So, I've tried with psycpog2 and I have no issue in docker:
def main(db_url):
engine = create_engine(db_url, echo="debug")
Session = sessionmaker(engine, expire_on_commit=False)
with engine.begin() as conn:
Base.metadata.drop_all(conn)
Base.metadata.create_all(conn)
for i in range(100):
with Session() as session:
with session.begin():
session.add(RecordA(a=A.ONE))
with session.begin():
session.add(RecordB(b=B.THREE, c=C.FIVE))
with session.begin():
session.add(RecordB(b=B.FOUR, c=C.SIX))
main("postgresql://scott:tiger@localhost/test")
Also using asyncpg directly does not have any issue (also with docker)
async def main(db_url):
engine = create_async_engine(db_url, echo="debug")
async with engine.begin() as conn:
await conn.run_sync(Base.metadata.drop_all)
await conn.run_sync(Base.metadata.create_all)
conn = await
asyncpg.connect(db_url.replace('postgresql+asyncpg','postgresql'))
async with conn.transaction():
await conn.execute('INSERT INTO "TableA" (a) VALUES ($1) RETURNING
"TableA".id', A.ONE.name)
async with conn.transaction():
await conn.execute('INSERT INTO "TableB" (b, c) VALUES ($1, $2)
RETURNING "TableB".id', B.THREE.name, C.FIVE.name)
async with conn.transaction():
await conn.execute('INSERT INTO "TableB" (b, c) VALUES ($1, $2)
RETURNING "TableB".id', B.FOUR.name, C.SIX.name)
await conn.close()
asyncio.run(main("postgresql+asyncpg://scott:tiger@localhost/test"))
It seems to be somehow connected to sqlalchemy, but I'm not really sure
how. Ideas Mike?
On Thursday, 25 March 2021 at 20:28:25 UTC+1 Michaël Van de Steene wrote:
> Thanks for the feedback! So that would imply the issue is in running
> postgres in docker, I guess?
>
> I'm still somewhat confused by my tests earlier where I also had the
> problem when running against a postgres instance without docker in a Ubuntu
> VM.
> Then again, that does also use a virtualised network adapter. Perhaps the
> issue is in that direction...
>
> I'll redo my tests with postgres outside of docker to confirm that aspect.
> Any other thoughts of things to check?
> On Thursday, 25 March 2021 at 20:23:01 UTC+1 [email protected] wrote:
>
>> I can reproduce using postgres in docker. About 1s of delay
>>
>> 2021-03-25 20:22:12,488 INFO sqlalchemy.engine.Engine INSERT INTO
>> "TableA" (a) VALUES (?) RETURNING "TableA".id
>> 2021-03-25 20:22:12,488 INFO sqlalchemy.engine.Engine [generated in
>> 0.00091s] ('ONE',)
>> 2021-03-25 20:22:12,631 DEBUG sqlalchemy.engine.Engine Col ('id',)
>> 2021-03-25 20:22:12,632 DEBUG sqlalchemy.engine.Engine Row (1,)
>> 2021-03-25 20:22:12,632 INFO sqlalchemy.engine.Engine COMMIT
>> 2021-03-25 20:22:12,637 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>> 2021-03-25 20:22:12,639 INFO sqlalchemy.engine.Engine INSERT INTO
>> "TableB" (b, c) VALUES (?, ?) RETURNING "TableB".id
>> 2021-03-25 20:22:12,639 INFO sqlalchemy.engine.Engine [generated in
>> 0.00055s] ('THREE', 'FIVE')
>> 2021-03-25 20:22:13,692 DEBUG sqlalchemy.engine.Engine Col ('id',)
>> 2021-03-25 20:22:13,693 DEBUG sqlalchemy.engine.Engine Row (1,)
