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# monkeypatch the "cdecimal" library in.
# this is a drop-in replacement for "decimal".
# All SQLA versions support cdecimal except
# for the MS-SQL dialect, which is fixed in 0.7
try:
import cdecimal
import sys
sys.modules['decimal'] = cdecimal
except ImportError:
pass
from sqlalchemy import __version__
from sqlalchemy import Column, Integer, create_engine, ForeignKey, \
String, Numeric
if __version__ < "0.6":
from sqlalchemy.orm.session import Session
from sqlalchemy.orm import relation as relationship
else:
from sqlalchemy.orm import Session, relationship
from sqlalchemy.ext.declarative import declarative_base
import random
import os
from decimal import Decimal
Base = declarative_base()
class Employee(Base):
__tablename__ = 'employee'
id = Column(Integer, primary_key=True)
name = Column(String(100), nullable=False)
type = Column(String(50), nullable=False)
__mapper_args__ = {'polymorphic_on':type}
class Boss(Employee):
__tablename__ = 'boss'
id = Column(Integer, ForeignKey('employee.id'), primary_key=True)
golf_average = Column(Numeric)
__mapper_args__ = {'polymorphic_identity':'boss'}
class Grunt(Employee):
__tablename__ = 'grunt'
id = Column(Integer, ForeignKey('employee.id'), primary_key=True)
savings = Column(Numeric)
employer_id = Column(Integer, ForeignKey('boss.id'))
# Configure an 'employer' relationship, where Grunt references
# Boss. This is a joined-table subclass to subclass relationship,
# which is a less typical case.
# In 0.7, "Boss.id" is the "id" column of "boss", as would be expected.
if __version__ >= "0.7":
employer = relationship("Boss", backref="employees",
primaryjoin=Boss.id==employer_id)
# Prior to 0.7, "Boss.id" is the "id" column of "employee".
# Long story. So we hardwire the relationship against the "id"
# column of Boss' table.
elif __version__ >= "0.6":
employer = relationship("Boss", backref="employees",
primaryjoin=Boss.__table__.c.id==employer_id)
# In 0.5, the many-to-one loader wouldn't recognize the above as a
# simple "identity map" fetch. So to give 0.5 a chance to emit
# the same amount of SQL as 0.6, we hardwire the relationship against
# "employee.id" to work around the bug.
else:
employer = relationship("Boss", backref="employees",
primaryjoin=Employee.__table__.c.id==employer_id,
foreign_keys=employer_id)
__mapper_args__ = {'polymorphic_identity':'grunt'}
if os.path.exists('orm2010.db'):
os.remove('orm2010.db')
# use a file based database so that cursor.execute() has some
# palpable overhead.
engine = create_engine('sqlite:///orm2010.db')
Base.metadata.create_all(engine)
sess = Session(engine)
def runit():
# create 1000 Boss objects.
bosses = [
Boss(
name="Boss %d" % i,
golf_average=Decimal(random.randint(40, 150))
)
for i in range(1000)
]
sess.add_all(bosses)
# create 10000 Grunt objects.
grunts = [
Grunt(
name="Grunt %d" % i,
savings=Decimal(random.randint(5000000, 15000000) / 100)
)
for i in range(10000)
]
# Assign each Grunt a Boss. Look them up in the DB
# to simulate a little bit of two-way activity with the
# DB while we populate. Autoflush occurs on each query.
# In 0.7 executemany() is used for all the "boss" and "grunt"
# tables since priamry key fetching is not needed.
while grunts:
boss = sess.query(Boss).\
filter_by(name="Boss %d" % (101 - len(grunts) / 100)).\
first()
for grunt in grunts[0:100]:
grunt.employer = boss
grunts = grunts[100:]
sess.commit()
report = []
# load all the Grunts, print a report with their name, stats,
# and their bosses' stats.
for grunt in sess.query(Grunt):
# here, the overhead of a many-to-one fetch of
# "grunt.employer" directly from the identity map
# is less than half of that of 0.6.
report.append((
grunt.name,
grunt.savings,
grunt.employer.name,
grunt.employer.golf_average
))
import cProfile, os, pstats
filename = "orm2010.profile"
cProfile.runctx('runit()', globals(), locals(), filename)
stats = pstats.Stats(filename)
counts_by_methname = dict((key[2], stats.stats[key][0]) for key in stats.stats)
print("SQLA Version: %s" % __version__)
print("Total calls %d" % stats.total_calls)
print("Total cpu seconds: %.2f" % stats.total_tt)
print('Total execute calls: %d' \
% counts_by_methname["<method 'execute' of 'sqlite3.Cursor' "
"objects>"])
print('Total executemany calls: %d' \
% counts_by_methname.get("<method 'executemany' of 'sqlite3.Cursor' "
"objects>", 0))
#stats.sort_stats('time', 'calls')
#stats.print_stats()
os.system("runsnake %s" % filename)
# SQLA Version: 0.7b1
# Total calls 4956750
# Total execute calls: 11201
# Total executemany calls: 101
# SQLA Version: 0.6.6
# Total calls 7963214
# Total execute calls: 22201
# Total executemany calls: 0
# SQLA Version: 0.5.8
# Total calls 10556480
# Total execute calls: 22201
# Total executemany calls: 0
|
