Underrated step for logic building in programming.

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Logic building is a crucial and complex skill in programming. In essence, it is ability to come-up with solution of coding problem and write precise instructions ( or code) that a computer can execute autonomously. This skill requires aligning your thought process with computer and its capabilities. And running through code some-what abstractly to know and predict the behavior of code before it is executed. To be able to do this, one essential step that many beginner programmers overlook is performing dry runs. Understanding Dry Runs The concept of a dry run in programming is straightforward: can you mentally execute your code and predict its output without actually running it on a computer? While this seems simple, it is a challenging task. Typically, we are taught to write code, run it, and observe the output. This cycle is essential because code needs to run to be validated. However, if you rely solely on running your code to understand its behavior, you may struggle with building

Python code for beginner's # 9

 def find_length_of_number(number):

    # Convert the number to a string
num_str = str(number)

# Initialize a counter for the length
length = 0

# Iterate through each character in the string
for digit in num_str:
length += 1

return length

# Example usage
user_input = int(input("Enter a number: "))
length_of_number = find_length_of_number(user_input)
print(f"The length of the number {user_input} is: {length_of_number}")
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def factorial(n):
# Base case: factorial of 0 or 1 is 1
if n == 0 or n == 1:
return 1
else:
# Recursive case: n! = n * (n-1)!
return n * factorial(n-1)

# Example usage:
number = int(input('enter num; '))
result = factorial(number)
print(f"The factorial of {number} is: {result}")

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