Lambda vs. List Comprehension: Which is Best for Element-wise Differences in Python Lists?

Performing Element-wise Difference in Lists: Lambda vs. List Comprehension

Finding differences between adjacent elements in a list is a common operation in programming. In Python, there are several ways to accomplish this, including using lambda expressions or list comprehensions.

Lambda Expression:

A lambda expression can be used to create a function on the fly, which can then be used to operate on each element in the list. For example:

<code class="python">t = [1, 3, 6]
differences = list(map(lambda i, j: j - i, t[:-1], t[1:]))</code>

In this case, the lambda function lambda i, j: j - i subtracts the (i)-th element from its (i 1)-th element. The map function then applies this function to each pair of adjacent elements in the list.

List Comprehension:

List comprehensions provide a concise way to create a new list based on an existing list. The following list comprehension performs the same operation as the lambda expression above:

<code class="python">differences = [j - i for i, j in zip(t[:-1], t[1:])]</code>

The zip function pairs up the adjacent elements in the list, and the list comprehension iterates over these pairs. For each pair (i, j), it calculates the difference j - i.

Comparison:

Both approaches have their advantages and disadvantages. Lambda expressions are more versatile and can be used in a wider range of situations. However, list comprehensions are often more concise and easier to read.

Example:

Given the list t = [1, 3, 6], both the lambda expression and the list comprehension will produce the following output:

[2, 3]

This is because the first difference (3 - 1) is 2, and the second difference (6 - 3) is 3.

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