>> 2021-03-25 20:22:13,694 INFO sqlalchemy.engine.Engine COMMIT
>> 2021-03-25 20:22:13,700 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>> 2021-03-25 20:22:13,701 INFO sqlalchemy.engine.Engine INSERT INTO
>> "TableB" (b, c) VALUES (?, ?) RETURNING "TableB".id
>> 2021-03-25 20:22:13,701 INFO sqlalchemy.engine.Engine [cached since
>> 1.063s ago] ('FOUR', 'SIX')
>> 2021-03-25 20:22:13,705 DEBUG sqlalchemy.engine.Engine Col ('id',)
>> 2021-03-25 20:22:13,706 DEBUG sqlalchemy.engine.Engine Row (2,)
>> 2021-03-25 20:22:13,706 INFO sqlalchemy.engine.Engine COMMIT
>>
>> On Thursday, 25 March 2021 at 20:18:59 UTC+1 Federico Caselli wrote:
>>
>>> Hi,
>>>
>>> I've tried the script and I also cannot reproduce it:
>>>
>>> py3.7 + pg 13.1 (non-docker) on windows
>>>
>>> 2021-03-25 19:35:15,977 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>> 2021-03-25 19:35:15,979 INFO sqlalchemy.engine.Engine INSERT INTO
>>> "TableA" (a) VALUES (?) RETURNING "TableA".id
>>> 2021-03-25 19:35:15,980 INFO sqlalchemy.engine.Engine [generated in
>>> 0.00080s] ('ONE',)
>>> 2021-03-25 19:35:15,999 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>> 2021-03-25 19:35:16,000 DEBUG sqlalchemy.engine.Engine Row (1,)
>>> 2021-03-25 19:35:16,001 INFO sqlalchemy.engine.Engine COMMIT
>>> 2021-03-25 19:35:16,004 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>> 2021-03-25 19:35:16,006 INFO sqlalchemy.engine.Engine INSERT INTO
>>> "TableB" (b, c) VALUES (?, ?) RETURNING "TableB".id
>>> 2021-03-25 19:35:16,006 INFO sqlalchemy.engine.Engine [generated in
>>> 0.00070s] ('THREE', 'FIVE')
>>> 2021-03-25 19:35:16,014 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>> 2021-03-25 19:35:16,014 DEBUG sqlalchemy.engine.Engine Row (1,)
>>> 2021-03-25 19:35:16,015 INFO sqlalchemy.engine.Engine COMMIT
>>> 2021-03-25 19:35:16,016 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>> 2021-03-25 19:35:16,017 INFO sqlalchemy.engine.Engine INSERT INTO
>>> "TableB" (b, c) VALUES (?, ?) RETURNING "TableB".id
>>> 2021-03-25 19:35:16,017 INFO sqlalchemy.engine.Engine [cached since
>>> 0.0114s ago] ('FOUR', 'SIX')
>>> 2021-03-25 19:35:16,018 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>> 2021-03-25 19:35:16,019 DEBUG sqlalchemy.engine.Engine Row (2,)
>>> 2021-03-25 19:35:16,020 INFO sqlalchemy.engine.Engine COMMIT
>>>
>>> On Thursday, 25 March 2021 at 19:33:57 UTC+1 Michaël Van de Steene wrote:
>>>
>>>> *what happens if you run the asyncio.run() part in a loop? is the 700
>>>> ms every time ? *
>>>> Yes, it happens each time.
>>>>
>>>> I also just ran the same test on a different device, a raspberry pi as
>>>> that's what I had quickly available. Logging from that run is attached
>>>> below.
>>>> There's a slowdown at two points, and it's substantially larger. This
>>>> slowdown in the first query is also present in the original log, it's just
>>>> less noticeable (70 ms).
>>>>
>>>> Gives me the impression the slowdown is caused by some CPU bound
>>>> process, as the raspberry pi's performance is a lot worse than my
>>>> workstation.
