[Tut] list.clear() vs New List — Why Clearing a List Rather Than Creating a New One?

list.clear() vs New List — Why Clearing a List Rather Than Creating a New One?

Problem: You’ve just learned about the list.clear() method in Python. You wonder, what’s its purpose? Why not creating a new list and overwriting the variable instead of clearing an existing list?

Example: Say, you have the following list.

lst = ['Alice', 'Bob', 'Carl']

If you clear the list, it becomes empty:

lst.clear()

print(lst)

# []

However, you could have accomplished the same thing by just assigning a new empty list to the variable lst:

lst = ['Alice', 'Bob', 'Carl']

lst = []

print(lst)

# []

The output is the same. Why does the list.clear() method exist in the first place?

If you go through the following interactive memory visualizer, you’ll see that both variants lead to different results if you have multiple variables pointing to the list object:

In the second example, the variable lst_2 still points to a non-empty list object!

So, there are at least two reasons why the list.clear() method can be superior to creating a new list:

• Release Memory: If you have a large list that fills your memory—such as a huge data set or a large file read via readlines()—and you don’t need it anymore, you can immediately release the memory with list.clear(). Especially in interactive mode, Python doesn’t know which variable you still need – so it must keep all variables till session end. But if you call list.clear(), it can release the memory for other processing tasks.
• Clear Multiple List Variables: Multiple variables may refer to the same list object. If you want to reflect that the list is now empty, you can either call list.clear() on one variable and all other variables will see it, or you must call var1 = [], var2 = [], ..., varn = [] for all variables. This can be a pain if you have many variables.

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