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from decimal import Decimal
import os
import random
from sqlalchemy import __version__
from sqlalchemy import Column
from sqlalchemy import create_engine
from sqlalchemy import ForeignKey
from sqlalchemy import Integer
from sqlalchemy import Numeric
from sqlalchemy import String
from sqlalchemy.orm import declarative_base
from sqlalchemy.orm import relationship
from sqlalchemy.orm import Session
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"))
employer = relationship(
"Boss", backref="employees", primaryjoin=Boss.id == 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_persist(status, factor=1, query_runs=5):
num_bosses = 100 * factor
num_grunts = num_bosses * 100
bosses = [
Boss(name="Boss %d" % i, golf_average=Decimal(random.randint(40, 150)))
for i in range(num_bosses)
]
sess.add_all(bosses)
status("Added %d boss objects" % num_bosses)
grunts = [
Grunt(
name="Grunt %d" % i,
savings=Decimal(random.randint(5000000, 15000000) / 100),
)
for i in range(num_grunts)
]
status("Added %d grunt objects" % num_grunts)
while grunts:
# this doesn't associate grunts with bosses evenly,
# just associates lots of them with a relatively small
# handful of bosses
batch_size = 100
batch_num = (num_grunts - len(grunts)) / batch_size
boss = sess.query(Boss).filter_by(name="Boss %d" % batch_num).first()
for grunt in grunts[0:batch_size]:
grunt.employer = boss
grunts = grunts[batch_size:]
sess.commit()
status("Associated grunts w/ bosses and committed")
def runit_query_runs(status, factor=1, query_runs=5):
# do some heavier reading
for i in range(query_runs):
status("Heavy query run #%d" % (i + 1))
report = []
# load all the Grunts, print a report with their name, stats,
# and their bosses' stats.
for grunt in sess.query(Grunt):
report.append(
(
grunt.name,
grunt.savings,
grunt.employer.name,
grunt.employer.golf_average,
)
)
sess.close() # close out the session
def run_with_profile(runsnake=False, dump=False):
import cProfile
import pstats
filename = "orm2010.profile"
if os.path.exists("orm2010.profile"):
os.remove("orm2010.profile")
def status(msg):
print(msg)
cProfile.runctx(
# "runit_persist(status)",
"runit_persist(status); runit_query_runs(status)",
globals(),
locals(),
filename,
)
stats = pstats.Stats(filename)
counts_by_methname = {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
)
)
if dump:
# stats.sort_stats("nfl")
stats.sort_stats("cumtime", "calls")
stats.print_stats()
# stats.print_callers()
if runsnake:
os.system("runsnake %s" % filename)
def run_with_time(factor):
import time
now = time.time()
def status(msg):
print("%d - %s" % (time.time() - now, msg))
runit_persist(status, factor)
print("Total time: %d" % (time.time() - now))
runit_query_runs(status, factor)
print("Total time: %d" % (time.time() - now))
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"--profile",
action="store_true",
help="run shorter test suite w/ cprofilng",
)
parser.add_argument(
"--dump",
action="store_true",
help="dump full call profile (implies --profile)",
)
parser.add_argument(
"--runsnake",
action="store_true",
help="invoke runsnakerun (implies --profile)",
)
parser.add_argument(
"--factor",
type=int,
default=10,
help="scale factor, a multiple of how many records to work with. "
"defaults to 10",
)
args = parser.parse_args()
args.profile = args.profile or args.dump or args.runsnake
if args.profile:
run_with_profile(runsnake=args.runsnake, dump=args.dump)
else:
run_with_time(args.factor)
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