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import time
from datetime import datetime
from sqlalchemy import *
from sqlalchemy.orm import *
from sqlalchemy.test import *
from sqlalchemy.test.profiling import profiled
class Item(object):
def __repr__(self):
return 'Item<#%s "%s">' % (self.id, self.name)
class SubItem(object):
def __repr__(self):
return 'SubItem<#%s "%s">' % (self.id, self.name)
class Customer(object):
def __repr__(self):
return 'Customer<#%s "%s">' % (self.id, self.name)
class Purchase(object):
def __repr__(self):
return 'Purchase<#%s "%s">' % (self.id, self.purchase_date)
items, subitems, customers, purchases, purchaseitems = \
None, None, None, None, None
metadata = MetaData()
@profiled('table')
def define_tables():
global items, subitems, customers, purchases, purchaseitems
items = Table('items', metadata,
Column('id', Integer, primary_key=True),
Column('name', String(100)),
test_needs_acid=True)
subitems = Table('subitems', metadata,
Column('id', Integer, primary_key=True),
Column('item_id', Integer, ForeignKey('items.id'),
nullable=False),
Column('name', String(100), server_default='no name'),
test_needs_acid=True)
customers = Table('customers', metadata,
Column('id', Integer, primary_key=True),
Column('name', String(100)),
*[Column("col_%s" % chr(i), String(64), default=str(i))
for i in range(97,117)],
**dict(test_needs_acid=True))
purchases = Table('purchases', metadata,
Column('id', Integer, primary_key=True),
Column('customer_id', Integer,
ForeignKey('customers.id'), nullable=False),
Column('purchase_date', DateTime,
default=datetime.now),
test_needs_acid=True)
purchaseitems = Table('purchaseitems', metadata,
Column('purchase_id', Integer,
ForeignKey('purchases.id'),
nullable=False, primary_key=True),
Column('item_id', Integer, ForeignKey('items.id'),
nullable=False, primary_key=True),
test_needs_acid=True)
@profiled('mapper')
def setup_mappers():
mapper(Item, items, properties={
'subitems': relationship(SubItem, backref='item', lazy='select')
})
mapper(SubItem, subitems)
mapper(Customer, customers, properties={
'purchases': relationship(Purchase, lazy='select', backref='customer')
})
mapper(Purchase, purchases, properties={
'items': relationship(Item, lazy='select', secondary=purchaseitems)
})
@profiled('inserts')
def insert_data():
q_items = 1000
q_sub_per_item = 10
q_customers = 1000
con = testing.db.connect()
transaction = con.begin()
data, subdata = [], []
for item_id in xrange(1, q_items + 1):
data.append({'name': "item number %s" % item_id})
for subitem_id in xrange(1, (item_id % q_sub_per_item) + 1):
subdata.append({'item_id': item_id,
'name': "subitem number %s" % subitem_id})
if item_id % 100 == 0:
items.insert().execute(*data)
subitems.insert().execute(*subdata)
del data[:]
del subdata[:]
if data:
items.insert().execute(*data)
if subdata:
subitems.insert().execute(*subdata)
transaction.commit()
transaction = con.begin()
data = []
for customer_id in xrange(1, q_customers):
data.append({'name': "customer number %s" % customer_id})
if customer_id % 100 == 0:
customers.insert().execute(*data)
del data[:]
if data:
customers.insert().execute(*data)
transaction.commit()
transaction = con.begin()
data, subdata = [], []
order_t = int(time.time()) - (5000 * 5 * 60)
current = xrange(1, q_customers)
step, purchase_id = 1, 0
while current:
next = []
for customer_id in current:
order_t += 300
data.append({'customer_id': customer_id,
'purchase_date': datetime.fromtimestamp(order_t)})
purchase_id += 1
for item_id in range(customer_id % 200, customer_id + 1, 200):
if item_id != 0:
subdata.append({'purchase_id': purchase_id,
'item_id': item_id})
if customer_id % 10 > step:
next.append(customer_id)
if len(data) >= 100:
purchases.insert().execute(*data)
if subdata:
purchaseitems.insert().execute(*subdata)
del data[:]
del subdata[:]
step, current = step + 1, next
if data:
purchases.insert().execute(*data)
if subdata:
purchaseitems.insert().execute(*subdata)
transaction.commit()
@profiled('queries')
def run_queries():
session = create_session()
# no explicit transaction here.
# build a report of summarizing the last 50 purchases and
# the top 20 items from all purchases
q = session.query(Purchase). \
order_by(desc(Purchase.purchase_date)). \
limit(50).\
options(joinedload('items'), joinedload('items.subitems'),
joinedload('customer'))
report = []
# "write" the report. pretend it's going to a web template or something,
# the point is to actually pull data through attributes and collections.
for purchase in q:
report.append(purchase.customer.name)
report.append(purchase.customer.col_a)
report.append(purchase.purchase_date)
for item in purchase.items:
report.append(item.name)
report.extend([s.name for s in item.subitems])
# mix a little low-level with orm
# pull a report of the top 20 items of all time
_item_id = purchaseitems.c.item_id
top_20_q = select([func.distinct(_item_id).label('id')],
group_by=[purchaseitems.c.purchase_id, _item_id],
order_by=[desc(func.count(_item_id)), _item_id],
limit=20)
ids = [r.id for r in top_20_q.execute().fetchall()]
q2 = session.query(Item).filter(Item.id.in_(ids))
for num, item in enumerate(q2):
report.append("number %s: %s" % (num + 1, item.name))
@profiled('creating')
def create_purchase():
# commit a purchase
customer_id = 100
item_ids = (10,22,34,46,58)
session = create_session()
session.begin()
customer = session.query(Customer).get(customer_id)
items = session.query(Item).filter(Item.id.in_(item_ids))
purchase = Purchase()
purchase.customer = customer
purchase.items.extend(items)
session.flush()
session.commit()
session.expire(customer)
def setup_db():
metadata.drop_all()
metadata.create_all()
def cleanup_db():
metadata.drop_all()
@profiled('default')
def default():
run_queries()
create_purchase()
@profiled('all')
def main():
metadata.bind = testing.db
try:
define_tables()
setup_mappers()
setup_db()
insert_data()
default()
finally:
cleanup_db()
main()
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