来自@zzzeek 的出色回答。对于那些想知道查询的相同统计信息的人，我稍微修改了@zzzeek 代码以在插入它们后立即查询这些相同的记录，然后将这些记录转换为字典列表。
这是结果
SqlAlchemy ORM: Total time for 100000 records 11.9210000038 secs
SqlAlchemy ORM query: Total time for 100000 records 2.94099998474 secs
SqlAlchemy ORM pk given: Total time for 100000 records 7.51800012589 secs
SqlAlchemy ORM pk given query: Total time for 100000 records 3.07699990273 secs
SqlAlchemy Core: Total time for 100000 records 0.431999921799 secs
SqlAlchemy Core query: Total time for 100000 records 0.389000177383 secs
sqlite3: Total time for 100000 records 0.459000110626 sec
sqlite3 query: Total time for 100000 records 0.103999853134 secs
有趣的是，使用裸 sqlite3 进行查询仍然比使用 SQLAlchemy Core 快大约 3 倍。我想这就是你为返回 ResultProxy 而不是裸的 sqlite3 行所付出的代价。
SQLAlchemy Core 比使用 ORM 快大约 8 倍。所以无论如何使用 ORM 查询都会慢很多。
这是我使用的代码：
import time
import sqlite3
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, create_engine
from sqlalchemy.orm import scoped_session, sessionmaker
from sqlalchemy.sql import select
Base = declarative_base()
DBSession = scoped_session(sessionmaker())
class Customer(Base):
__tablename__ = "customer"
id = Column(Integer, primary_key=True)
name = Column(String(255))
def init_sqlalchemy(dbname = 'sqlite:///sqlalchemy.db'):
global engine
engine = create_engine(dbname, echo=False)
DBSession.remove()
DBSession.configure(bind=engine, autoflush=False, expire_on_commit=False)
Base.metadata.drop_all(engine)
Base.metadata.create_all(engine)
def test_sqlalchemy_orm(n=100000):
init_sqlalchemy()
t0 = time.time()
for i in range(n):
customer = Customer()
customer.name = 'NAME ' + str(i)
DBSession.add(customer)
if i % 1000 == 0:
DBSession.flush()
DBSession.commit()
print "SqlAlchemy ORM: Total time for " + str(n) + " records " + str(time.time() - t0) + " secs"
t0 = time.time()
q = DBSession.query(Customer)
dict = [{'id':r.id, 'name':r.name} for r in q]
print "SqlAlchemy ORM query: Total time for " + str(len(dict)) + " records " + str(time.time() - t0) + " secs"
def test_sqlalchemy_orm_pk_given(n=100000):
init_sqlalchemy()
t0 = time.time()
for i in range(n):
customer = Customer(id=i+1, name="NAME " + str(i))
DBSession.add(customer)
if i % 1000 == 0:
DBSession.flush()
DBSession.commit()
print "SqlAlchemy ORM pk given: Total time for " + str(n) + " records " + str(time.time() - t0) + " secs"
t0 = time.time()
q = DBSession.query(Customer)
dict = [{'id':r.id, 'name':r.name} for r in q]
print "SqlAlchemy ORM pk given query: Total time for " + str(len(dict)) + " records " + str(time.time() - t0) + " secs"
def test_sqlalchemy_core(n=100000):
init_sqlalchemy()
t0 = time.time()
engine.execute(
Customer.__table__.insert(),
[{"name":'NAME ' + str(i)} for i in range(n)]
)
print "SqlAlchemy Core: Total time for " + str(n) + " records " + str(time.time() - t0) + " secs"
conn = engine.connect()
t0 = time.time()
sql = select([Customer.__table__])
q = conn.execute(sql)
dict = [{'id':r[0], 'name':r[0]} for r in q]
print "SqlAlchemy Core query: Total time for " + str(len(dict)) + " records " + str(time.time() - t0) + " secs"
def init_sqlite3(dbname):
conn = sqlite3.connect(dbname)
c = conn.cursor()
c.execute("DROP TABLE IF EXISTS customer")
c.execute("CREATE TABLE customer (id INTEGER NOT NULL, name VARCHAR(255), PRIMARY KEY(id))")
conn.commit()
return conn
def test_sqlite3(n=100000, dbname = 'sqlite3.db'):
conn = init_sqlite3(dbname)
c = conn.cursor()
t0 = time.time()
for i in range(n):
row = ('NAME ' + str(i),)
c.execute("INSERT INTO customer (name) VALUES (?)", row)
conn.commit()
print "sqlite3: Total time for " + str(n) + " records " + str(time.time() - t0) + " sec"
t0 = time.time()
q = conn.execute("SELECT * FROM customer").fetchall()
dict = [{'id':r[0], 'name':r[0]} for r in q]
print "sqlite3 query: Total time for " + str(len(dict)) + " records " + str(time.time() - t0) + " secs"
if __name__ == '__main__':
test_sqlalchemy_orm(100000)
test_sqlalchemy_orm_pk_given(100000)
test_sqlalchemy_core(100000)
test_sqlite3(100000)
我也没有将查询结果转换为dicts进行了测试，并且统计数据相似：
SqlAlchemy ORM: Total time for 100000 records 11.9189999104 secs
SqlAlchemy ORM query: Total time for 100000 records 2.78500008583 secs
SqlAlchemy ORM pk given: Total time for 100000 records 7.67199993134 secs
SqlAlchemy ORM pk given query: Total time for 100000 records 2.94000005722 secs
SqlAlchemy Core: Total time for 100000 records 0.43700003624 secs
SqlAlchemy Core query: Total time for 100000 records 0.131000041962 secs
sqlite3: Total time for 100000 records 0.500999927521 sec
sqlite3 query: Total time for 100000 records 0.0859999656677 secs
使用 SQLAlchemy Core 进行查询比 ORM 快大约 20 倍。
需要注意的是，这些测试非常肤浅，不应过于认真。我可能遗漏了一些可以完全改变统计数据的明显技巧。
衡量性能改进的最佳方法是直接在您自己的应用程序中。不要把我的统计数据视为理所当然。