

== Compares whether the contents of two objects are equal. By default, the __eq__ method of the object will be called.

== is a comparison operator among python standard operators, used to compare and determine whether the values ​​of two objects are equal.

Let’s look at an example first

>>> a = [1, 2, 3]
>>> b = a
>>> b is a 
True
>>> b == a
True
>>> b = a[:]
>>> b is a
False
>>> b == a
True

is is also called the identity operator, that is, whether the id is the same.

Look at the code below. The ids of variables a and b are different, so b == a is True, b is a is False.

Look at their ids again:

>>> id(a)
4364243328
>>> 
>>> id(b)
4364202696

In which cases is and == have exactly the same results?

>>> a = 256
>>> b = 256
>>> a is b
True
>>> a == b
True
>>> a = 1000
>>> b = 10**3
>>> a == b
True
>>> a is b
False
>>>

So the number types are not exactly the same.

Then why is it the same at 256 but different at 1000?

Because of performance considerations, Python has done a lot of internal optimization work. For integer objects, Python caches some frequently used integer objects and saves them in a linked list called small_ints. In Python During the entire life cycle, any place that needs to reference these integer objects will no longer create new objects, but directly reference the objects in the cache.

Python puts these small objects that may be frequently used in the range [-5, 256] in small_ints. Whenever you need to use some small integers, just take them from here. To temporarily create new objects.

>>> c = 'miracle.young'
>>> d = 'miracle.young'
>>> c is d
False
>>> c == d
True
>>> c = 'miracleyoung'
>>> d = 'miracleyoung'
>>> c is c
True
>>> c == d
True

So the string types are not exactly the same, this is related to the interpreter implementation.

>>> a = (1,2,3) # a和b为元组类型
>>> b = (1,2,3)
>>> a is b
False
>>> a = [1,2,3] # a和b为list类型
>>> b = [1,2,3]
>>> a is b
False
>>> a = {'miracle':100,'young':1} # a和b为dict类型
>>> b = {'miracle':100,'young':1}
>>> a is b
False
>>> a = set([1,2,3]) # a和b为set类型
>>> b = set([1,2,3])
>>> a is b
False

So when the variable is a number, string, tuple, list, or dictionary, is and == are not the same and cannot be used interchangeably! When comparing values, you should use ==, and when comparing whether they are the same memory address, you should use is.
Of course, there are many situations where values ​​are compared in development.

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