>>>>
>>>> 2021-03-25 18:26:23,807 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>> 2021-03-25 18:26:23,810 INFO sqlalchemy.engine.Engine INSERT INTO
>>>> "TableA" (a) VALUES (%s) RETURNING "TableA".id
>>>> 2021-03-25 18:26:23,811 INFO sqlalchemy.engine.Engine [generated in
>>>> 0.00055s] ('ONE',)
>>>> 2021-03-25 18:26:24,274 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>> 2021-03-25 18:26:24,275 DEBUG sqlalchemy.engine.Engine Row (1,)
>>>> 2021-03-25 18:26:24,276 INFO sqlalchemy.engine.Engine COMMIT
>>>> 2021-03-25 18:26:24,289 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>> 2021-03-25 18:26:24,291 INFO sqlalchemy.engine.Engine INSERT INTO
>>>> "TableB" (b, c) VALUES (%s, %s) RETURNING "TableB".id
>>>> 2021-03-25 18:26:24,291 INFO sqlalchemy.engine.Engine [generated in
>>>> 0.00056s] ('THREE', 'FIVE')
>>>> 2021-03-25 18:26:28,102 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>> 2021-03-25 18:26:28,102 DEBUG sqlalchemy.engine.Engine Row (1,)
>>>> 2021-03-25 18:26:28,103 INFO sqlalchemy.engine.Engine COMMIT
>>>> 2021-03-25 18:26:28,115 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>> 2021-03-25 18:26:28,116 INFO sqlalchemy.engine.Engine INSERT INTO
>>>> "TableB" (b, c) VALUES (%s, %s) RETURNING "TableB".id
>>>> 2021-03-25 18:26:28,116 INFO sqlalchemy.engine.Engine [cached since
>>>> 3.825s ago] ('FOUR', 'SIX')
>>>> 2021-03-25 18:26:28,119 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>> 2021-03-25 18:26:28,119 DEBUG sqlalchemy.engine.Engine Row (2,)
>>>> 2021-03-25 18:26:28,120 INFO sqlalchemy.engine.Engine COMMIT
>>>> On Thursday, 25 March 2021 at 19:25:11 UTC+1 Mike Bayer wrote:
>>>>
>>>>> what happens if you run the asyncio.run() part in a loop? is the 700
>>>>> ms every time ?
>>>>>
>>>>> On Thu, Mar 25, 2021, at 1:54 PM, Michaël Van de Steene wrote:
>>>>>
>>>>> Sorry for the slow reply, been dealing with a few other issues while
>>>>> also working on this.
>>>>> To confirm your question: using PG12 and Python 3.7 I do see the
>>>>> slowdown.
>>>>>
>>>>> Since then I've taken to some extra tests (all using SQLAlchemy 1.4.2
>>>>> and asyncpg 0.2.2.0)
>>>>>
>>>>> 1. PG12.6 (no docker) with Python 3.8 (in docker): 700 ms slowdown
>>>>> 2. PG12.6 (no docker) with Python 3.9 (in docker): 700 ms slowdown
>>>>> 3. PG12.6 (no docker) with Python 3.8.8 (no docker): 700 ms
>>>>> slowdown
>>>>> - I am also getting a 'OSError: [Errno 9] Bad file descriptor'
>>>>> error in this configuration. Seems as if there is still
>>>>> communication with
>>>>> the database when the asyncio loop is torn down.
>>>>> Figure this may be related to the compile process. I've
>>>>> installed it from source using ./configure --enable-optimizations
>>>>> 4. PG12.6 (no docker) with Python 3.7.10 (no docker): 700 ms
>>>>> slowdown
>>>>>
>>>>> In short, I am always seeing this delay on the second insert in the
>>>>> example script regardless of python version and use of docker.
>>>>>
>>>>> In all these tests the PG instance was running on a Ubuntu 20.04.2
>>>>> virtual machine.
>>>>> The python (and docker) side of things was running in Debian 10 (in
>>>>> WSL2 on a windows machine, if that matters).
>>>>>
>>>>> In an attempt to exclude the WSL2 environment, I also attempted to run
>>>>> (dockerised) python in the same Ubuntu 20.04.2 virtual machine but that
>>>>> too
>>>>> is showing the delay.
>>>>> On Thursday, 25 March 2021 at 15:57:17 UTC+1 Mike Bayer wrote:
>>>>>
>>>>>
>>>>> so with PG12 and python 3.7 you *do* or *do not* see the slowdown?
>>>>>
>>>>>
>>>>>
>>>>> On Thu, Mar 25, 2021, at 10:45 AM, Michaël Van de Steene wrote:
>>>>>
>>>>> Thanks for the quick reply! It does appear to be an environment issue
>>>>> on my end then.
