I had terrible memory problems using Python on larger graphs (1M+ V/E). Weird memory usage happened and even 64GB filled up fast. For example, the everything i

I had terrible memory problems using Python on larger graphs (1M+ V/E). Weird memory usage happened and even 64GB filled up fast. For example, the everything is a dictionary approach that widely used NetworkX library utilizes was a horrible memory gobbler on large graphs. It sounds very nice in theory, works well on smaller graphs but is near useless for larger ones. The best graph tool that I found for larger graphs was graph-tool which is heavily NumPy based. When I write in C, at least I know where my memory goes.