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This article mainly introduces "what is the difference between Python and is". In daily operation, I believe that many people have doubts about the difference between Python and is. Xiaobian consulted all kinds of materials and sorted out simple and easy-to-use methods of operation. I hope it will be helpful for you to answer the question of "what is the difference between Python and is?" Next, please follow the editor to study!

Both "= =" and "is" are operators in Python. Beginners may understand "a = = b" as "an equals b" and "an is b" as "an is b". Maybe this is why beginners in Python confuse "=" with "is".

Before going any further, I'd like to give a few use cases for "=" and "is":

> a = 5 > b = 5 > a = = bTrue > an is bTrue

It's easy, isn't it? both True = b and an is b can return True. The next example is:

> a = 1000 > b = 1000 > a = = bTrue > > an is b False

Why is that? The only difference between the second example and the first is that the values of an and b have changed from 5 to 1000, but the output of "= =" and "is" is completely different. Let's look at the next example:

> a = [] > > b = [] > a = = bTrue > an is b False

If that's not shocking enough, take a look at the last example:

> > a = 1000 > b = 1000 > a = = bTrue > > an is b False > a = b > a = = bTrue > an is bTrue

The formal operation of "= =" is equal, while the operation of "is" is the identity. Using "=" is to compare the values of two objects. "a = = b" should be interpreted as "whether the value of an is equal to the value of b". In all the above examples, the value of an is always equal to the value of b (even for the example of an empty column), so "a = = b" is always true.

Before I explain the concept of identity, I need to introduce the id function. The identity of the object can be obtained through the id function. The identity of an object is always unique and constant, and you can think of it as the address of the object. If two objects have the same identity, their values must also be the same.

> id (a) 2047616

The operator "is" is used to compare whether the identity of two objects is the same, and "an is b" means "the identity of an is the same as that of b".

Now that you know the true meaning of "= =" and "is", we can discuss the above example in depth.

The first is the difference between the first case and the second case. Because Python stores a list of integers between-5 and 256, each integer has a fixed corresponding identity. When you assign an integer variable in this range, Python assigns the variable as an integer in the array column.

So, in the first example, because the identities of an and b are both obtained from the array list, their identities are of course the same, so an is b is true.

> a = 5 > id (a) 1450375152 > b = 5 > id (b) 1450375152

However, once the value of a variable is not within this range, because there is no object within Python that corresponds to the value, Python will create a new identity for the variable and assign a value to it.

As mentioned earlier, each created identity is unique, so even if two variables have the same value, their identities will never be the same. This is why the an is b in the second example returns False.

> a = 1000 > id (a) 12728608 > b = 1000 > id (b) 13620208

In addition, suppose you open two consoles, and if the value is still in the range, you can get the same identification. However, if the value is not in the range, the result will of course be different.

Once you understand the difference between the first case and the second case, it is easy to understand the results of the third case. Because Python does not store an "empty list" object, Python creates a new object and assigns an "empty list" value. Whether the two lists are empty or the elements are the same, the result is the same.

> a = [1 bTrue 10 > b = [1] > a = = id (a) 12578024 > id (b) 12578056

Let's take a look at the last example. The only difference between the second case and the last one is that there is an extra line of code a = b. However, this line of code changes the fate of the variable a. The following results explain why:

> > a = 1000 > > b = 2000 > id (a) 2047616 > > id (b) 5034992 > a = b > id (a) 5034992 > id (b) 5034992 > > a2000 > > b2000

As you can see, after a = b, the identity of a becomes the logo of b. A = b assigns the logo of b to a. So an and b have the same identity, and the value of an is now equal to the value of b, that is, 2000.

The last example conveys an important message that you may inadvertently change the value of an object, especially if the object is a list.

> a = [1 id (a) 5237992 > > b = a > id (b) 5237992 > a.append (4) > a [1, 2, 4] > > b [1, 2, 4]

As you can see from the above example, if an and b have the same identity, their values must be the same. So when a new element is attached to a, the value of b is also affected. To avoid this, if you want to copy the value of one object to another without referencing the same identity, one way is to use deepcopy in the copy module. For the list, you can also implement it with b = a [:].

> import copy > a = [1Jing 2Jing 3] > > b = copy.deepcopy (a) > id (a) 39785256 > id (b) 5237992

Use [:] to copy the element to the new variable:

Id (a) 39785256 > b = a [:] > id (b) 23850216 > > a.append (4) > a [1pime 2pr 3,4] > > b [1pr 2pr 3]. At this point, the study of "what is the difference between Python = = and is" is over. I hope to solve everyone's doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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