SQLAlchemy stress test

#!flask/bin/python
import sys
from time import time

from app import database
from app.modules.user_manager import models as user

# Query once, filter each time
t = time()
q = database.session.query(user.User)
for i in range(10000):
    # r = database.session.query(user.User).filter(
    #         user.User.username == 'brandonm').all()
    r = q.filter(user.User.username == 'brandonm').all()
    for result in r:
        assert result.display == 'Brandon Morris'
print('New query each time: {:.2f}'.format(time() - t))

# Query every time
t = time()
q = database.session.query(user.User)
for i in range(10000):
    # r = database.session.query(user.User).filter(
    #         user.User.username == 'brandonm').all()
    r = q.filter(user.User.username == 'brandonm').all()
    for result in r:
        assert result.display == 'Brandon Morris'
print('New filter each time: {:.2f}'.format(time() - t))

# Query once, dict lookup
t = time()
all = database.session.query(user.User).all()
name_to_display = dict()
for user in all:
    name_to_display[user.username] = user.display

for i in range(10000):
    assert name_to_display['brandonm'] == 'Brandon Morris'
print('Cache lookup: {:.4f}'.format(time() - t))

Running this on my machine, I got the following results:

New query each time: 7.56
New filter each time: 7.57
Cache lookup: 0.0027

So it seems SQLAlchemy doesn't do any kind of caching for its queries