As part of chemfp I've started doing benchmarking. I noticed that 2.3's SDF
parsing speed is about 1/2 that of 2.2. I don't recall hearing about that. Has
anyone else seen a similar slowdown?
In the following, the "23150" is the number of structures read, and the next
field on the line is the total time.
% env BABEL_LIBDIR=/Users/dalke/envs/openbabel-2.2.3-x86/lib/openbabel/2.2.3
BABEL_DATADIR=/Users/dalke/envs/openbabel-2.2.3-x86/share/openbabel/2.2.3
DYLD_LIBRARY_PATH=/Users/dalke/envs/openbabel-2.2.3-x64/lib
PYTHONPATH=/Users/dalke/envs/py27-ob223/lib/python2.7/site-packages/
/Users/dalke/envs/py27-ob223/bin/python2.7 read_time.py
23150 11.9479241371
% env BABEL_LIBDIR=/Users/dalke/envs/openbabel-2.3.0-x64/lib/openbabel/2.3.0
BABEL_DATADIR=/Users/dalke/envs/openbabel-2.3.0-x64/share/openbabel/2.3.0
DYLD_LIBRARY_PATH=/Users/dalke/envs/openbabel-2.3.0-x64/lib
PYTHONPATH=/Users/dalke/envs/openbabel-2.3.0-x64/lib/python2.7/site-packages
/Users/dalke/envs/py27-ob230/bin/python2.7 read_time.py
23150 28.779763937
The benchmark code is essentially
import time
filename =
"/Users/dalke/databases/pubchem/Compound_000000001_000025000.sdf.gz"
import openbabel as ob
obconversion = ob.OBConversion()
obconversion.SetInFormat("sdf")
obmol = ob.OBMol()
notatend = obconversion.ReadFile(obmol, filename)
n = 0
t1 = time.time()
while notatend:
n += 1
# reuse the molecule for 0.3 seconds of savings vs. making an new one
obmol.Clear()
notatend = obconversion.Read(obmol)
print n, time.time()-t1
("Essentially" because the timing tests use chemfp code; I used the above to
verify that the raw OpenBabel API matched one of my chemfp times.)
Andrew
da...@dalkescientific.com
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