Complete Methods For Python List Copy

After my post on python shallow and deep copy, a reader asked me: you can also copy a list with list slicing and it is fast. Which should I use?

Well, I decided to dedicate a post on the numerous ways you can copy a python list and then evaluate their timing to find out which is the fastest in order to give a concise answer.

 

So, here are the different methods one after the other.

1. The built-in python list.copy method

This method is built-in for sequences and a list is a sequence. Because it is built-in, I guarantee you that like everything python built, it should be fast. I just love using this method whenever I need to copy a list. But let the timing will tell us the most efficient.

An example of how you can use it to copy a list is:

As you can see from the code names2 was independent of names after copying. So, it gives desired behavior. But I need to tell you a caveat. List.copy() does a shallow copy; it cannot recursively copy nested lists. Too bad.

2. Slicing the entire list

Yes, I said it again. When you slice the entire list, you eventually copy everything into another object. This method is so cool. The syntax is listname[:]. That’s all you need to do to copy.

Let’s try this with an example.

Yes, it is extremely convenient. It worked just as we expected, producing an independent list as output even when the original was changed. Like the first method, this method of slicing to copy python lists is shallow copy also. Too bad.

3. Using the built-in list constructor, list()

This is just like creating a list from another list. The syntax is list(originallist). It returns a new object, a list.

Here is an example.

4. Use the generic shallow copy method.

For the generic shallow copy method, you need to import the copy module: import copy. Then call the copy method of the module on the original list: copy.copy(originalist). I talked all about how to do this in the post on python shallow copy and deep copy. You can reference it for a refresher.

Here is an example.

So, as we expected. The returned list, names2, was independent of the original list, names. But as the name says, it does shallow copy. That means it cannot copy recursively. Like where we have a nested list, it cannot copy deep down but returns a reference to the nested items.

5. The generic deep copy method

This is the last and the method I use whenever I have lists in my custom classes and need to copy them. This method copies deep down, even to the nested items in a nested list. It is also a method of the copy module. You can read all about it in the link I gave above.

Let’s do an example.

I really need to do one more example with this method, to show that it copies deep down even to nested lists.

As you can see from the above nested list, when we change one of the nested items in the original list, the copy did not reflect that change to show that it was not copying by reference but copying deep down to the values.

Now that you are familiar with all the different ways to copy a list, which is the most time efficient?

First, I will have to tell you that if you have a nested list or an array, the only method you can use is the python deep copy method. That is the only method that copies everything in the nested list or array without leaving any references.

Now, for the other types of lists, that is, lists that are not nested, all the methods can be used so we will now try to find out which is more time efficient by timing their processes.

Which method is more time efficient?

To test it out, you have to run the code below and see for yourself.

You will notice that the built-in python list copy method was approximately faster than all the other methods of copying a list. That’s why I love using any function or method that is built-in specifically for any data type or data structure. But list slicing comes at a close second place. Although I would not want to use list slicing if I have a very large list.

That’s it. I hope you did enjoy this post. Watch out for other interesting posts. Just update via your email and they will surely land right in your inbox.

Happy pythoning.