Skip to content

Python GraphBLAS

Chapter 1

Interactive Notebook

Summary

This chapter covers installing and using GraphBLAS libraries with practical examples:

  • Installation - Installing Python-GraphBLAS via pip, with SuiteSparse as the underlying implementation
  • Language Bindings - Overview of GraphBLAS bindings for Python, Julia, and PostgreSQL
  • COO Format - Creating sparse vectors and matrices using coordinate (COO) format with indices and values arrays
  • Sparse Representation - Understanding why zeros are not stored in sparse data structures
  • Matrix-Vector Multiplication - Using the mxv operation and @ operator shorthand for graph traversal
  • GraphBLAS Assignment - The << operator for writing results back to vectors and matrices
  • Breadth-First Search - Implementing BFS as repeated matrix-vector multiplication, discovering frontier neighbors through linear algebra