Question

Rewrite the generation of the nested list q, $$ \mathrm{q}=[r * * 2 \text { for } \mathrm{r} \text { in }[10 * * \mathrm{i} \text { for } \mathrm{i} \text { in } \mathrm{range}(5)]] $$ by using standard for loops instead of list comprehensions. Name of program file: listcomp2for.py.

Short answer

Use two nested loops to generate the list: the outer loop squares numbers from an inner loop that generates \([10^0, 10^1, 10^2, 10^3, 10^4]\).

Step-by-step solution

Understanding the List Comprehension

The list comprehension given in the problem creates a nested list. The inner list comprehension generates a list of numbers calculated by raising 10 to the power of numbers from 0 to 4. This generates the list \([10^0, 10^1, 10^2, 10^3, 10^4]\). The outer list comprehension squares each of these numbers, resulting in the final list \([1, 100, 10000, 1000000, 100000000]\).

Writing the Inner Loop

Translate the inner list comprehension into a standard for loop. This loop will iterate over the range of numbers from 0 to 4 and calculate \(10^i\) for each number \(i\).```pythoninner_list = []for i in range(5): inner_list.append(10 ** i)```This code snippet replaces the inner list comprehension \([10 ** i \text{ for } i \text{ in range}(5)]\).

Writing the Outer Loop

Translate the outer list comprehension into a standard for loop. This loop will iterate over the list that was generated in Step 2 and calculate the square of each number.```pythonq = []for r in inner_list: q.append(r ** 2)```This code snippet replaces the outer list comprehension \([r ** 2 \text{ for } r \text{ in } inner_list]\).

Combine Both Loops into One Program

Now, combine both loops into one Python script file named `listcomp2for.py`. Ensure that the variable names and logic are the same as when we used comprehensions. ```python # listcomp2for.py inner_list = [] for i in range(5): inner_list.append(10 ** i) q = [] for r in inner_list: q.append(r ** 2) print(q) ``` This script replicates the logic of the nested list comprehension using two "for" loops, and outputs the same list.

Key concepts

Python Loops

Loops in Python are essential constructs that allow you to execute a block of code repeatedly. The most common loops used in Python are `for` and `while` loops. In this exercise, we focus on `for` loops.

Here are some key points about `for` loops:

• A `for` loop iterates over a sequence, such as a list, tuple, or string.
• Each iteration passes a single element from the sequence into the loop block.
• Looping helps to automate repetitive tasks, like processing each item in a dataset.

One of the main advantages of using `for` loops over manual iteration is code readability and efficiency. You tell Python exactly how many iterations you want by specifying a sequence, like `range(5)`, which produces numbers from 0 to 4.

In our exercise, we use `for` loops to construct and manipulate lists, demonstrating how loops can replace list comprehensions with explicit iteration.

Python Script

A Python script is a file that contains Python code executed by the Python interpreter. Scripts are used to automate tasks and run programs in a structured manner. In this exercise, our Python script, `listcomp2for.py`, combines two `for` loops into one cohesive program.

Features of creating a Python script include:

• Scripts can be created using any text editor and saved with a `.py` extension.
• You can execute a script by calling Python on the command line with the script filename, like `python listcomp2for.py`.
• Scripts can import libraries and modules to use their functions and variables.

By structuring the code into a script, we ensure reusability and clarity. Any user can simply run the script to perform the same operations, allowing them to generate the list repeatedly without typing commands manually each time.

Nested Lists

A nested list is a list that contains other lists as its elements. This structure is useful for storing complex data arrangements, such as matrices or multi-dimensional arrays.

Understanding how to work with nested lists:

• Like regular lists, you access a nested list using indexes. However, you need multiple indexes for nested elements: `nested_list[0][1]` accesses the second item of the first sublist.
• Nested lists provide a way to organize data hierarchically, which is beneficial for storing or representing structured information.
• In our exercise, the nested list comprehension constructs an inner and outer list. The inner list uses exponentiation to calculate powers of 10, while the outer list further processes these numbers by squaring them.

Nested lists add an additional layer of complexity but offer powerful data representation capabilities. Thus, understanding how to iterate over and manipulate nested lists is a crucial Python skill.

Exponentiation in Python

Exponentiation is the mathematical operation of raising one number (the base) to the power of another number (the exponent). In Python, the ** operator is used for exponentiation.

Several important features of exponentiation in Python include:

• The operator syntax is `base ** exponent`. For example, `10 ** 2` computes 100.
• It is capable of handling both integer and floating-point numbers.
• Exponentiation can be embedded within loops and comprehensions for calculations like powering elements in a list.

In this exercise, we use the `**` operator in both the inner list creation and outer list processing. This illustrates its versatility and power in performing bulk calculations easily.

Understanding exponentiation is valuable when dealing with growth calculations, algorithm complexity, or any process modeling involving repeated multiplication.