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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
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Python code #14

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 1. Insertion sort: def InsertionSort (TheData): for Count in range ( 0 , len (TheData)): DataToInsert = TheData[Count] Inserted = 0 NextValue = Count - 1 while (NextValue >= 0 and Inserted != 1 ): if (DataToInsert < TheData[NextValue]): TheData[NextValue + 1 ] = TheData[NextValue] NextValue = NextValue - 1 TheData[NextValue + 1 ] = DataToInsert else : Inserted = 1 return TheData print (InsertionSort([ 3 , 2 , 1 , 7 , 5 , 9 , 0 ]))
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Python code #13

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1. 2D array bubble sort of array with 3 columns def bubble_sort_2d (arr): rows = len (arr) for i in range (rows): for j in range (rows - i - 1 ): if arr[j][ 0 ] > arr[j + 1 ][ 0 ]: temp1 = arr[j][ 0 ] arr[j][ 0 ] = arr[j + 1 ][ 0 ] arr[j + 1 ][ 0 ] = temp1 temp2 = arr[j][ 1 ] arr[j][ 1 ] = arr[j + 1 ][ 1 ] arr[j + 1 ][ 1 ] = temp2 temp3 = arr[j][ 2 ] arr[j][ 2 ] = arr[j + 1 ][ 2 ] arr[j + 1 ][ 2 ] = temp3 return arr two_d_array = [ [ 4 , 2 , 3 ], [ 1 , 5 , 6 ], [ 7 , 8 , 9 ], [ 10 , 11 , 12 ], [ 13 , 14 , 15 ], [ 16 , 17 , 18 ], [ 19 , 20 , 21 ], [ 8 , 23 , 24 ], [ 28 , 26 , 27 ], [ 21 , 29 , 30 ] ] sorted_array = bubble_sort_2d(two_d_array) for row in sorted_array: print (row) ------------------------------------------------------------------------------------------
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Popular posts from this blog

Building JavaScript Array Methods from Scratch in 2024 - Easy tutorial for beginners # 1

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  Hi guys, in this blog we will be build JavaScript array methods as a function from JavaScript basics as it is great and simple way to refine your JavaScript programming skill and make your fundamentals strong as beginner and you’ll also know various JavaScript array methods along the way, we will start from easiest to more complex ones, i have try to keep it as beginner friendly as possible.  First, i will be introducing the array method with their example input and output, then we will examine those methods, identifying which programming tools and tricks to used and in which order to arrange them. Along that process we will build pseudocode algorithm for required function and later on, i will show you flowchart version of that algorithm, the important tip that i can give to you all, to get most out of this blog, is to first try to build it by yourself then come to this blog. 1. Array.isArray() :  So lets, start with simple one Array.isArray() method. The Array.isArray() method
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Python Code # 12

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  def binary_search (arr, target): """ Perform binary search on the given sorted list to find the target value. Parameters: - arr (list): The sorted list to be searched. - target: The value to be searched for. Returns: - int: Index of the target value if found, otherwise -1. """ low, high = 0 , len (arr) - 1 while low <= high: mid = (low + high) // 2 # Calculate mid index if arr[mid] == target: return mid # Target found, return its index elif arr[mid] < target: low = mid + 1 # Adjust the search range to the right half else : high = mid - 1 # Adjust the search range to the left half return - 1 # Target not found # Example usage: my_sorted_list = [ 2 , 5 , 8 , 12 , 16 , 23 , 38 , 45 , 50 ] target_value = 16 result = binary_search(my_sorted_list, target_value) if result != - 1 : print ( f'Target { target_value } found at index {
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A better way to learn programming.

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In this post, I will be talking about two methods to learn how to program. The first method (common method) is a step-by-step tutorial approach like following a tutorial. It goes something like this: "Step one, create this component." The tutorial then provides you with detailed instructions on how to create that specific component. "Step two, do this," and you follow the next set of instructions. And when instructions finish you study and repeat the same instruction. This method gives you precise steps to follow. However, the issue here is that the person who created these steps went through a trial-and-error process themselves. They tried something, it didn't work, so they tried something else. They repeated this process until they found a solution that worked. What you're doing by following these steps is simply replicating their final result, which doesn't foster deep learning or problem-solving skills. Second method: The better way to learn progra
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