NetworkX can draw graphs that can be annotated using the matplotlib drawing tools because the result of nx.draw is a matplotlib figure on which you can use matplotlib to draw anything else you'd like on top of the networkx drawing of the graph.

This idea is motivated by this SO post:

• https://stackoverflow.com/questions/66221054/3-dimensional-graph-lightgraphs-graphplot-julia-or-networkx-py

steps to reproduce

Write a loop, from 1 to 80000, each time add a random int to the max heap.

In theory it takes very little time(NlogN, N=80000, <1sec ), but the program does take a long time.

I'v also tested the BinaryHeap in https://github.com/SolutionsDesign/Algorithmia, it performs well, so it is probably due to the bad algorithm.

We need to move the execution of CLI scripts used to build the documentation into a Make file. Wise suggestion from @louisguitton: DerwenAI/pytextrank#159 (comment)

Feature description (Mandatory)

Please add the capability to specify the type of array instead of defaulting to string. i.e.
apoc.array.int()

How this feature can improve the project?

By default, it is created as a string. Some customers have asked for the ability to hint at the data type.

The igraph tutorial (here online, source file here) should be reviewed:

• Is it up to date?
• Is it understandable by a newcomer?
• Are essential points unexplained or missing?

Ideally, this should be done by someone who is new to using igraph, to get a fresh perspective. Th

I have a gh graph on 37700 vertices and 289003 edges.

Calculation of its diameter like this:

maximum(maximum(gdistances(gh, i)) for i in vertices(gh))

takes around 250 seconds (probably this is not an optimal algorithm for the task but at least it works).

However, when I run diameter(gh) the process takes so long that I did not wait till it finished.