UPDATED rat_in_maze.py#9148

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Merged
cclauss merged 16 commits into from
Oct 4, 2023
Merged

UPDATED rat_in_maze.py #9148

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9450821
UPDATED rat_in_maze.py
Muhammadummerr Sep 30, 2023
9a1d65f
Update reddit.py in Webprogramming b/c it was causing error in pre-co…
Muhammadummerr Sep 30, 2023
741bb72
Merge branch 'TheAlgorithms:master' into new_branch
Muhammadummerr Oct 1, 2023
1b2a9e6
UPDATED rat_in_maze.py
Muhammadummerr Oct 1, 2023
726bc5c
Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…
Muhammadummerr Oct 1, 2023
d9e1956
Merge branch 'TheAlgorithms:master' into new_branch
Muhammadummerr Oct 4, 2023
49e6dee
fixed return type to only maze,otherwise raise valueError.
Muhammadummerr Oct 4, 2023
b59a85d
Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…
Muhammadummerr Oct 4, 2023
cedaf35
fixed whitespaces error,improved matrix visual.
Muhammadummerr Oct 4, 2023
775d6cd
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Oct 4, 2023
c740da3
updated.
Muhammadummerr Oct 4, 2023
591c098
Try
Muhammadummerr Oct 4, 2023
9c89c79
Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…
Muhammadummerr Oct 4, 2023
1539b6f
updated
Muhammadummerr Oct 4, 2023
e169d07
updated
Muhammadummerr Oct 4, 2023
8013870
Apply suggestions from code review
cclauss Oct 4, 2023
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181 changes: 130 additions & 51 deletions backtracking/rat_in_maze.py
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Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
maze: list[list[int]],
source_row: int,
source_column: int,
destination_row: int,
destination_column: int,
) -> list[list[int]]:
"""
This method solves the "rat in maze" problem.
In this problem we have some n by n matrix, a start point and an end point.
We want to go from the start to the end. In this matrix zeroes represent walls
and ones paths we can use.
Parameters :
maze(2D matrix) : maze
- maze: A two dimensional matrix of zeros and ones.
- source_row: The row index of the starting point.
- source_column: The column index of the starting point.
- destination_row: The row index of the destination point.
- destination_column: The column index of the destination point.
Returns:
Return: True if the maze has a solution or False if it does not.
- solution: A 2D matrix representing the solution path if it exists.
Raises:
- ValueError: If no solution exists or if the source or
destination coordinates are invalid.
Description:
This method navigates through a maze represented as an n by n matrix,
starting from a specified source cell and
aiming to reach a destination cell.
The maze consists of walls (1s) and open paths (0s).
By providing custom row and column values, the source and destination
cells can be adjusted.
>>> maze = [[0, 1, 0, 1, 1],
... [0, 0, 0, 0, 0],
... [1, 0, 1, 0, 1],
... [0, 0, 1, 0, 0],
... [1, 0, 0, 1, 0]]
>>> solve_maze(maze)
[1, 0, 0, 0, 0]
[1, 1, 1, 1, 0]
[0, 0, 0, 1, 0]
[0, 0, 0, 1, 1]
[0, 0, 0, 0, 1]
True
>>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
[[0, 1, 1, 1, 1],
[0, 0, 0, 0, 1],
[1, 1, 1, 0, 1],
[1, 1, 1, 0, 0],
[1, 1, 1, 1, 0]]

Note:
In the output maze, the zeros (0s) represent one of the possible
paths from the source to the destination.

>>> maze = [[0, 1, 0, 1, 1],
... [0, 0, 0, 0, 0],
... [0, 0, 0, 0, 1],
... [0, 0, 0, 0, 0],
... [0, 0, 0, 0, 0]]
>>> solve_maze(maze)
[1, 0, 0, 0, 0]
[1, 0, 0, 0, 0]
[1, 0, 0, 0, 0]
[1, 0, 0, 0, 0]
[1, 1, 1, 1, 1]
True
>>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
[[0, 1, 1, 1, 1],
[0, 1, 1, 1, 1],
[0, 1, 1, 1, 1],
[0, 1, 1, 1, 1],
[0, 0, 0, 0, 0]]

>>> maze = [[0, 0, 0],
... [0, 1, 0],
... [1, 0, 0]]
>>> solve_maze(maze)
[1, 1, 1]
[0, 0, 1]
[0, 0, 1]
True
>>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
[[0, 0, 0],
[1, 1, 0],
[1, 1, 0]]

>>> maze = [[0, 1, 0],
>>> maze = [[1, 0, 0],
... [0, 1, 0],
... [1, 0, 0]]
>>> solve_maze(maze)
No solution exists!
False
>>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
[[1, 0, 0],
[1, 1, 0],
[1, 1, 0]]

>>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
... [1, 0, 1, 0, 0, 1, 1, 1],
... [0, 1, 0, 1, 0, 0, 1, 0],
... [1, 1, 1, 0, 0, 1, 0, 1],
... [0, 1, 0, 0, 1, 0, 1, 1],
... [0, 0, 0, 1, 1, 1, 0, 1],
... [0, 1, 0, 1, 0, 1, 1, 1],
... [1, 1, 0, 0, 0, 0, 0, 1]]
>>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
[[1, 1, 0, 0, 1, 1, 1, 1],
[1, 1, 1, 0, 0, 1, 1, 1],
[1, 1, 1, 1, 0, 1, 1, 1],
[1, 1, 1, 0, 0, 1, 1, 1],
[1, 1, 0, 0, 1, 1, 1, 1],
[1, 1, 0, 1, 1, 1, 1, 1],
[1, 1, 0, 1, 1, 1, 1, 1],
[1, 1, 0, 1, 1, 1, 1, 1]]
>>> maze = [[1, 0, 0],
... [0, 1, 1],
... [1, 0, 1]]
>>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
Traceback (most recent call last):
...
ValueError: No solution exists!

>>> maze = [[0, 0],
... [1, 1]]
>>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
Traceback (most recent call last):
...
ValueError: No solution exists!

>>> maze = [[0, 1],
... [1, 0]]
>>> solve_maze(maze)
No solution exists!
False
>>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
Traceback (most recent call last):
...
ValueError: Invalid source or destination coordinates

