Sparse Matrix Class Implementation | Dataford Interview Questions

Describe how you would implement a sparse matrix class and the key operations you would support efficiently.

Implement sparse_matrix_operations(rows, cols, operations). Store only nonzero values. Each operation is a dictionary: set, add, get, transpose, multiply, or dense. Return one result per operation, using null for updates. A multiplication operand has rows, cols, and an entries list of [row, column, value].

The matrix dimensions are valid, indices are zero-based, and multiplication dimensions are compatible.

Constraints

1 <= rows, cols <= 10^4
At most 10^5 nonzero entries are stored
0 <= row < rows and 0 <= col < cols
Values are integers in the range -10^9 to 10^9
All multiplication operands have compatible dimensions
The input operation sequence contains at least one operation

Function Signature

def sparse_matrix_operations(rows, cols, operations):

Your question is Sparse Matrix Class Implementation. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Describe how you would implement a sparse matrix class and the key operations you would support efficiently.

The matrix dimensions are valid, indices are zero-based, and multiplication dimensions are compatible.

Constraints

1 <= rows, cols <= 10^4
At most 10^5 nonzero entries are stored
0 <= row < rows and 0 <= col < cols
Values are integers in the range -10^9 to 10^9
All multiplication operands have compatible dimensions
The input operation sequence contains at least one operation

Function Signature

def sparse_matrix_operations(rows, cols, operations):

Your question is Sparse Matrix Class Implementation. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.