Visualizing Bubble Sort using Tkinter in Python
In this article, we will use the Python GUI Library Tkinter to visualize the Bubble Sort algorithm.
- Tkinter is a very easy to use and beginner-friendly GUI library that can be used to visualize the sorting algorithms.
- Here Bubble Sort Algorithm is visualized which works by repeatedly swapping the adjacent elements/values if they are in the wrong order until the whole array is sorted.
- The idea is that : if arr[i] > arr[i+1] then swap them.
- In the first iteration, N-1 items have to be scanned and the largest element moves to its right position. In the second iteration, the second largest item will move to its correct position, and after the third iteration (stopping at item N-3) the third largest will be in place. Therefore, to place all the elements in the correct order the above operation is performed N-1 times. This algorithm has Time Complexity = O(N2).
Procedure:
- A list of random values within a specified range is generated as bars.
- Different colors (red and green) are used to show the sorting process.
- A suitable “Speed” range bar is created for the ease of the user to visualize.
- “Generate” and “Start” buttons are created separately for the creation of data bars and initiation of the sorting process.
Extension Code for Bubble Sort :
This is the extension code for the bubble sort algorithm which is imported in the main Tkinter visualizer code to implement the bubble sort algorithm and return the sorted result.
Python3
# Extension Bubble Sort Code # importing time module import time # function to implement bubble sort by passing # the following parameters: # data is passed for the set of unsorted data values # drawdata is used to generate the data bars # timer is for the speed range def bubble(data, drawData, timer): n = len (data) for i in range (n): for j in range ( 0 , n - i - 1 ): if data[j] > data[j + 1 ]: data[j], data[j + 1 ] = data[j + 1 ], data[j] # if swapped then color becomes Green else stays Red drawData(data, [ 'Green' if x = = j + 1 else 'Red' for x in range ( len (data))]) time.sleep(timer) # sorted elements generated with Green color drawData(data, [ 'Green' for x in range ( len (data))]) |
Code for Tkinter :
In this code, we are generating the data values as bars of different lengths and a particular color. The basic layout is designed in a Tkinter ‘Frame’ and the portion when the bars are generated and the algorithm is visualized is designed in a Tkinter ‘Canvas’.
The code essentially has the following components:
- Mainframe: a Tkinter frame to arrange all the necessary components(labels, buttons, speed bar, etc.) in an organized manner
- Canvas: A Tkinter canvas used as the space where the generated data bars are drawn and the sorting process is visualized
- generate(): Method to generate the data values by accepting a range and then passing that as a parameter to the drawData() function
- drawData(): Method to generate bars to normalized data values(within the given range) of a particular color on the canvas
- start_algorithm(): This function is called when the “START” button is pressed. It initiates the sorting process by calling the bubble() function from the Bubble Sort Extension Code.
Python3
# code for Bubble Sort Visualizer using Python and Tkinter from tkinter import * from tkinter import ttk import random from bub_srt import bubble # initialising root class for Tkinter root = Tk() root.title( "Bubble Sort Visualizer" ) # maximum window size root.maxsize( 900 , 600 ) root.config(bg = "Black" ) select_alg = StringVar() data = [] # function to generate the data values by accepting a given range def generate(): global data # minval : minimum value of the range minval = int (minEntry.get()) # maxval : maximum value of the range maxval = int (maxEntry.get()) # sizeval : number of data values/bars to be generated sizeval = int (sizeEntry.get()) # creating a blank data list which will be further # filled with random data values # within the entered range data = [] for _ in range (sizeval): data.append(random.randrange(minval, maxval + 1 )) drawData(data, [ 'Red' for x in range ( len (data))]) # function to create the data bars by creating a canvas in Tkinter def drawData(data, colorlist): canvas.delete( "all" ) can_height = 380 can_width = 550 x_width = can_width / ( len (data) + 1 ) offset = 30 spacing = 10 # normalizing data for rescaling real-valued numeric data within the # given range normalized_data = [i / max (data) for i in data] for i, height in enumerate (normalized_data): # top left corner x0 = i * x_width + offset + spacing y0 = can_height - height * 340 # bottom right corner x1 = ((i + 1 ) * x_width) + offset y1 = can_height # data bars are generated as Red colored vertical rectangles canvas.create_rectangle(x0, y0, x1, y1, fill = colorlist[i]) canvas.create_text(x0 + 2 , y0, anchor = SE, text = str (data[i])) root.update_idletasks() # function to initiate the sorting process by # calling the extension code def start_algorithm(): global data bubble(data, drawData, speedbar.get()) # creating main user interface frame and # basic layout by creating a frame Mainframe = Frame(root, width = 600 , height = 200 , bg = "Grey" ) Mainframe.grid(row = 0 , column = 0 , padx = 10 , pady = 5 ) canvas = Canvas(root, width = 600 , height = 380 , bg = "Grey" ) canvas.grid(row = 1 , column = 0 , padx = 10 , pady = 5 ) # creating user interface area in grid manner # first row components Label(Mainframe, text = "ALGORITHM" , bg = 'Grey' ).grid( row = 0 , column = 0 , padx = 5 , pady = 5 , sticky = W) # algorithm menu for showing the name of the sorting algorithm algmenu = ttk.Combobox( Mainframe, textvariable = select_alg, values = [ "Bubble Sort" ]) algmenu.grid(row = 0 , column = 1 , padx = 5 , pady = 5 ) algmenu.current( 0 ) # creating Start Button to start the sorting visualization process Button(Mainframe, text = "START" , bg = "Blue" , command = start_algorithm).grid( row = 1 , column = 3 , padx = 5 , pady = 5 ) # creating Speed Bar using scale in Tkinter speedbar = Scale(Mainframe, from_ = 0.10 , to = 2.0 , length = 100 , digits = 2 , resolution = 0.2 , orient = HORIZONTAL, label = "Select Speed" ) speedbar.grid(row = 0 , column = 2 , padx = 5 , pady = 5 ) # second row components # sizeEntry : scale to select the size/number of data bars sizeEntry = Scale(Mainframe, from_ = 3 , to = 60 , resolution = 1 , orient = HORIZONTAL, label = "Size" ) sizeEntry.grid(row = 1 , column = 0 , padx = 5 , pady = 5 ) # minEntry : scale to select the minimum value of data bars minEntry = Scale(Mainframe, from_ = 0 , to = 10 , resolution = 1 , orient = HORIZONTAL, label = "Minimum Value" ) minEntry.grid(row = 1 , column = 1 , padx = 5 , pady = 5 ) # maxEntry : scale to select the maximum value of data bars maxEntry = Scale(Mainframe, from_ = 10 , to = 100 , resolution = 1 , orient = HORIZONTAL, label = "Maximum Value" ) maxEntry.grid(row = 1 , column = 2 , padx = 5 , pady = 5 ) # creating generate button Button(Mainframe, text = "Generate" , bg = "Red" , command = generate).grid( row = 0 , column = 3 , padx = 5 , pady = 5 ) # to stop automatic window termination root.mainloop() |
Output :
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