5 Best Ways to Create a List in Python Using a For Loop

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πŸ’‘ Problem Formulation: In Python, how do you transform a sequence or range of elements into a list using a for loop? For instance, you might want to take a range of numbers from 1 to 10, or a list of strings and create a new list where each item has been processed or filtered in some way. The desired output would be a list that contains the processed items.

Method 1: Using a For Loop with the append() Method

This traditional approach involves initializing an empty list and then appending each processed item to the list within a for loop. It’s simple and explicit, making it great for beginners to understand what’s going on.

Here’s an example:

my_list = []
for i in range(1, 11):
    my_list.append(i**2)

The output of this code snippet will be the list: [1, 4, 9, 16, 25, 36, 49, 64, 81, 100].

This code snippet creates a list called my_list, then iterates over a range of numbers from 1 to 10, squares each number, and appends the result to the list.

Method 2: List Comprehension

List comprehension is a concise way to create lists. It consists of brackets containing an expression followed by a for clause, then zero or more for or if clauses. It’s highly readable and often more efficient than using a plain for loop.

Here’s an example:

my_list = [i**2 for i in range(1, 11)]

The output of this code snippet will be the same list: [1, 4, 9, 16, 25, 36, 49, 64, 81, 100].

The list comprehension iterates over the range, squares each number and collects the results directly into a new list.

Method 3: Using the map() Function

Using Python’s built-in map() function allows you to apply a function to each item in an iterable and convert the result into a list. This can be particularly useful when using pre-defined functions.

Here’s an example:

my_list = list(map(lambda x: x**2, range(1, 11)))

The output will once again be: [1, 4, 9, 16, 25, 36, 49, 64, 81, 100].

This code passes a lambda function that squares a number to the map() function along with a range, then converts the map object to a list.

Method 4: Using the filter() Function

Similar to map(), the filter() function allows you to filter items in an iterable. When combined with a list constructor, it builds a list containing only items where the filter function returns True.

Here’s an example:

my_list = list(filter(lambda x: x % 2 == 0, range(1, 11)))

And the output of this code snippet will be: [2, 4, 6, 8, 10].

This snippet uses filter() to retain only even numbers from a range and then converts the result to a list.

Bonus One-Liner Method 5: Using a Generator Expression with list()

Generator expressions are similar to list comprehensions but with parentheses instead of brackets. They are more memory efficient and can also be directly converted into a list.

Here’s an example:

my_list = list(i**2 for i in range(1, 11))

The output will be: [1, 4, 9, 16, 25, 36, 49, 64, 81, 100].

This one-liner code uses a generator expression to square each number in the range yielding a generator, which is then converted into a list.

Summary/Discussion

  • Method 1: Using a For Loop with append(). Strengths: Explicit and easy to understand. Weaknesses: Can be verbose and less efficient than other methods.
  • Method 2: List Comprehension. Strengths: More concise and often faster than a traditional for loop. Weaknesses: Can be less readable when complex.
  • Method 3: Using the map() Function. Strengths: Clean syntax for applying a function to each item. Weaknesses: Requires converting the map object to a list, and the need for lambda functions can be less readable.
  • Method 4: Using the filter() Function. Strengths: Good for conditional inclusion of items. Weaknesses: Requires an additional function to determine inclusion.
  • Bonus Method 5: Using a Generator Expression. Strengths: Memory efficient and can be written as a one-liner. Weaknesses: Slightly less readable and known among beginners.