>>> maze = [[1, 0, 0],
... [0, 1, 0],
... [1, 0, 0]]
>>> solve_maze(maze,0,1,len(maze),len(maze)-1)
Traceback (most recent call last):
...
ValueError: Invalid source or destination coordinates
"""
size = len(maze)
# Check if source and destination coordinates are Invalid.
if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
):
raise ValueError("Invalid source or destination coordinates")
# We need to create solution object to save path.
solutions = [[0 for _ in range(size)] for _ in range(size)]
solved = run_maze(maze, 0, 0, solutions)
solutions = [[1 for _ in range(size)] for _ in range(size)]
solved = run_maze(
maze, source_row, source_column, destination_row, destination_column, solutions
)
if solved:
print("\n".join(str(row) for row in solutions))
return solutions
else:
print("No solution exists!")
return solved
raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
maze: list[list[int]],
i: int,
j: int,
destination_row: int,
destination_column: int,
solutions: list[list[int]],
) -> bool:
"""
This method is recursive starting from (i, j) and going in one of four directions:
up, down, left, right.
If a path is found to destination it returns True otherwise it returns False.
Parameters:
maze(2D matrix) : maze
Parameters
maze: A two dimensional matrix of zeros and ones.
i, j : coordinates of matrix
solutions(2D matrix) : solutions
solutions: A two dimensional matrix of solutions.
Returns:
Boolean if path is found True, Otherwise False.
"""
size = len(maze)
# Final check point.
if i == j == (size - 1):
solutions[i][j] = 1
if i == destination_row and j == destination_column and maze[i][j] == 0:
solutions[i][j] = 0
return True

lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
upper_flag = (i < size) and (j < size) # Check upper bounds

if lower_flag and upper_flag:
# check for already visited and block points.
block_flag = (not solutions[i][j]) and (not maze[i][j])
block_flag = (solutions[i][j]) and (not maze[i][j])
if block_flag:
# check visited
solutions[i][j] = 1
solutions[i][j] = 0

# check for directions
if (
run_maze(maze, i + 1, j, solutions)
or run_maze(maze, i, j + 1, solutions)
or run_maze(maze, i - 1, j, solutions)
or run_maze(maze, i, j - 1, solutions)
run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
or run_maze(
maze, i, j + 1, destination_row, destination_column, solutions
)
or run_maze(
maze, i - 1, j, destination_row, destination_column, solutions
)
or run_maze(
maze, i, j - 1, destination_row, destination_column, solutions
)
):
return True

solutions[i][j] = 0
solutions[i][j] = 1
return False
return False


if __name__ == "__main__":
import doctest

doctest.testmod()
doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)

@cclausscclaussOct 4, 2023

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Does this work?!?

@MuhammadummerrMuhammadummerrOct 4, 2023

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Does this work?!?

Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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UPDATED rat_in_maze.py#9148

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 Merged

cclauss
merged 16 commits into

from

Oct 4, 2023
 Merged


UPDATED rat_in_maze.py
#9148
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Show all changes


16 commits


Select commit
Hold shift + click to select a range
9450821

UPDATED rat_in_maze.py


Muhammadummerr Sep 30, 2023
9a1d65f

Update reddit.py in Webprogramming b/c it was causing error in pre-co…


Muhammadummerr Sep 30, 2023
741bb72

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 1, 2023
1b2a9e6

UPDATED rat_in_maze.py


Muhammadummerr Oct 1, 2023
726bc5c

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 1, 2023
d9e1956

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 4, 2023
49e6dee

fixed return type to only maze,otherwise raise valueError.


Muhammadummerr Oct 4, 2023
b59a85d

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
cedaf35

fixed whitespaces error,improved matrix visual.


Muhammadummerr Oct 4, 2023
775d6cd

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Oct 4, 2023
c740da3

updated.


Muhammadummerr Oct 4, 2023
591c098

Try


Muhammadummerr Oct 4, 2023
9c89c79

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
1539b6f

updated


Muhammadummerr Oct 4, 2023
e169d07

updated


Muhammadummerr Oct 4, 2023
8013870

Apply suggestions from code review


cclauss Oct 4, 2023

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181 changes: 130 additions & 51 deletions
backtracking/rat_in_maze.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
 maze: list[list[int]],
 source_row: int,
 source_column: int,
 destination_row: int,
 destination_column: int,
) -> list[list[int]]:
 """
 This method solves the "rat in maze" problem.
 In this problem we have some n by n matrix, a start point and an end point.
 We want to go from the start to the end. In this matrix zeroes represent walls
 and ones paths we can use.
 Parameters :
 maze(2D matrix) : maze
 - maze: A two dimensional matrix of zeros and ones.
 - source_row: The row index of the starting point.
 - source_column: The column index of the starting point.
 - destination_row: The row index of the destination point.
 - destination_column: The column index of the destination point.
 Returns:
 Return: True if the maze has a solution or False if it does not.
 - solution: A 2D matrix representing the solution path if it exists.
 Raises:
 - ValueError: If no solution exists or if the source or
 destination coordinates are invalid.
 Description:
 This method navigates through a maze represented as an n by n matrix,
 starting from a specified source cell and
 aiming to reach a destination cell.
 The maze consists of walls (1s) and open paths (0s).
 By providing custom row and column values, the source and destination
 cells can be adjusted.
 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [1, 0, 1, 0, 1],
 ... [0, 0, 1, 0, 0],
 ... [1, 0, 0, 1, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 0]
 [0, 0, 0, 1, 0]
 [0, 0, 0, 1, 1]
 [0, 0, 0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 0, 0, 0, 1],
 [1, 1, 1, 0, 1],
 [1, 1, 1, 0, 0],
 [1, 1, 1, 1, 0]]

 Note:
 In the output maze, the zeros (0s) represent one of the possible
 paths from the source to the destination.

 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 0, 0, 0, 0]]

 >>> maze = [[0, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 [1, 1, 1]
 [0, 0, 1]
 [0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[0, 1, 0],
 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[1, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
 ... [1, 0, 1, 0, 0, 1, 1, 1],
 ... [0, 1, 0, 1, 0, 0, 1, 0],
 ... [1, 1, 1, 0, 0, 1, 0, 1],
 ... [0, 1, 0, 0, 1, 0, 1, 1],
 ... [0, 0, 0, 1, 1, 1, 0, 1],
 ... [0, 1, 0, 1, 0, 1, 1, 1],
 ... [1, 1, 0, 0, 0, 0, 0, 1]]
 >>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
 [[1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 1, 1, 0, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1]]
 >>> maze = [[1, 0, 0],
 ... [0, 1, 1],
 ... [1, 0, 1]]
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 0],
 ... [1, 1]]
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 1],
 ... [1, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates

 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze,0,1,len(maze),len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates
 """
 size = len(maze)
 # Check if source and destination coordinates are Invalid.
 if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
 not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
 ):
 raise ValueError("Invalid source or destination coordinates")
 # We need to create solution object to save path.
 solutions = [[0 for _ in range(size)] for _ in range(size)]
 solved = run_maze(maze, 0, 0, solutions)
 solutions = [[1 for _ in range(size)] for _ in range(size)]
 solved = run_maze(
 maze, source_row, source_column, destination_row, destination_column, solutions
 )
 if solved:
print("\n".join(str(row) for row in solutions))
return solutions
 else:
 print("No solution exists!")
 return solved
 raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
 maze: list[list[int]],
 i: int,
 j: int,
 destination_row: int,
 destination_column: int,
 solutions: list[list[int]],
) -> bool:
 """
 This method is recursive starting from (i, j) and going in one of four directions:
 up, down, left, right.
 If a path is found to destination it returns True otherwise it returns False.
 Parameters:
 maze(2D matrix) : maze
 Parameters
 maze: A two dimensional matrix of zeros and ones.
 i, j : coordinates of matrix
 solutions(2D matrix) : solutions
 solutions: A two dimensional matrix of solutions.
 Returns:
 Boolean if path is found True, Otherwise False.
 """
 size = len(maze)
 # Final check point.
 if i == j == (size - 1):
 solutions[i][j] = 1
 if i == destination_row and j == destination_column and maze[i][j] == 0:
 solutions[i][j] = 0
 return True

 lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
 upper_flag = (i < size) and (j < size) # Check upper bounds

 if lower_flag and upper_flag:
 # check for already visited and block points.
 block_flag = (not solutions[i][j]) and (not maze[i][j])
 block_flag = (solutions[i][j]) and (not maze[i][j])
 if block_flag:
 # check visited
 solutions[i][j] = 1
 solutions[i][j] = 0

