# Graph vertex and edge attributes

**URL:** <https://discourse.julialang.org/t/graph-vertex-and-edge-attributes/82234>\
**Category:** Graphs\
**Tags:** graphs\
**Created:** [June 4, 2022, 1:01pm UTC](https://discourse.julialang.org/t/graph-vertex-and-edge-attributes/82234 "2022-06-04T13:01:16Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![jlapeyre](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jlapeyre/32/4514_2.png) [@jlapeyre](https://discourse.julialang.org/u/jlapeyre)\
**Post date:** [June 4, 2022, 7:06pm UTC](https://discourse.julialang.org/t/graph-vertex-and-edge-attributes/82234/5 "2022-06-04T19:06:29Z")

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In [this post](https://discourse.julialang.org/t/retworkx-new-high-performance-python-graph-library/71109) I offered a specific example of what I mean by “rather poor”.

> [@Retworkx: new, high-performance Python graph library](https://discourse.julialang.org/t/retworkx-new-high-performance-python-graph-library/71109/1):
>
> I could even parse the weights and put them in an Array and be fast. I just could not put them in a graph structure without taking five times longer than (pure-Python) networkx.

For the particular problem I was working on, the more performant of of `MetaGraphs` and `SimpleWeightedGraphs` was five times slower than (the famoulsy slow) networkx at reading and building a graph. But, I did _not_ try `MetaGraphsNext`, and IIUC one of the goals there is better performance. Also, I should reiterate that, 1) if you carry the metadata yourself in another structure, then Graphs.jl is very performant. 2) My experience is very limited, I tried only one problem of one size.

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