👀 Views: 98 💬 Answers: 1 📅 Created: 2025-06-12

python sparse-matrix performance Python

I'm attempting to set up I'm working through a tutorial and I've been banging my head against this for hours... I'm currently working on implementing a sparse matrix representation using a dictionary of lists in Python to efficiently store and manipulate large matrices. However, I'm noticing significant performance issues when attempting to perform matrix multiplication, particularly with larger matrices. My implementation uses a dictionary where the keys are the row indices and the values are lists of non-zero tuples (column index, value). The multiplication logic iterates through each non-zero entry in the first matrix and looks for matching entries in the second matrix, but it seems to be running into performance bottlenecks. Here's a snippet of my current implementation for the multiplication: ```python class SparseMatrix: def __init__(self): self.data = {} def add_value(self, row, col, value): if row not in self.data: self.data[row] = [] self.data[row].append((col, value)) def multiply(self, other): result = SparseMatrix() for row in self.data: for (col1, val1) in self.data[row]: if col1 in other.data: for (col2, val2) in other.data[col1]: result.add_value(row, col2, val1 * val2) return result ``` When I multiply two sparse matrices where one has dimensions of 1000x1000 with approximately 10% non-zero entries, the operation takes an unacceptably long time (over 30 seconds). I'm running this on Python 3.9 and using a standard dictionary for storage. I’ve tried optimizing the inner loop by using a set to store the column indices of the second matrix temporarily, but it didn't yield significant improvements. I also considered using NumPy for better performance but am unsure how to effectively leverage it for a sparse matrix polynomial representation. Any guidance on optimizing this multiplication process or recommendations for alternative libraries that might handle this more efficiently would be greatly appreciated. Here’s the output I get when running my multiplication code: ``` Error: Execution timeout after 30 seconds. ``` For context: I'm using Python on Linux. This issue appeared after updating to Python LTS. How would you solve this? I'm working with Python in a Docker container on Debian. What's the correct way to implement this?