 # check for directions
 if (
 run_maze(maze, i + 1, j, solutions)
 or run_maze(maze, i, j + 1, solutions)
 or run_maze(maze, i - 1, j, solutions)
 or run_maze(maze, i, j - 1, solutions)
 run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
 or run_maze(
 maze, i, j + 1, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i - 1, j, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i, j - 1, destination_row, destination_column, solutions
 )
 ):
 return True

 solutions[i][j] = 0
 solutions[i][j] = 1
 return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
@cclausscclaussOct 4, 2023

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Does this work?!?
@MuhammadummerrMuhammadummerrOct 4, 2023

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Does this work?!?
Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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UPDATED rat_in_maze.py#9148

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UPDATED rat_in_maze.py
#9148
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9450821

UPDATED rat_in_maze.py


Muhammadummerr Sep 30, 2023
9a1d65f

Update reddit.py in Webprogramming b/c it was causing error in pre-co…


Muhammadummerr Sep 30, 2023
741bb72

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 1, 2023
1b2a9e6

UPDATED rat_in_maze.py


Muhammadummerr Oct 1, 2023
726bc5c

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 1, 2023
d9e1956

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 4, 2023
49e6dee

fixed return type to only maze,otherwise raise valueError.


Muhammadummerr Oct 4, 2023
b59a85d

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
cedaf35

fixed whitespaces error,improved matrix visual.


Muhammadummerr Oct 4, 2023
775d6cd

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Oct 4, 2023
c740da3

updated.


Muhammadummerr Oct 4, 2023
591c098

Try


Muhammadummerr Oct 4, 2023
9c89c79

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
1539b6f

updated


Muhammadummerr Oct 4, 2023
e169d07

updated


Muhammadummerr Oct 4, 2023
8013870

Apply suggestions from code review


cclauss Oct 4, 2023

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181 changes: 130 additions & 51 deletions
backtracking/rat_in_maze.py

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Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
 maze: list[list[int]],
 source_row: int,
 source_column: int,
 destination_row: int,
 destination_column: int,
) -> list[list[int]]:
 """
 This method solves the "rat in maze" problem.
 In this problem we have some n by n matrix, a start point and an end point.
 We want to go from the start to the end. In this matrix zeroes represent walls
 and ones paths we can use.
 Parameters :
 maze(2D matrix) : maze
 - maze: A two dimensional matrix of zeros and ones.
 - source_row: The row index of the starting point.
 - source_column: The column index of the starting point.
 - destination_row: The row index of the destination point.
 - destination_column: The column index of the destination point.
 Returns:
 Return: True if the maze has a solution or False if it does not.
 - solution: A 2D matrix representing the solution path if it exists.
 Raises:
 - ValueError: If no solution exists or if the source or
 destination coordinates are invalid.
 Description:
 This method navigates through a maze represented as an n by n matrix,
 starting from a specified source cell and
 aiming to reach a destination cell.
 The maze consists of walls (1s) and open paths (0s).
 By providing custom row and column values, the source and destination
 cells can be adjusted.
 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [1, 0, 1, 0, 1],
 ... [0, 0, 1, 0, 0],
 ... [1, 0, 0, 1, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 0]
 [0, 0, 0, 1, 0]
 [0, 0, 0, 1, 1]
 [0, 0, 0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 0, 0, 0, 1],
 [1, 1, 1, 0, 1],
 [1, 1, 1, 0, 0],
 [1, 1, 1, 1, 0]]

 Note:
 In the output maze, the zeros (0s) represent one of the possible
 paths from the source to the destination.

 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 0, 0, 0, 0]]

 >>> maze = [[0, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 [1, 1, 1]
 [0, 0, 1]
 [0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[0, 1, 0],
 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[1, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
 ... [1, 0, 1, 0, 0, 1, 1, 1],
 ... [0, 1, 0, 1, 0, 0, 1, 0],
 ... [1, 1, 1, 0, 0, 1, 0, 1],
 ... [0, 1, 0, 0, 1, 0, 1, 1],
 ... [0, 0, 0, 1, 1, 1, 0, 1],
 ... [0, 1, 0, 1, 0, 1, 1, 1],
 ... [1, 1, 0, 0, 0, 0, 0, 1]]
 >>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
 [[1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 1, 1, 0, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1]]
 >>> maze = [[1, 0, 0],
 ... [0, 1, 1],
 ... [1, 0, 1]]
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 0],
 ... [1, 1]]
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 1],
 ... [1, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates

 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze,0,1,len(maze),len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates
 """
 size = len(maze)
 # Check if source and destination coordinates are Invalid.
 if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
 not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
 ):
 raise ValueError("Invalid source or destination coordinates")
 # We need to create solution object to save path.
 solutions = [[0 for _ in range(size)] for _ in range(size)]
 solved = run_maze(maze, 0, 0, solutions)
 solutions = [[1 for _ in range(size)] for _ in range(size)]
 solved = run_maze(
 maze, source_row, source_column, destination_row, destination_column, solutions
 )
 if solved:
print("\n".join(str(row) for row in solutions))
return solutions
 else:
 print("No solution exists!")
 return solved
 raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
 maze: list[list[int]],
 i: int,
 j: int,
 destination_row: int,
 destination_column: int,
 solutions: list[list[int]],
) -> bool:
 """
 This method is recursive starting from (i, j) and going in one of four directions:
 up, down, left, right.
 If a path is found to destination it returns True otherwise it returns False.
 Parameters:
 maze(2D matrix) : maze
 Parameters
 maze: A two dimensional matrix of zeros and ones.
 i, j : coordinates of matrix
 solutions(2D matrix) : solutions
 solutions: A two dimensional matrix of solutions.
 Returns:
 Boolean if path is found True, Otherwise False.
 """
 size = len(maze)
 # Final check point.
 if i == j == (size - 1):
 solutions[i][j] = 1
 if i == destination_row and j == destination_column and maze[i][j] == 0:
 solutions[i][j] = 0
 return True

 lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
 upper_flag = (i < size) and (j < size) # Check upper bounds

 if lower_flag and upper_flag:
 # check for already visited and block points.
 block_flag = (not solutions[i][j]) and (not maze[i][j])
 block_flag = (solutions[i][j]) and (not maze[i][j])
 if block_flag:
 # check visited
 solutions[i][j] = 1
 solutions[i][j] = 0

