mdipierro
55 lines
1.4 KiB
Python
55 lines
1.4 KiB
Python
# run with web2py.py -S welcome -N -R thisfile.py
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import time
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db=DAL()
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db.define_table('test',Field('one'))
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db(db.test).delete()
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for k in range(1000):
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db.test.insert(one='one')
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db.commit()
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n = 100
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t0 = time.time()
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for k in range(n):
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y = db.test.one
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print 'time to access field obj',(time.time()-t0)/n
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t0 = time.time()
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for k in range(n):
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rows = db(db.test).select(cacheable=False) # (*)
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print 'time to select 1000 recods',(time.time()-t0)/n/1000
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row = db(db.test).select().first()
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t0 = time.time()
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for k in range(n):
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y = row.id
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y = row.one
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print 'time to access field values',(time.time()-t0)/n
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"""
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Results:
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web2py 1.99.7
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time to access field obj 5.068 (microseconds)
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time to select 1000 recods 38.441 (microseconds)
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time to access field values 7.710 (microseconds)
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total time to access one field for each of 1000 records: 7748 (microseconds)
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web2py 2.0
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time to access field obj 0.579 (microseconds)
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time to select 1000 recods 33.820 (microseconds)
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time to access field values 0.338 (microseconds)
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total time to access one field for each of 1000 records: 371 (microseconds)
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web2py 2.0 w cacheable = True (*)
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time to access field obj 0.579 (microseconds)
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time to select 1000 recods 24.741 (microseconds)
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time to access field values 0.300 (microseconds)
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total time to access one field for each of 1000 records: 324 (microseconds)
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(benhcmarks with SQLite on Mac Air and python 2.7)
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"""
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