Which is fastest dict or list.index() ?

[VanL]

Hello,

I am curious about your experience with these BTrees.  I am 
writing an outliner with a ZODB backend in which I was going 
to use these as nodes for storage (IOBTrees, probably) as 
opposed to the supplied PersistentDict class.

I was planning on using a data structure that (with 
extraneous stuff ommitted) looked like this:

(Note: ObjID is a unique int.)

BTree(ObjID_1: {'Content': <Stuff>,
           'Connections': [Parent_ObjID,
            ObjID_child1, ObjID_child2, etc]
           'ID': ObjID},
ObjID_2: {'Content': <Stuff>,
           'Connections': [Parent_ObjID,
            ObjID_child1, ObjID_child2, etc]
           'ID': ObjID},
etc.

(This is an extension of the 'ideal python graph model' as 
expounded by Guido at 
http://www.python.org/doc/essays/graphs.html)

The content of the various nodes (the <stuff> above) could 
potentially be quite large (500 k -> 1MB per node), so I was 
thinking that the BTree might be better, as it would only 
bring the necessary nodes into memory.

However, your mention that these Btrees are 'sluggish' 
grabbed my attention.  Would it be better to pay the memory 
price for speedier performance?

I guess I am asking what you mean by sluggish. Sluggish as 
in "I get 10,000 ops per second on a Btree, but 100,000 ops 
per second on a dict" or sluggish as in "I only get 10 ops 
per second on a Btree because I have to go to disk every 
time I pull a node?"

Thanks,

VanL

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