On canvas widget we can draw figures like lines,circle,rectangles etc. We can also draw text, images and other widgets on canvas. To draw shapes in the canvas, use the create methods to add new items. Let's create a canvas and draw some shapes on it.
1. rectangle: For creating rectangles we have the method create_rectangle(coords, options). Coords is again defined by two points, but this time the first one is the top left point and the bottom right point of the rectangle.
See the program below:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 250, height = 250, bg = 'green')
canvas.create_rectangle(202,100,30,150, fill = 'red')
canvas.pack()
mainloop()
We first created a canvas with a green background that is 250* 250 pixels in size as shown in the following code:
canvas = Canvas (root, width = 250, height = 250, bg = 'green')
Next we draw a rectangle filled with red color as shown by the following code:
canvas.create_rectangle(202,100,30,150, fill = 'red')
The upper left of the rectangle is at (202, 100), and the lower right is at (30, 150).
![](data:image/png;base64,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)
If were to leave off bg = 'green and 'fill='red' fields , the result would be a canvas with white background with a rectangle having black outline as shown in the figure below:
![](data:image/png;base64,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)
2. Lines: The method create_line(coords, options) is used to draw a straight line. The coordinates "coords" are given as four integer numbers: x1, y1, x2, y2 This means that the line goes from the point (x1, y1) to the point (x2, y2) After these coordinates follows a comma separated list of additional parameters, which may be empty.
3. Ovals: We can create an oval on a canvas c with the following method:
create_oval ( x0, y0, x1, y1, option, ... )
We can draw lines and ovals in the similar way as we drew rectangle. The following program draws ovals and lines:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 250, height = 250)
canvas.create_rectangle(202,100,30,150)
canvas.create_oval(202,100,30,150, fill = 'green')
canvas.create_line(202,100,30,150, fill = 'red')
canvas.pack()
mainloop()
The output of the program is shown below:
![](data:image/png;base64,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)
4. Polygons: To draw a polygon we use create_polygon method() and provide at least three coordinate points in the create_polygon method:
create_polygon(x0,y0, x1,y1, x2,y2, ...)
The following program draws a triangle:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 220, height = 200)
canvas.create_polygon(0,0,200,100,0,200, outline="#476042",fill='yellow', width=3)
canvas.pack()
mainloop()
The output of the program is shown below:
![](data:image/png;base64,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)
5. Images: The Canvas method create_image(x0,y0, options ...) is used to draw an image on a canvas. create_image doesn't accept an image directly. It uses an object which is created by the PhotoImage() method. The PhotoImage class can only read GIF and PGM/PPM images from files. See the program below:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 220, height = 200)
canvas.pack()
img = PhotoImage(file="covri.gif")
canvas.create_image(20,20, anchor=NW, image=img)
mainloop()
The output of the program is shown below:
![](data:image/png;base64,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)
6. Bitmaps: The method create_bitmap() can be be used to include a bitmap on a canvas. The following bitmaps are available on all platforms:
"error", "gray75", "gray50", "gray25", "gray12", "hourglass", "info", "questhead", "question", "warning"
The following program puts all of these bitmaps on a canvas:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 300, height = 100)
canvas.pack()
bitmaps = ["error", "gray75", "gray50", "gray25", "gray12", "hourglass", "info", "questhead", "question", "warning"]
nsteps = len(bitmaps)
step_x = int(300 / nsteps)
for i in range(0, nsteps):
canvas.create_bitmap((i+1)*step_x - step_x/2,50, bitmap=bitmaps[i])
mainloop()
The output of the program is shown below:
Here I am ending today's post. Make some programs on your own as GUI needs a lot practice. Till we meet next keep practicing and learning Python as Python is easy to learn!
1. rectangle: For creating rectangles we have the method create_rectangle(coords, options). Coords is again defined by two points, but this time the first one is the top left point and the bottom right point of the rectangle.
See the program below:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 250, height = 250, bg = 'green')
canvas.create_rectangle(202,100,30,150, fill = 'red')
canvas.pack()
mainloop()
We first created a canvas with a green background that is 250* 250 pixels in size as shown in the following code:
canvas = Canvas (root, width = 250, height = 250, bg = 'green')
Next we draw a rectangle filled with red color as shown by the following code:
canvas.create_rectangle(202,100,30,150, fill = 'red')
The upper left of the rectangle is at (202, 100), and the lower right is at (30, 150).
If were to leave off bg = 'green and 'fill='red' fields , the result would be a canvas with white background with a rectangle having black outline as shown in the figure below:
2. Lines: The method create_line(coords, options) is used to draw a straight line. The coordinates "coords" are given as four integer numbers: x1, y1, x2, y2 This means that the line goes from the point (x1, y1) to the point (x2, y2) After these coordinates follows a comma separated list of additional parameters, which may be empty.
3. Ovals: We can create an oval on a canvas c with the following method:
create_oval ( x0, y0, x1, y1, option, ... )
We can draw lines and ovals in the similar way as we drew rectangle. The following program draws ovals and lines:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 250, height = 250)
canvas.create_rectangle(202,100,30,150)
canvas.create_oval(202,100,30,150, fill = 'green')
canvas.create_line(202,100,30,150, fill = 'red')
canvas.pack()
mainloop()
The output of the program is shown below:
4. Polygons: To draw a polygon we use create_polygon method() and provide at least three coordinate points in the create_polygon method:
create_polygon(x0,y0, x1,y1, x2,y2, ...)
The following program draws a triangle:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 220, height = 200)
canvas.create_polygon(0,0,200,100,0,200, outline="#476042",fill='yellow', width=3)
canvas.pack()
mainloop()
5. Images: The Canvas method create_image(x0,y0, options ...) is used to draw an image on a canvas. create_image doesn't accept an image directly. It uses an object which is created by the PhotoImage() method. The PhotoImage class can only read GIF and PGM/PPM images from files. See the program below:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 220, height = 200)
canvas.pack()
img = PhotoImage(file="covri.gif")
canvas.create_image(20,20, anchor=NW, image=img)
mainloop()
6. Bitmaps: The method create_bitmap() can be be used to include a bitmap on a canvas. The following bitmaps are available on all platforms:
"error", "gray75", "gray50", "gray25", "gray12", "hourglass", "info", "questhead", "question", "warning"
The following program puts all of these bitmaps on a canvas:
from tkinter import *
root = Tk()
canvas = Canvas (root,width = 300, height = 100)
canvas.pack()
bitmaps = ["error", "gray75", "gray50", "gray25", "gray12", "hourglass", "info", "questhead", "question", "warning"]
nsteps = len(bitmaps)
step_x = int(300 / nsteps)
for i in range(0, nsteps):
canvas.create_bitmap((i+1)*step_x - step_x/2,50, bitmap=bitmaps[i])
mainloop()
The output of the program is shown below:
Here I am ending today's post. Make some programs on your own as GUI needs a lot practice. Till we meet next keep practicing and learning Python as Python is easy to learn!
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