 # check for directions
 if (
 run_maze(maze, i + 1, j, solutions)
 or run_maze(maze, i, j + 1, solutions)
 or run_maze(maze, i - 1, j, solutions)
 or run_maze(maze, i, j - 1, solutions)
 run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
 or run_maze(
 maze, i, j + 1, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i - 1, j, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i, j - 1, destination_row, destination_column, solutions
 )
 ):
 return True

 solutions[i][j] = 0
 solutions[i][j] = 1
 return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
@cclausscclaussOct 4, 2023

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Does this work?!?
@MuhammadummerrMuhammadummerrOct 4, 2023

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Does this work?!?
Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
UPDATED rat_in_maze.py#9148

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 Merged

cclauss
merged 16 commits into

from

Oct 4, 2023
 Merged


UPDATED rat_in_maze.py
#9148
 Changes from all commits
Commits

Show all changes


16 commits


Select commit
Hold shift + click to select a range
9450821

UPDATED rat_in_maze.py


Muhammadummerr Sep 30, 2023
9a1d65f

Update reddit.py in Webprogramming b/c it was causing error in pre-co…


Muhammadummerr Sep 30, 2023
741bb72

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 1, 2023
1b2a9e6

UPDATED rat_in_maze.py


Muhammadummerr Oct 1, 2023
726bc5c

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 1, 2023
d9e1956

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 4, 2023
49e6dee

fixed return type to only maze,otherwise raise valueError.


Muhammadummerr Oct 4, 2023
b59a85d

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
cedaf35

fixed whitespaces error,improved matrix visual.


Muhammadummerr Oct 4, 2023
775d6cd

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Oct 4, 2023
c740da3

updated.


Muhammadummerr Oct 4, 2023
591c098

Try


Muhammadummerr Oct 4, 2023
9c89c79

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
1539b6f

updated


Muhammadummerr Oct 4, 2023
e169d07

updated


Muhammadummerr Oct 4, 2023
8013870

Apply suggestions from code review


cclauss Oct 4, 2023

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Filter by extension
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181 changes: 130 additions & 51 deletions
backtracking/rat_in_maze.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
 maze: list[list[int]],
 source_row: int,
 source_column: int,
 destination_row: int,
 destination_column: int,
) -> list[list[int]]:
 """
 This method solves the "rat in maze" problem.
 In this problem we have some n by n matrix, a start point and an end point.
 We want to go from the start to the end. In this matrix zeroes represent walls
 and ones paths we can use.
 Parameters :
 maze(2D matrix) : maze
 - maze: A two dimensional matrix of zeros and ones.
 - source_row: The row index of the starting point.
 - source_column: The column index of the starting point.
 - destination_row: The row index of the destination point.
 - destination_column: The column index of the destination point.
 Returns:
 Return: True if the maze has a solution or False if it does not.
 - solution: A 2D matrix representing the solution path if it exists.
 Raises:
 - ValueError: If no solution exists or if the source or
 destination coordinates are invalid.
 Description:
 This method navigates through a maze represented as an n by n matrix,
 starting from a specified source cell and
 aiming to reach a destination cell.
 The maze consists of walls (1s) and open paths (0s).
 By providing custom row and column values, the source and destination
 cells can be adjusted.
 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [1, 0, 1, 0, 1],
 ... [0, 0, 1, 0, 0],
 ... [1, 0, 0, 1, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 0]
 [0, 0, 0, 1, 0]
 [0, 0, 0, 1, 1]
 [0, 0, 0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 0, 0, 0, 1],
 [1, 1, 1, 0, 1],
 [1, 1, 1, 0, 0],
 [1, 1, 1, 1, 0]]

 Note:
 In the output maze, the zeros (0s) represent one of the possible
 paths from the source to the destination.

 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 0, 0, 0, 0]]

 >>> maze = [[0, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 [1, 1, 1]
 [0, 0, 1]
 [0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[0, 1, 0],
 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[1, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
 ... [1, 0, 1, 0, 0, 1, 1, 1],
 ... [0, 1, 0, 1, 0, 0, 1, 0],
 ... [1, 1, 1, 0, 0, 1, 0, 1],
 ... [0, 1, 0, 0, 1, 0, 1, 1],
 ... [0, 0, 0, 1, 1, 1, 0, 1],
 ... [0, 1, 0, 1, 0, 1, 1, 1],
 ... [1, 1, 0, 0, 0, 0, 0, 1]]
 >>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
 [[1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 1, 1, 0, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1]]
 >>> maze = [[1, 0, 0],
 ... [0, 1, 1],
 ... [1, 0, 1]]
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 0],
 ... [1, 1]]
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 1],
 ... [1, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates

 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze,0,1,len(maze),len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates
 """
 size = len(maze)
 # Check if source and destination coordinates are Invalid.
 if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
 not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
 ):
 raise ValueError("Invalid source or destination coordinates")
 # We need to create solution object to save path.
 solutions = [[0 for _ in range(size)] for _ in range(size)]
 solved = run_maze(maze, 0, 0, solutions)
 solutions = [[1 for _ in range(size)] for _ in range(size)]
 solved = run_maze(
 maze, source_row, source_column, destination_row, destination_column, solutions
 )
 if solved:
print("\n".join(str(row) for row in solutions))
return solutions
 else:
 print("No solution exists!")
 return solved
 raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
 maze: list[list[int]],
 i: int,
 j: int,
 destination_row: int,
 destination_column: int,
 solutions: list[list[int]],
) -> bool:
 """
 This method is recursive starting from (i, j) and going in one of four directions:
 up, down, left, right.
 If a path is found to destination it returns True otherwise it returns False.
 Parameters:
 maze(2D matrix) : maze
 Parameters
 maze: A two dimensional matrix of zeros and ones.
 i, j : coordinates of matrix
 solutions(2D matrix) : solutions
 solutions: A two dimensional matrix of solutions.
 Returns:
 Boolean if path is found True, Otherwise False.
 """
 size = len(maze)
 # Final check point.
 if i == j == (size - 1):
 solutions[i][j] = 1
 if i == destination_row and j == destination_column and maze[i][j] == 0:
 solutions[i][j] = 0
 return True

 lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
 upper_flag = (i < size) and (j < size) # Check upper bounds

 if lower_flag and upper_flag:
 # check for already visited and block points.
 block_flag = (not solutions[i][j]) and (not maze[i][j])
 block_flag = (solutions[i][j]) and (not maze[i][j])
 if block_flag:
 # check visited
 solutions[i][j] = 1
 solutions[i][j] = 0

 # check for directions
 if (
 run_maze(maze, i + 1, j, solutions)
 or run_maze(maze, i, j + 1, solutions)
 or run_maze(maze, i - 1, j, solutions)
 or run_maze(maze, i, j - 1, solutions)
 run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
 or run_maze(
 maze, i, j + 1, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i - 1, j, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i, j - 1, destination_row, destination_column, solutions
 )
 ):
 return True

 solutions[i][j] = 0
 solutions[i][j] = 1
 return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
@cclausscclaussOct 4, 2023

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Does this work?!?
@MuhammadummerrMuhammadummerrOct 4, 2023

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Does this work?!?
Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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UPDATED rat_in_maze.py#9148

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cclauss
merged 16 commits into

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 Merged


UPDATED rat_in_maze.py
#9148
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9450821

UPDATED rat_in_maze.py


Muhammadummerr Sep 30, 2023
9a1d65f

Update reddit.py in Webprogramming b/c it was causing error in pre-co…


Muhammadummerr Sep 30, 2023
741bb72

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 1, 2023
1b2a9e6

UPDATED rat_in_maze.py


Muhammadummerr Oct 1, 2023
726bc5c

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 1, 2023
d9e1956

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 4, 2023
49e6dee

fixed return type to only maze,otherwise raise valueError.


