Given a character matrix, return all the characters in the clockwise spiral order starting from the top-left.
Example
Input:
[
[‘X’ ‘Y’ ‘A’]
[‘M’ ‘B’ ‘C’]
[‘P’ ‘Q’ ‘R’]
]
Output: “XYACRQPMB”
For the given matrix rows = 3 and cols = 3. Spiral order is ‘X’ -> ‘Y’ -> ‘A’ -> ‘C’ -> ‘R’ -> ‘Q’ -> ‘P’ -> ‘M’ -> ‘B’. So return string “XYACRQPMB” of length rows * cols = 9.
Notes
Input Parameters: There is only one argument denoting character matrix matrix.
Output: Return a string res, of length rows * cols denoting the spiral order of matrix.
Constraints:
This problem is less about logic, but more about careful index manipulation.
Hint – It may be faster to write this, if you name your variables clearly. Instead of i,j,k,l etc, try naming them like row, col, start, end etc. That will also help your interviewer follow along more easily.
There are many solutions possible for this problem.
Here we will provide one interesting solution that uses only one for loop. Suppose we start from the top-left corner (0, 0) and turn right at certain locations (indicated by # signs). Then we will visit the matrix in spiral order.
For a 4 * 4 grid (even * even):
O O O O
O O O O
O O O O
O O O O
The signs will be like this:
O O O #
# O # O
O # # O
# O O #
For a 4 * 5 grid (even * odd):
O O O O O
O O O O O
O O O O O
O O O O O
The signs will be like this:
O O O O #
# O O # O
O # O # O
# O O O #
For a 5 * 4 grid (odd * even):
O O O O
O O O O
O O O O
O O O O
O O O O
The signs will be like this:
O O O #
# O # O
O # O O
O # # O
# O O #
For a 5 * 5 grid (odd * odd):
O O O O O
O O O O O
O O O O O
O O O O O
O O O O O
The signs will be like this:
O O O O #
# O O # O
O # # O O
O # O # O
# O O O #
We can divide the grid in 4 parts and then follow some patterns.
4 parts will be:
1) top-left (lets call it a)
2) top-right (lets call it b)
3) bottom-right (lets call it c)
4) bottom-left (lets call it d)
So 6 * 6 grid will be divided like:
a a a b b b
a a a b b b
a a a b b b
d d d c c c
d d d c c c
d d d c c c
Now for most of the points we can easily decide in which part they will fall, except points which are horizontally centered or vertically centered. Horizontally centered points: Consider them in top parts. Vertically centered points: Consider them in right parts.
So 5 * 7 grid will be divided like:
a a a b b b b
a a a b b b b
a a a b b b b
d d d c c c c
d d d c c c c
Now again look at the grid:
O O O O O O #
# O O O O # O
O # O O # O O
O # O O O # O
# O O O O O #
and try to find patterns from parts:
O O O O O O #
# O O O O # O
O # O O # O O
O # O O O # O
# O O O O O #
For top-right, bottom-right and bottom-left pattern is same!
If matrix size is rows * cols then for any point (at position cur_row and cur_col) if we want to check if there is a sign or not simply check:
1) top-right: cur_row == cols – 1 – cur_col
2) bottom-right: rows – 1 – cur_row == cols – 1 – cur_col
3) bottom-left: rows – 1 – cur_row == cur_col
We can write conditions separately or combine them as:
min(cur_row, rows – 1 – cur_row) == min(cur_col, cols – 1 – cur_col) ……(1)
Now for the top-left part we need to check:
cur_row == cur_col + 1 ……(2)
Now you know where to put the signs! How to check if point is in top-left or other parts?
/*
Consider these grids to understand what the below code does.
O O O O O O #
# O O O O # O
O # O O # O O
O # O O O # O
# O O O O O #
=
O O O O O O #
# O O O O # O
O # O O # O O
O # O O O # O
# O O O O O #
< (rows + 1) / 2 will give priority to top part when current position is horizontally centered.
< cols / 2 will give priority to right part when current position is vertically centered.
*/
if ((cur_row < (rows + 1) / 2) && (cur_col < cols / 2))
{
// Condition to turn when current position is in top-left part.
}
else
{
// Condition to turn when current position in other parts.
}
Time Complexity:
O(rows * cols).
We are traversing the whole vector once.
Auxiliary Space Used:
O(1).
Space Complexity:
O(rows * cols).
// -------- START --------
int directions[4][2] =
{
// {row, col}
{0, 1}, // go right
{1, 0}, // go down
{0, -1}, // go left
{-1, 0} // go up.
};
bool should_turn(int cur_row, int cur_col, int rows, int cols)
{
/*
Consider these grids to understand what the below code does.
O O O O O O #
# O O O O # O
O # O O # O O
O # O O O # O
# O O O O O #
=
O O O O O O #
# O O O O # O
O # O O # O O
O # O O O # O
# O O O O O #
< (rows + 1) / 2 will give priority to top part when current position is horizontally
centered.
< cols / 2 will give priority to right part when current position is vertically centered.
*/
// Check if position is in top-left part.
if ((cur_row < (rows + 1) / 2) && (cur_col < cols / 2))
{
// Condition to turn when current position is in top-left part.
return cur_row == cur_col + 1;
}
// Condition to turn when current position in other parts.
return min(cur_row, rows - 1 - cur_row) == min(cur_col, cols - 1 - cur_col);
}
string printSpirally(vector<vector> matrix)
{
int rows = matrix.size();
int cols = matrix[0].size();
int total = rows * cols;
string ans(total, ' ');
// Initial position is at top left corner with direction towards right.
int direction = 0;
int cur_row = 0, cur_col = 0;
for (int i = 0; i < total; i++)
{
ans[i] = matrix[cur_row][cur_col];
// Check if we should turn our direction or not.
if (should_turn(cur_row, cur_col, rows, cols))
{
direction = (direction + 1) % 4;
}
// Update the position.
cur_row += directions[direction][0];
cur_col += directions[direction][1];
}
return ans;
}
// -------- END --------
</vector Master ML interviews with DSA, ML System Design, Supervised/Unsupervised Learning, DL, and FAANG-level interview prep.
Get strategies to ace TPM interviews with training in program planning, execution, reporting, and behavioral frameworks.
Course covering SQL, ETL pipelines, data modeling, scalable systems, and FAANG interview prep to land top DE roles.
Course covering Embedded C, microcontrollers, system design, and debugging to crack FAANG-level Embedded SWE interviews.
Nail FAANG+ Engineering Management interviews with focused training for leadership, Scalable System Design, and coding.
End-to-end prep program to master FAANG-level SQL, statistics, ML, A/B testing, DL, and FAANG-level DS interviews.
Time Zone:
Join 25,000+ tech professionals who’ve accelerated their careers with cutting-edge AI skills
25,000+ Professionals Trained
₹23 LPA Average Hike 60% Average Hike
600+ MAANG+ Instructors
Webinar Slot Blocked
Register for our webinar
Learn about hiring processes, interview strategies. Find the best course for you.
ⓘ Used to send reminder for webinar
Time Zone: Asia/Kolkata
Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
Explore your personalized path to AI/ML/Gen AI success
The 11 Neural “Power Patterns” For Solving Any FAANG Interview Problem 12.5X Faster Than 99.8% OF Applicants
The 2 “Magic Questions” That Reveal Whether You’re Good Enough To Receive A Lucrative Big Tech Offer
The “Instant Income Multiplier” That 2-3X’s Your Current Tech Salary