[Tut] List Changes After Assignment — How to Clone or Copy It?

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List Changes After Assignment — How to Clone or Copy It?

Problem: If you assign a list object to a new variable using

Code:

new_list = old_list

, any modification to

Code:

new_list

changes

Code:

old_list

. What’s the reason for this and how can you clone or copy the listto prevent this problem?

Example: Let’s consider the following example.

Code:

old_list = ['Alice', 'Bob', 'Carl'] new_list = old_list new_list.append(42) print(old_list) # ['Alice', 'Bob', 'Carl', 42]

Appending an element to the

Code:

new_list

also modifies the original list

Code:

old_list

. Thus,

Code:

old_list

has now four elements—even though you didn’t change it directly.

Explanation

This problem of simultaneously modifying “two” lists arises because you don’t have two lists but only a single one.

In Python, everything is an object. You create a new list object

Code:

['Alice', 'Bob', 'Carl']

that resides in your machine’s memory. Both variable names

Code:

new_list

and

Code:

old_list

point to the same object in memory—if you modify one, you also modify the other!



The following interactive tool visualizes the memory used by the Python interpreter when executing this particular code snippet:

https://pythontutor.com/iframe-embed.htm...nces=false

Exercise: Visualize how the problem arises by clicking “Next”.

Do you understand the source of the problem? Great, let’s dive into the solutions starting with a short overview!

Solution Overview

You can see all three solutions discussed in this tutorial in our interactive Python shell:

https://repl.it/@finxter/FaintCheapButton?lite=true

Exercise: Change the original list. Do all three methods still produce the same output?

Next, you’ll learn about each method in greater detail!

Method 1: Slicing

The easiest way to create a shallow copy of a Python list is via slicing:

Code:

# Method 1: Slicing old_list = ['Alice', 'Bob', 'Carl'] new_list = old_list[:] new_list.append(42) print(new_list) # ['Alice', 'Bob', 'Carl']

The slicing operation

Code:

old_list[:]

creates a new list, so the variables

Code:

new_list

and

Code:

old_list

now point to different objects in memory. If you change one, the other doesn’t change.

This is the way with the least amount of characters and many Python coders would consider this the most Pythonic one. If you want to learn more about slicing, watch the following video and dive into the detailed blog tutorial.

Related Tutorial: Introduction to Slicing in Python



Method 2: Copy

An alternative is to use the

Code:

list.copy()

method that creates a shallow copy of the list.

Code:

# Method 2: Copy old_list = ['Alice', 'Bob', 'Carl'] new_list = old_list.copy() new_list.append(42) print(old_list) # ['Alice', 'Bob', 'Carl']

The

Code:

list.copy()

method copies all

Code:

list

elements into a new list. The new list is the return value of the method. It’s a shallow copy—you copy only the object references to the list elements and not the objects themselves.

The result is the same as the slicing method: you have two variables pointing to two different list objects in memory.

You can learn more about the

Code:

list.copy()

method in my detailed blog tutorial and the following video:

Related Tutorial: Python

Code:

list.copy()

[Ultimate Guide]



Method 3: List Comprehension

A third way to solve the problem of two lists pointing to the same object in memory is the list comprehension way to create new lists.

Code:

# Method 3: List Comprehension old_list = ['Alice', 'Bob', 'Carl'] new_list = [x for x in old_list] new_list.append(42) print(old_list) # ['Alice', 'Bob', 'Carl']

List comprehension is a compact way of creating lists. The simple formula is

Code:

[expression + context]

.

• Expression: What to do with each list element?
  
  
• Context: What elements to select? The context consists of an arbitrary number of
  Code:

  for
  and
  Code:

  if
  statements.
  

You can watch the tutorial video and read over the related blog article to learn more about it!



Related Tutorial: An Introduction to List Comprehension

Where to Go From Here?

Enough theory, let’s get some practice!

To become successful in coding, you need to get out there and solve real problems for real people. That’s how you can become a six-figure earner easily. And that’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?

Practice projects is how you sharpen your saw in coding!

Do you want to become a code master by focusing on practical code projects that actually earn you money and solve problems for people?

Then become a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.

Join my free webinar “How to Build Your High-Income Skill Python” and watch how I grew my coding business online and how you can, too—from the comfort of your own home.

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