Muhammadummerr Oct 4, 2023
b59a85d

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
cedaf35

fixed whitespaces error,improved matrix visual.


Muhammadummerr Oct 4, 2023
775d6cd

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Oct 4, 2023
c740da3

updated.


Muhammadummerr Oct 4, 2023
591c098

Try


Muhammadummerr Oct 4, 2023
9c89c79

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
1539b6f

updated


Muhammadummerr Oct 4, 2023
e169d07

updated


Muhammadummerr Oct 4, 2023
8013870

Apply suggestions from code review


cclauss Oct 4, 2023

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181 changes: 130 additions & 51 deletions
backtracking/rat_in_maze.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
 maze: list[list[int]],
 source_row: int,
 source_column: int,
 destination_row: int,
 destination_column: int,
) -> list[list[int]]:
 """
 This method solves the "rat in maze" problem.
 In this problem we have some n by n matrix, a start point and an end point.
 We want to go from the start to the end. In this matrix zeroes represent walls
 and ones paths we can use.
 Parameters :
 maze(2D matrix) : maze
 - maze: A two dimensional matrix of zeros and ones.
 - source_row: The row index of the starting point.
 - source_column: The column index of the starting point.
 - destination_row: The row index of the destination point.
 - destination_column: The column index of the destination point.
 Returns:
 Return: True if the maze has a solution or False if it does not.
 - solution: A 2D matrix representing the solution path if it exists.
 Raises:
 - ValueError: If no solution exists or if the source or
 destination coordinates are invalid.
 Description:
 This method navigates through a maze represented as an n by n matrix,
 starting from a specified source cell and
 aiming to reach a destination cell.
 The maze consists of walls (1s) and open paths (0s).
 By providing custom row and column values, the source and destination
 cells can be adjusted.
 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [1, 0, 1, 0, 1],
 ... [0, 0, 1, 0, 0],
 ... [1, 0, 0, 1, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 0]
 [0, 0, 0, 1, 0]
 [0, 0, 0, 1, 1]
 [0, 0, 0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 0, 0, 0, 1],
 [1, 1, 1, 0, 1],
 [1, 1, 1, 0, 0],
 [1, 1, 1, 1, 0]]

 Note:
 In the output maze, the zeros (0s) represent one of the possible
 paths from the source to the destination.

 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 0, 0, 0, 0]]

 >>> maze = [[0, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 [1, 1, 1]
 [0, 0, 1]
 [0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[0, 1, 0],
 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[1, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
 ... [1, 0, 1, 0, 0, 1, 1, 1],
 ... [0, 1, 0, 1, 0, 0, 1, 0],
 ... [1, 1, 1, 0, 0, 1, 0, 1],
 ... [0, 1, 0, 0, 1, 0, 1, 1],
 ... [0, 0, 0, 1, 1, 1, 0, 1],
 ... [0, 1, 0, 1, 0, 1, 1, 1],
 ... [1, 1, 0, 0, 0, 0, 0, 1]]
 >>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
 [[1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 1, 1, 0, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1]]
 >>> maze = [[1, 0, 0],
 ... [0, 1, 1],
 ... [1, 0, 1]]
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 0],
 ... [1, 1]]
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 1],
 ... [1, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates

 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze,0,1,len(maze),len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates
 """
 size = len(maze)
 # Check if source and destination coordinates are Invalid.
 if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
 not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
 ):
 raise ValueError("Invalid source or destination coordinates")
 # We need to create solution object to save path.
 solutions = [[0 for _ in range(size)] for _ in range(size)]
 solved = run_maze(maze, 0, 0, solutions)
 solutions = [[1 for _ in range(size)] for _ in range(size)]
 solved = run_maze(
 maze, source_row, source_column, destination_row, destination_column, solutions
 )
 if solved:
print("\n".join(str(row) for row in solutions))
return solutions
 else:
 print("No solution exists!")
 return solved
 raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
 maze: list[list[int]],
 i: int,
 j: int,
 destination_row: int,
 destination_column: int,
 solutions: list[list[int]],
) -> bool:
 """
 This method is recursive starting from (i, j) and going in one of four directions:
 up, down, left, right.
 If a path is found to destination it returns True otherwise it returns False.
 Parameters:
 maze(2D matrix) : maze
 Parameters
 maze: A two dimensional matrix of zeros and ones.
 i, j : coordinates of matrix
 solutions(2D matrix) : solutions
 solutions: A two dimensional matrix of solutions.
 Returns:
 Boolean if path is found True, Otherwise False.
 """
 size = len(maze)
 # Final check point.
 if i == j == (size - 1):
 solutions[i][j] = 1
 if i == destination_row and j == destination_column and maze[i][j] == 0:
 solutions[i][j] = 0
 return True

 lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
 upper_flag = (i < size) and (j < size) # Check upper bounds

 if lower_flag and upper_flag:
 # check for already visited and block points.
 block_flag = (not solutions[i][j]) and (not maze[i][j])
 block_flag = (solutions[i][j]) and (not maze[i][j])
 if block_flag:
 # check visited
 solutions[i][j] = 1
 solutions[i][j] = 0

 # check for directions
 if (
 run_maze(maze, i + 1, j, solutions)
 or run_maze(maze, i, j + 1, solutions)
 or run_maze(maze, i - 1, j, solutions)
 or run_maze(maze, i, j - 1, solutions)
 run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
 or run_maze(
 maze, i, j + 1, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i - 1, j, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i, j - 1, destination_row, destination_column, solutions
 )
 ):
 return True

 solutions[i][j] = 0
 solutions[i][j] = 1
 return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
@cclausscclaussOct 4, 2023

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Does this work?!?
@MuhammadummerrMuhammadummerrOct 4, 2023

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ContributorAuthor
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Does this work?!?
Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
UPDATED rat_in_maze.py#9148

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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By clicking “Sign up for GitHub”, you agree to our terms of service and
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to your account

 Merged

cclauss
merged 16 commits into

from

Oct 4, 2023
 Merged


UPDATED rat_in_maze.py
#9148
 Changes from all commits
Commits

Show all changes


16 commits


Select commit
Hold shift + click to select a range
9450821

UPDATED rat_in_maze.py


Muhammadummerr Sep 30, 2023
9a1d65f

Update reddit.py in Webprogramming b/c it was causing error in pre-co…


Muhammadummerr Sep 30, 2023
741bb72

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 1, 2023
1b2a9e6

UPDATED rat_in_maze.py


Muhammadummerr Oct 1, 2023
726bc5c

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 1, 2023
d9e1956

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 4, 2023
49e6dee

fixed return type to only maze,otherwise raise valueError.


