Eliminating Loop from Python Code

In Python, loops like for and while are very common for repeating tasks. But sometimes, writing loops makes the code longer, slower, or harder to read. In many cases, you can eliminate loops by using Python’s built-in features, which are faster and cleaner.

Eliminate Loops with List Comprehension

A List comprehensions are another way to generate lists without the need for explicit loop structures.

# Without list comprehension
a = []
for i in range(8):
    a.append(i**2)

# With list comprehension
b = [i**2 for i in range(8)]

print("Using Loop: ", a)
print("Using List Comprehension: ", b)

Using Loop:  [0, 1, 4, 9, 16, 25, 36, 49]
Using List Comprehension:  [0, 1, 4, 9, 16, 25, 36, 49]

Explanation:

• n the first part, a normal for loop is used. It starts with an empty list a and keeps appending each squared number (i**2) one by one.
• In the second part, a list comprehension does the same thing but in a single line: it directly creates a list of squares of numbers from 0 to 7

Eliminate Loops with Itertools

The Python itertools modules are a collection of tools for handling iterators. They can eliminate the need for complex loops and make code more efficient and cleaner.

import itertools

# Flattening a list of lists using a loop
a = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
b = []
for sublist in a:
    for i in sublist:
        b.append(i)
print(b)

# Flattening a list of lists using itertools
b = list(itertools.chain(*a))
print(b)

[1, 2, 3, 4, 5, 6, 7, 8, 9]
[1, 2, 3, 4, 5, 6, 7, 8, 9]

Remove Loops with Pandas

You can eliminate loops while working with numerical data, and libraries in Python such as NumPy and Pandas. These Libraries leverage a technique called Vectorization. It generally performs operations on the entire array of data.

Let's consider a simple example in which we need to square each number in a list and the range is given from 1 to 6.

Example: By using a for loop

numbers = list(range(1, 6))
squares = []
for number in numbers:
    squares.append(number ** 2)
print(squares)

[1, 4, 9, 16, 25]

Example: By using NumPy

import numpy as np 
numbers = np.arange(1,6)
squares = numbers ** 2
print(squares)

[ 1  4  9 16 25]

Eliminate Loops with Built-in Functions: map(), reduce, and filter()

Python's built-in function "map()", "reduce()", and "filter()" provides powerful, functional programming alternatives to loops.

"map()": It applies a function to all items in an input list.

numbers = list(range(1, 6))
squares = list(map(lambda x: x ** 2, numbers))
print(squares)

[1, 4, 9, 16, 25]

"reduce()": It applies a function of two arguments cumulatively to the elements of an iterable.

from functools import reduce
numbers = list(range(1,6))
product= reduce(lambda x,y: x*y, numbers)
print(product)

120

"filter()": It creates a list of elements for which the function returns True.

numbers = list(range(1, 6))
even_numbers = list(filter(lambda x: x % 2 == 0, numbers))
print(even_numbers)

[2, 4]

Remove Loops with Generator Expression 

The Generators are a main type of Python function that allows you to create an iterable object, but they generate the value according to the need, which can save memory while dealing with large data sets.

# Using a for loop to create a list of squares
squares = []
for n in range(50000):
    squares.append(n ** 2)
print(squares)

# Using a generator expression
# Reduced to 10 for brevity
squares_gen = (n ** 2 for n in range(50000))  
for square in squares_gen:
    print(square, end=' ')
 

Output:

Using for loop: [0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521, 1600,...]

Using generator expression: 0 1 4 9 16 25 36 49 64 81 100 121 144 169 196 225 256 289 324 361 400 441 484 529 576 625 676 729 784 841 900 961 1024 1089 1156 1225 1296 1369 1444 1521 1600.........