sqlalchemy批量插入数据(性能问题)
sqlalchemy批量插入数据方式1:first_time = datetime.utcnow()for i in range(10000):user = User(username=username + str(i), password=password)db.session.add(user)db.session.commit()second_ti...
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sqlalchemy批量插入数据
方式1:
first_time = datetime.utcnow() for i in range(10000): user = User(username=username + str(i), password=password) db.session.add(user) db.session.commit() second_time = datetime.utcnow() print((second_time - first_time).total_seconds()) # 38.14347s
方式2:
second_time = datetime.utcnow() db.session.bulk_save_objects( [ User(username=username + str(i), password=password) for i in range(10000) ] ) db.session.commit() third_time = datetime.utcnow() print((third_time - second_time).total_seconds()) # 2.121589s
方式3:
third_time = datetime.utcnow() db.session.bulk_insert_mappings( User, [ dict(username="NAME INSERT " + str(i), password=password) for i in range(10000) ] ) db.session.commit() fourth_time = datetime.utcnow() print((fourth_time - third_time).total_seconds()) # 1.13548s
方式4:
fourth_time = datetime.utcnow() db.session.execute( User.__table__.insert(), [{"username": 'Execute NAME ' + str(i), "password": password} for i in range(10000)] ) db.session.commit() five_time = datetime.utcnow() print((five_time - fourth_time).total_seconds()) # 0.888822s

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