>>>>>
>>>>> I've already tried a few things:
>>>>>
>>>>> - Postgres 12
>>>>> - Python 3.7
>>>>>
>>>>> So far no dice. This was all within docker though, I'll try a few more
>>>>> things outside of the docker environment and report back.
>>>>>
>>>>> On Thursday, 25 March 2021 at 14:02:29 UTC+1 Mike Bayer wrote:
>>>>>
>>>>>
>>>>> Hi there -
>>>>>
>>>>> thanks for the clear example. I just ran it against a several PG
>>>>> databases, including a PG 13 and PG 12 on the local network, and I am not
>>>>> observing any delay of that magnitude, SQL output with timestamps
>>>>> follow.
>>>>>
>>>>> what OS are you running on ? I would say you might want to try
>>>>> replicating these commands to plain asyncpg, but that will not
>>>>> necessarily
>>>>> produce the same sequence as we use prepared statements explicitly in all
>>>>> cases, or try running the equivalent commands with psycopg2 to see if
>>>>> there's some database-specific issue going on. but you're running
>>>>> against
>>>>> a vanilla docker container so that's a little strange, try running the
>>>>> script from your workstation instead perhaps.
>>>>>
>>>>> 2021-03-25 08:56:24,722 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>>> 2021-03-25 08:56:24,723 INFO sqlalchemy.engine.Engine INSERT INTO
>>>>> "TableA" (a) VALUES (%s) RETURNING "TableA".id
>>>>> 2021-03-25 08:56:24,723 INFO sqlalchemy.engine.Engine [generated in
>>>>> 0.00023s] ('ONE',)
>>>>> 2021-03-25 08:56:24,754 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>>> 2021-03-25 08:56:24,754 DEBUG sqlalchemy.engine.Engine Row (1,)
>>>>> 2021-03-25 08:56:24,754 INFO sqlalchemy.engine.Engine COMMIT
>>>>> 2021-03-25 08:56:24,758 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>>> 2021-03-25 08:56:24,759 INFO sqlalchemy.engine.Engine INSERT INTO
>>>>> "TableB" (b, c) VALUES (%s, %s) RETURNING "TableB".id
>>>>> 2021-03-25 08:56:24,759 INFO sqlalchemy.engine.Engine [generated in
>>>>> 0.00019s] ('THREE', 'FIVE')
>>>>> 2021-03-25 08:56:24,767 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>>> 2021-03-25 08:56:24,767 DEBUG sqlalchemy.engine.Engine Row (1,)
>>>>> 2021-03-25 08:56:24,768 INFO sqlalchemy.engine.Engine COMMIT
>>>>> 2021-03-25 08:56:24,770 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>>> 2021-03-25 08:56:24,771 INFO sqlalchemy.engine.Engine INSERT INTO
>>>>> "TableB" (b, c) VALUES (%s, %s) RETURNING "TableB".id
>>>>> 2021-03-25 08:56:24,771 INFO sqlalchemy.engine.Engine [cached since
>>>>> 0.01149s ago] ('FOUR', 'SIX')
>>>>> 2021-03-25 08:56:24,772 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>>> 2021-03-25 08:56:24,772 DEBUG sqlalchemy.engine.Engine Row (2,)
>>>>> 2021-03-25 08:56:24,772 INFO sqlalchemy.engine.Engine COMMIT
>>>>>
>>>>>
>>>>>
>>>>> On Thu, Mar 25, 2021, at 8:31 AM, Michaël Van de Steene wrote:
>>>>>
>>>>> Hi everyone,
>>>>>
>>>>> We recently started using sqlalchemy in combination with asyncpg and
>>>>> are observing some behaviour we can't quite figure out. I hope this is
>>>>> the
>>>>> right place to get help, if it would be better addressed elsewhere please
>>>>> let me know.
>>>>>
>>>>> To frame the issue, we have a table with several enum columns. The
>>>>> first time we access this table, there is a roughly 600 ms delay before
>>>>> any
>>>>> results are returned. This seems to apply both for insert and select
>>>>> operations. After that first access, everything seems speedy returning in
>>>>> just a few milliseconds.