Muhammadummerr Oct 4, 2023
b59a85d

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
cedaf35

fixed whitespaces error,improved matrix visual.


Muhammadummerr Oct 4, 2023
775d6cd

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Oct 4, 2023
c740da3

updated.


Muhammadummerr Oct 4, 2023
591c098

Try


Muhammadummerr Oct 4, 2023
9c89c79

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
1539b6f

updated


Muhammadummerr Oct 4, 2023
e169d07

updated


Muhammadummerr Oct 4, 2023
8013870

Apply suggestions from code review


cclauss Oct 4, 2023

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Filter by extension
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181 changes: 130 additions & 51 deletions
backtracking/rat_in_maze.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
 maze: list[list[int]],
 source_row: int,
 source_column: int,
 destination_row: int,
 destination_column: int,
) -> list[list[int]]:
 """
 This method solves the "rat in maze" problem.
 In this problem we have some n by n matrix, a start point and an end point.
 We want to go from the start to the end. In this matrix zeroes represent walls
 and ones paths we can use.
 Parameters :
 maze(2D matrix) : maze
 - maze: A two dimensional matrix of zeros and ones.
 - source_row: The row index of the starting point.
 - source_column: The column index of the starting point.
 - destination_row: The row index of the destination point.
 - destination_column: The column index of the destination point.
 Returns:
 Return: True if the maze has a solution or False if it does not.
 - solution: A 2D matrix representing the solution path if it exists.
 Raises:
 - ValueError: If no solution exists or if the source or
 destination coordinates are invalid.
 Description:
 This method navigates through a maze represented as an n by n matrix,
 starting from a specified source cell and
 aiming to reach a destination cell.
 The maze consists of walls (1s) and open paths (0s).
 By providing custom row and column values, the source and destination
 cells can be adjusted.
 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [1, 0, 1, 0, 1],
 ... [0, 0, 1, 0, 0],
 ... [1, 0, 0, 1, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 0]
 [0, 0, 0, 1, 0]
 [0, 0, 0, 1, 1]
 [0, 0, 0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 0, 0, 0, 1],
 [1, 1, 1, 0, 1],
 [1, 1, 1, 0, 0],
 [1, 1, 1, 1, 0]]

 Note:
 In the output maze, the zeros (0s) represent one of the possible
 paths from the source to the destination.

 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 0, 0, 0, 0]]

 >>> maze = [[0, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 [1, 1, 1]
 [0, 0, 1]
 [0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[0, 1, 0],
 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[1, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
 ... [1, 0, 1, 0, 0, 1, 1, 1],
 ... [0, 1, 0, 1, 0, 0, 1, 0],
 ... [1, 1, 1, 0, 0, 1, 0, 1],
 ... [0, 1, 0, 0, 1, 0, 1, 1],
 ... [0, 0, 0, 1, 1, 1, 0, 1],
 ... [0, 1, 0, 1, 0, 1, 1, 1],
 ... [1, 1, 0, 0, 0, 0, 0, 1]]
 >>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
 [[1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 1, 1, 0, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1]]
 >>> maze = [[1, 0, 0],
 ... [0, 1, 1],
 ... [1, 0, 1]]
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 0],
 ... [1, 1]]
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 1],
 ... [1, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates

 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze,0,1,len(maze),len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates
 """
 size = len(maze)
 # Check if source and destination coordinates are Invalid.
 if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
 not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
 ):
 raise ValueError("Invalid source or destination coordinates")
 # We need to create solution object to save path.
 solutions = [[0 for _ in range(size)] for _ in range(size)]
 solved = run_maze(maze, 0, 0, solutions)
 solutions = [[1 for _ in range(size)] for _ in range(size)]
 solved = run_maze(
 maze, source_row, source_column, destination_row, destination_column, solutions
 )
 if solved:
print("\n".join(str(row) for row in solutions))
return solutions
 else:
 print("No solution exists!")
 return solved
 raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
 maze: list[list[int]],
 i: int,
 j: int,
 destination_row: int,
 destination_column: int,
 solutions: list[list[int]],
) -> bool:
 """
 This method is recursive starting from (i, j) and going in one of four directions:
 up, down, left, right.
 If a path is found to destination it returns True otherwise it returns False.
 Parameters:
 maze(2D matrix) : maze
 Parameters
 maze: A two dimensional matrix of zeros and ones.
 i, j : coordinates of matrix
 solutions(2D matrix) : solutions
 solutions: A two dimensional matrix of solutions.
 Returns:
 Boolean if path is found True, Otherwise False.
 """
 size = len(maze)
 # Final check point.
 if i == j == (size - 1):
 solutions[i][j] = 1
 if i == destination_row and j == destination_column and maze[i][j] == 0:
 solutions[i][j] = 0
 return True

 lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
 upper_flag = (i < size) and (j < size) # Check upper bounds

 if lower_flag and upper_flag:
 # check for already visited and block points.
 block_flag = (not solutions[i][j]) and (not maze[i][j])
 block_flag = (solutions[i][j]) and (not maze[i][j])
 if block_flag:
 # check visited
 solutions[i][j] = 1
 solutions[i][j] = 0

 # check for directions
 if (
 run_maze(maze, i + 1, j, solutions)
 or run_maze(maze, i, j + 1, solutions)
 or run_maze(maze, i - 1, j, solutions)
 or run_maze(maze, i, j - 1, solutions)
 run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
 or run_maze(
 maze, i, j + 1, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i - 1, j, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i, j - 1, destination_row, destination_column, solutions
 )
 ):
 return True

 solutions[i][j] = 0
 solutions[i][j] = 1
 return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
@cclausscclaussOct 4, 2023

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Does this work?!?
@MuhammadummerrMuhammadummerrOct 4, 2023

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Does this work?!?
Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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UPDATED rat_in_maze.py#9148

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 Merged

cclauss
merged 16 commits into

from

Oct 4, 2023
 Merged


UPDATED rat_in_maze.py
#9148
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9450821

UPDATED rat_in_maze.py


Muhammadummerr Sep 30, 2023
9a1d65f

Update reddit.py in Webprogramming b/c it was causing error in pre-co…


Muhammadummerr Sep 30, 2023
741bb72

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 1, 2023
1b2a9e6

UPDATED rat_in_maze.py


Muhammadummerr Oct 1, 2023
726bc5c

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 1, 2023
d9e1956

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 4, 2023
49e6dee

fixed return type to only maze,otherwise raise valueError.


Muhammadummerr Oct 4, 2023
b59a85d

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
cedaf35

fixed whitespaces error,improved matrix visual.


Muhammadummerr Oct 4, 2023
775d6cd

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Oct 4, 2023
c740da3

updated.


