[graph-tool-tickets] [graph-tool] Page: Performance changed

graph-tool webmaster at skewed.de
Wed Mar 6 19:43:22 UTC 2013


 * The user 'tiago peixoto' has changed the page: Performance.
 * Diff link: <URL:http://graph-tool.skewed.de/wiki/Performance?action=diff&version=20> 

Index: Performance
==============================================================================
--- Performance (version: 19)
+++ Performance (version: 20)
@@ -55,7 +55,7 @@
 
 * The igraph library requires less resources for compilation, and comes with additional bindings for the R and C languages which the other two lack.
 
-* NetworkX is comparatively very inefficient, but it is trivial to install --- requiring no compilation at all, since it is pure python. Thus one can get started with very little to no effort. The speed may not be a problem if one is dealing with small graphs, and does not care if an algorithm runs in 1 or 30 seconds.  However, if the graph size increases to hundreds of thousand or millions of vertices/edges, this difference can scale up to 1 day vs. 1 month, or one month vs. several years, which may be prohibitively slow.
+* NetworkX is comparatively very inefficient, but it is trivial to install --- requiring no compilation at all, since it is pure python. Thus one can get started with very little to no effort. The speed may not be a problem if one is dealing with small graphs, and does not care if an algorithm runs in, say, 1 or 30 seconds.  However, if the graph size increases to hundreds of thousand or millions of vertices/edges, this difference can scale up to tens of days vs. several years, which is quite significant.
 
 Additionally, these libraries have different APIs and handle things
 slightly differently, and they may appeal to different user

--
Page URL: <URL:http://graph-tool.skewed.de/wiki/Performance>
graph-tool <URL:http://graph-tool.skewed.de/>
An efficient python module for graph analysis and manipulation.
-------------- next part --------------
 * The user 'tiago peixoto' has changed the page: Performance.
 * Diff link: <URL:http://graph-tool.skewed.de/wiki/Performance?action=diff&version=20> 

Index: Performance
==============================================================================
--- Performance (version: 19)
+++ Performance (version: 20)
@@ -55,7 +55,7 @@
 
 * The igraph library requires less resources for compilation, and comes with additional bindings for the R and C languages which the other two lack.
 
-* NetworkX is comparatively very inefficient, but it is trivial to install --- requiring no compilation at all, since it is pure python. Thus one can get started with very little to no effort. The speed may not be a problem if one is dealing with small graphs, and does not care if an algorithm runs in 1 or 30 seconds.  However, if the graph size increases to hundreds of thousand or millions of vertices/edges, this difference can scale up to 1 day vs. 1 month, or one month vs. several years, which may be prohibitively slow.
+* NetworkX is comparatively very inefficient, but it is trivial to install --- requiring no compilation at all, since it is pure python. Thus one can get started with very little to no effort. The speed may not be a problem if one is dealing with small graphs, and does not care if an algorithm runs in, say, 1 or 30 seconds.  However, if the graph size increases to hundreds of thousand or millions of vertices/edges, this difference can scale up to tens of days vs. several years, which is quite significant.
 
 Additionally, these libraries have different APIs and handle things
 slightly differently, and they may appeal to different user

--
Page URL: <URL:http://graph-tool.skewed.de/wiki/Performance>
graph-tool <URL:http://graph-tool.skewed.de/>
An efficient python module for graph analysis and manipulation.


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