>>>>>
>>>>> I've created a short example application to show this problem:
>>>>> import asyncio
>>>>> import enum
>>>>> from sqlalchemy import Enum, Column, Integer
>>>>> from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
>>>>> from sqlalchemy.ext.declarative import declarative_base
>>>>> from sqlalchemy.orm import sessionmaker
>>>>>
>>>>> Base = declarative_base()
>>>>>
>>>>>
>>>>> class A(enum.Enum):
>>>>> ONE = 1
>>>>> TWO = 2
>>>>>
>>>>>
>>>>> class B(enum.Enum):
>>>>> THREE = 3
>>>>> FOUR = 4
>>>>>
>>>>>
>>>>> class C(enum.Enum):
>>>>> FIVE = 5
>>>>> SIX = 6
>>>>>
>>>>>
>>>>> class RecordA(Base):
>>>>> __tablename__ = "TableA"
>>>>>
>>>>> id = Column(Integer, primary_key=True, autoincrement=True)
>>>>> a = Column(Enum(A))
>>>>>
>>>>>
>>>>> class RecordB(Base):
>>>>> __tablename__ = "TableB"
>>>>>
>>>>> id = Column(Integer, primary_key=True, autoincrement=True)
>>>>> b = Column(Enum(B))
>>>>> c = Column(Enum(C))
>>>>>
>>>>>
>>>>> async def main(db_url):
>>>>> engine = create_async_engine(db_url, echo="debug")
>>>>> Session = sessionmaker(engine, expire_on_commit=False,
>>>>> class_=AsyncSession)
>>>>>
>>>>> async with engine.begin() as conn:
>>>>> await conn.run_sync(Base.metadata.drop_all)
>>>>> await conn.run_sync(Base.metadata.create_all)
>>>>>
>>>>> async with Session() as session:
>>>>> async with session.begin():
>>>>> session.add(RecordA(a=A.ONE))
>>>>> async with session.begin():
>>>>> session.add(RecordB(b=B.THREE, c=C.FIVE))
>>>>> async with session.begin():
>>>>> session.add(RecordB(b=B.FOUR, c=C.SIX))
>>>>>
>>>>>
>>>>> asyncio.run(main(
>>>>>
>>>>> "postgresql+asyncpg://postgres:[email protected]/postgres"))
>>>>>
>>>>> The logging of the three insert operations shows:
>>>>> 2021-03-25 12:14:10,224 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>>> 2021-03-25 12:14:10,225 INFO sqlalchemy.engine.Engine INSERT INTO
>>>>> "TableA" (a) VALUES (%s) RETURNING "TableA".id
>>>>> 2021-03-25 12:14:10,225 INFO sqlalchemy.engine.Engine [generated in
>>>>> 0.00011s] ('ONE',)
>>>>> 2021-03-25 12:14:10,296 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>>> 2021-03-25 12:14:10,296 DEBUG sqlalchemy.engine.Engine Row (1,)
>>>>> 2021-03-25 12:14:10,296 INFO sqlalchemy.engine.Engine COMMIT
>>>>> 2021-03-25 12:14:10,299 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>>> 2021-03-25 12:14:10,299 INFO sqlalchemy.engine.Engine INSERT INTO
>>>>> "TableB" (b, c) VALUES (%s, %s) RETURNING "TableB".id
>>>>> 2021-03-25 12:14:10,299 INFO sqlalchemy.engine.Engine [generated in
>>>>> 0.00012s] ('THREE', 'FIVE')
>>>>> 2021-03-25 12:14:10,906 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>>> 2021-03-25 12:14:10,906 DEBUG sqlalchemy.engine.Engine Row (1,)
>>>>> 2021-03-25 12:14:10,906 INFO sqlalchemy.engine.Engine COMMIT
>>>>> 2021-03-25 12:14:10,924 INFO sqlalchemy.engine.Engine BEGIN (implicit)
>>>>> 2021-03-25 12:14:10,924 INFO sqlalchemy.engine.Engine INSERT INTO
>>>>> "TableB" (b, c) VALUES (%s, %s) RETURNING "TableB".id
>>>>> 2021-03-25 12:14:10,924 INFO sqlalchemy.engine.Engine [cached since
>>>>> 0.625s ago] ('FOUR', 'SIX')
>>>>> 2021-03-25 12:14:10,926 DEBUG sqlalchemy.engine.Engine Col ('id',)
>>>>> 2021-03-25 12:14:10,926 DEBUG sqlalchemy.engine.Engine Row (2,)
>>>>> 2021-03-25 12:14:10,926 INFO sqlalchemy.engine.Engine COMMIT
>>>>>
>>>>> I've highlighted the timestamps showing the 600 ms delay in red.