Muhammadummerr Oct 4, 2023
591c098

Try


Muhammadummerr Oct 4, 2023
9c89c79

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
1539b6f

updated


Muhammadummerr Oct 4, 2023
e169d07

updated


Muhammadummerr Oct 4, 2023
8013870

Apply suggestions from code review


cclauss Oct 4, 2023

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181 changes: 130 additions & 51 deletions
backtracking/rat_in_maze.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
 maze: list[list[int]],
 source_row: int,
 source_column: int,
 destination_row: int,
 destination_column: int,
) -> list[list[int]]:
 """
 This method solves the "rat in maze" problem.
 In this problem we have some n by n matrix, a start point and an end point.
 We want to go from the start to the end. In this matrix zeroes represent walls
 and ones paths we can use.
 Parameters :
 maze(2D matrix) : maze
 - maze: A two dimensional matrix of zeros and ones.
 - source_row: The row index of the starting point.
 - source_column: The column index of the starting point.
 - destination_row: The row index of the destination point.
 - destination_column: The column index of the destination point.
 Returns:
 Return: True if the maze has a solution or False if it does not.
 - solution: A 2D matrix representing the solution path if it exists.
 Raises:
 - ValueError: If no solution exists or if the source or
 destination coordinates are invalid.
 Description:
 This method navigates through a maze represented as an n by n matrix,
 starting from a specified source cell and
 aiming to reach a destination cell.
 The maze consists of walls (1s) and open paths (0s).
 By providing custom row and column values, the source and destination
 cells can be adjusted.
 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [1, 0, 1, 0, 1],
 ... [0, 0, 1, 0, 0],
 ... [1, 0, 0, 1, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 0]
 [0, 0, 0, 1, 0]
 [0, 0, 0, 1, 1]
 [0, 0, 0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 0, 0, 0, 1],
 [1, 1, 1, 0, 1],
 [1, 1, 1, 0, 0],
 [1, 1, 1, 1, 0]]

 Note:
 In the output maze, the zeros (0s) represent one of the possible
 paths from the source to the destination.

 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 0, 0, 0, 0]]

 >>> maze = [[0, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 [1, 1, 1]
 [0, 0, 1]
 [0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[0, 1, 0],
 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[1, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
 ... [1, 0, 1, 0, 0, 1, 1, 1],
 ... [0, 1, 0, 1, 0, 0, 1, 0],
 ... [1, 1, 1, 0, 0, 1, 0, 1],
 ... [0, 1, 0, 0, 1, 0, 1, 1],
 ... [0, 0, 0, 1, 1, 1, 0, 1],
 ... [0, 1, 0, 1, 0, 1, 1, 1],
 ... [1, 1, 0, 0, 0, 0, 0, 1]]
 >>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
 [[1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 1, 1, 0, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1]]
 >>> maze = [[1, 0, 0],
 ... [0, 1, 1],
 ... [1, 0, 1]]
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 0],
 ... [1, 1]]
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 1],
 ... [1, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates

 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze,0,1,len(maze),len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates
 """
 size = len(maze)
 # Check if source and destination coordinates are Invalid.
 if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
 not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
 ):
 raise ValueError("Invalid source or destination coordinates")
 # We need to create solution object to save path.
 solutions = [[0 for _ in range(size)] for _ in range(size)]
 solved = run_maze(maze, 0, 0, solutions)
 solutions = [[1 for _ in range(size)] for _ in range(size)]
 solved = run_maze(
 maze, source_row, source_column, destination_row, destination_column, solutions
 )
 if solved:
print("\n".join(str(row) for row in solutions))
return solutions
 else:
 print("No solution exists!")
 return solved
 raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
 maze: list[list[int]],
 i: int,
 j: int,
 destination_row: int,
 destination_column: int,
 solutions: list[list[int]],
) -> bool:
 """
 This method is recursive starting from (i, j) and going in one of four directions:
 up, down, left, right.
 If a path is found to destination it returns True otherwise it returns False.
 Parameters:
 maze(2D matrix) : maze
 Parameters
 maze: A two dimensional matrix of zeros and ones.
 i, j : coordinates of matrix
 solutions(2D matrix) : solutions
 solutions: A two dimensional matrix of solutions.
 Returns:
 Boolean if path is found True, Otherwise False.
 """
 size = len(maze)
 # Final check point.
 if i == j == (size - 1):
 solutions[i][j] = 1
 if i == destination_row and j == destination_column and maze[i][j] == 0:
 solutions[i][j] = 0
 return True

 lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
 upper_flag = (i < size) and (j < size) # Check upper bounds

 if lower_flag and upper_flag:
 # check for already visited and block points.
 block_flag = (not solutions[i][j]) and (not maze[i][j])
 block_flag = (solutions[i][j]) and (not maze[i][j])
 if block_flag:
 # check visited
 solutions[i][j] = 1
 solutions[i][j] = 0

 # check for directions
 if (
 run_maze(maze, i + 1, j, solutions)
 or run_maze(maze, i, j + 1, solutions)
 or run_maze(maze, i - 1, j, solutions)
 or run_maze(maze, i, j - 1, solutions)
 run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
 or run_maze(
 maze, i, j + 1, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i - 1, j, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i, j - 1, destination_row, destination_column, solutions
 )
 ):
 return True

 solutions[i][j] = 0
 solutions[i][j] = 1
 return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
@cclausscclaussOct 4, 2023

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Does this work?!?
@MuhammadummerrMuhammadummerrOct 4, 2023

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Does this work?!?
Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
UPDATED rat_in_maze.py#9148

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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to your account

 Merged

cclauss
merged 16 commits into

from

Oct 4, 2023
 Merged


UPDATED rat_in_maze.py
#9148
 Changes from all commits
Commits

Show all changes


16 commits


Select commit
Hold shift + click to select a range
9450821

UPDATED rat_in_maze.py


Muhammadummerr Sep 30, 2023
9a1d65f

Update reddit.py in Webprogramming b/c it was causing error in pre-co…


Muhammadummerr Sep 30, 2023
741bb72

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 1, 2023
1b2a9e6

UPDATED rat_in_maze.py


Muhammadummerr Oct 1, 2023
726bc5c

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 1, 2023
d9e1956

Merge branch 'TheAlgorithms:master' into new_branch


Muhammadummerr Oct 4, 2023
49e6dee

fixed return type to only maze,otherwise raise valueError.


Muhammadummerr Oct 4, 2023
b59a85d

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
cedaf35

fixed whitespaces error,improved matrix visual.


Muhammadummerr Oct 4, 2023
775d6cd

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Oct 4, 2023
c740da3

updated.


Muhammadummerr Oct 4, 2023
591c098

Try


Muhammadummerr Oct 4, 2023
9c89c79

Merge branch 'new_branch' of https://github.com/Muhammadummerr/Python…


Muhammadummerr Oct 4, 2023
1539b6f

updated


Muhammadummerr Oct 4, 2023
e169d07

updated


Muhammadummerr Oct 4, 2023
8013870

Apply suggestions from code review


cclauss Oct 4, 2023

File filter

Filter by extension
Filter by extension
Conversations

Failed to load comments. 
Loading
Jump to

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Failed to load files. 
Loading
 Diff view

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181 changes: 130 additions & 51 deletions
backtracking/rat_in_maze.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,118 +1,197 @@
from __future__ import annotations


def solve_maze(maze: list[list[int]]) -> bool:
def solve_maze(
 maze: list[list[int]],
 source_row: int,
 source_column: int,
 destination_row: int,
 destination_column: int,
) -> list[list[int]]:
 """
 This method solves the "rat in maze" problem.
 In this problem we have some n by n matrix, a start point and an end point.
 We want to go from the start to the end. In this matrix zeroes represent walls
 and ones paths we can use.
 Parameters :
 maze(2D matrix) : maze
 - maze: A two dimensional matrix of zeros and ones.
 - source_row: The row index of the starting point.
 - source_column: The column index of the starting point.
 - destination_row: The row index of the destination point.
 - destination_column: The column index of the destination point.
 Returns:
 Return: True if the maze has a solution or False if it does not.
 - solution: A 2D matrix representing the solution path if it exists.
 Raises:
 - ValueError: If no solution exists or if the source or
 destination coordinates are invalid.
 Description:
 This method navigates through a maze represented as an n by n matrix,
 starting from a specified source cell and
 aiming to reach a destination cell.
 The maze consists of walls (1s) and open paths (0s).
 By providing custom row and column values, the source and destination
 cells can be adjusted.
 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [1, 0, 1, 0, 1],
 ... [0, 0, 1, 0, 0],
 ... [1, 0, 0, 1, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 0]
 [0, 0, 0, 1, 0]
 [0, 0, 0, 1, 1]
 [0, 0, 0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 0, 0, 0, 1],
 [1, 1, 1, 0, 1],
 [1, 1, 1, 0, 0],
 [1, 1, 1, 1, 0]]

 Note:
 In the output maze, the zeros (0s) represent one of the possible
 paths from the source to the destination.

 >>> maze = [[0, 1, 0, 1, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 1],
 ... [0, 0, 0, 0, 0],
 ... [0, 0, 0, 0, 0]]
 >>> solve_maze(maze)
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 0, 0, 0, 0]
 [1, 1, 1, 1, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 1, 1, 1, 1],
 [0, 0, 0, 0, 0]]

 >>> maze = [[0, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 [1, 1, 1]
 [0, 0, 1]
 [0, 0, 1]
 True
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[0, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[0, 1, 0],
 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1) # doctest: +NORMALIZE_WHITESPACE
 [[1, 0, 0],
 [1, 1, 0],
 [1, 1, 0]]

 >>> maze = [[1, 1, 0, 0, 1, 0, 0, 1],
 ... [1, 0, 1, 0, 0, 1, 1, 1],
 ... [0, 1, 0, 1, 0, 0, 1, 0],
 ... [1, 1, 1, 0, 0, 1, 0, 1],
 ... [0, 1, 0, 0, 1, 0, 1, 1],
 ... [0, 0, 0, 1, 1, 1, 0, 1],
 ... [0, 1, 0, 1, 0, 1, 1, 1],
 ... [1, 1, 0, 0, 0, 0, 0, 1]]
 >>> solve_maze(maze,0,2,len(maze)-1,2) # doctest: +NORMALIZE_WHITESPACE
 [[1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 1, 1, 0, 1, 1, 1],
 [1, 1, 1, 0, 0, 1, 1, 1],
 [1, 1, 0, 0, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1],
 [1, 1, 0, 1, 1, 1, 1, 1]]
 >>> maze = [[1, 0, 0],
 ... [0, 1, 1],
 ... [1, 0, 1]]
 >>> solve_maze(maze,0,1,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 0],
 ... [1, 1]]
 >>> solve_maze(maze,0,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: No solution exists!

 >>> maze = [[0, 1],
 ... [1, 0]]
 >>> solve_maze(maze)
 No solution exists!
 False
 >>> solve_maze(maze,2,0,len(maze)-1,len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates

 >>> maze = [[1, 0, 0],
 ... [0, 1, 0],
 ... [1, 0, 0]]
 >>> solve_maze(maze,0,1,len(maze),len(maze)-1)
 Traceback (most recent call last):
 ...
 ValueError: Invalid source or destination coordinates
 """
 size = len(maze)
 # Check if source and destination coordinates are Invalid.
 if not (0 <= source_row <= size - 1 and 0 <= source_column <= size - 1) or (
 not (0 <= destination_row <= size - 1 and 0 <= destination_column <= size - 1)
 ):
 raise ValueError("Invalid source or destination coordinates")
 # We need to create solution object to save path.
 solutions = [[0 for _ in range(size)] for _ in range(size)]
 solved = run_maze(maze, 0, 0, solutions)
 solutions = [[1 for _ in range(size)] for _ in range(size)]
 solved = run_maze(
 maze, source_row, source_column, destination_row, destination_column, solutions
 )
 if solved:
print("\n".join(str(row) for row in solutions))
return solutions
 else:
 print("No solution exists!")
 return solved
 raise ValueError("No solution exists!")


def run_maze(maze: list[list[int]], i: int, j: int, solutions: list[list[int]]) -> bool:
def run_maze(
 maze: list[list[int]],
 i: int,
 j: int,
 destination_row: int,
 destination_column: int,
 solutions: list[list[int]],
) -> bool:
 """
 This method is recursive starting from (i, j) and going in one of four directions:
 up, down, left, right.
 If a path is found to destination it returns True otherwise it returns False.
 Parameters:
 maze(2D matrix) : maze
 Parameters
 maze: A two dimensional matrix of zeros and ones.
 i, j : coordinates of matrix
 solutions(2D matrix) : solutions
 solutions: A two dimensional matrix of solutions.
 Returns:
 Boolean if path is found True, Otherwise False.
 """
 size = len(maze)
 # Final check point.
 if i == j == (size - 1):
 solutions[i][j] = 1
 if i == destination_row and j == destination_column and maze[i][j] == 0:
 solutions[i][j] = 0
 return True

 lower_flag = (not i < 0) and (not j < 0) # Check lower bounds
 upper_flag = (i < size) and (j < size) # Check upper bounds

 if lower_flag and upper_flag:
 # check for already visited and block points.
 block_flag = (not solutions[i][j]) and (not maze[i][j])
 block_flag = (solutions[i][j]) and (not maze[i][j])
 if block_flag:
 # check visited
 solutions[i][j] = 1
 solutions[i][j] = 0

 # check for directions
 if (
 run_maze(maze, i + 1, j, solutions)
 or run_maze(maze, i, j + 1, solutions)
 or run_maze(maze, i - 1, j, solutions)
 or run_maze(maze, i, j - 1, solutions)
 run_maze(maze, i + 1, j, destination_row, destination_column, solutions)
 or run_maze(
 maze, i, j + 1, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i - 1, j, destination_row, destination_column, solutions
 )
 or run_maze(
 maze, i, j - 1, destination_row, destination_column, solutions
 )
 ):
 return True

 solutions[i][j] = 0
 solutions[i][j] = 1
 return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
@cclausscclaussOct 4, 2023

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Does this work?!?
@MuhammadummerrMuhammadummerrOct 4, 2023

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Does this work?!?
Yes, it's working on my local machine, but it's not working on the build test. That's why I added '# doctest: +NORMALIZE_WHITESPACE' to each test.