>>>>> It seems as if:
>>>>>
>>>>> - An insert with just 1 enum does not incur delay
>>>>> - An insert with 2 enums incurs delays
>>>>> - A subsequent insert using those same enums doesn't incur delay
>>>>>
>>>>> I'm at a loss to explain this behaviour. As I mentioned we're quite
>>>>> new to SQLAlchemy. Is there anything we're doing wrong?
>>>>>
>>>>> The output is generated using:
>>>>>
>>>>> - PostgreSQL 13.2
>>>>> - Python 3.9.2
>>>>> - SQLAlchemy 1.4.2
>>>>> - Asyncpg 0.22.0
>>>>>
>>>>>
>>>>> Finally, run instructions using docker just in case it can help to
>>>>> quickly reproduce:
>>>>>
>>>>> 1. Save the example as `asyncpg_enum.py` in the current directory
>>>>> 2. Run docker run -d --name=postgres -e
>>>>> POSTGRES_PASSWORD="example" -p 5432:5432 postgres
>>>>> 3. Run docker run -it -v ${PWD}/asyncpg_enum.py:/asyncpg_enum.py
>>>>> python bash -c 'pip install sqlalchemy asyncpg && python
>>>>> /asyncpg_enum.py'
>>>>>
>>>>> Any insight or things to check would be appreciated.
>>>>>
>>>>> Thanks,
>>>>> Michael
>>>>>
>>>>>
>>>>> --
>>>>> SQLAlchemy -
>>>>> The Python SQL Toolkit and Object Relational Mapper
>>>>>
>>>>> http://www.sqlalchemy.org/
>>>>>
>>>>> To post example code, please provide an MCVE: Minimal, Complete, and
>>>>> Verifiable Example. See http://stackoverflow.com/help/mcve for a full
>>>>> description.
>>>>> ---
>>>>> You received this message because you are subscribed to the Google
>>>>> Groups "sqlalchemy" group.
>>>>> To unsubscribe from this group and stop receiving emails from it, send
>>>>> an email to [email protected].
>>>>> To view this discussion on the web visit
>>>>> https://groups.google.com/d/msgid/sqlalchemy/65748bd4-bea6-4e07-b7ce-c1a8c5a91c98n%40googlegroups.com
>>>>>
>>>>> <https://groups.google.com/d/msgid/sqlalchemy/65748bd4-bea6-4e07-b7ce-c1a8c5a91c98n%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>> .
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> SQLAlchemy -
>>>>> The Python SQL Toolkit and Object Relational Mapper
>>>>>
>>>>> http://www.sqlalchemy.org/
>>>>>
>>>>> To post example code, please provide an MCVE: Minimal, Complete, and
>>>>> Verifiable Example. See http://stackoverflow.com/help/mcve for a full
>>>>> description.
>>>>> ---
>>>>> You received this message because you are subscribed to the Google
>>>>> Groups "sqlalchemy" group.
>>>>> To unsubscribe from this group and stop receiving emails from it, send
>>>>> an email to [email protected].
>>>>>
>>>>> To view this discussion on the web visit
>>>>> https://groups.google.com/d/msgid/sqlalchemy/8c817a6b-8e9b-41bd-940b-c91ceb6081a3n%40googlegroups.com
>>>>>
>>>>> <https://groups.google.com/d/msgid/sqlalchemy/8c817a6b-8e9b-41bd-940b-c91ceb6081a3n%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>> .
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> SQLAlchemy -
>>>>> The Python SQL Toolkit and Object Relational Mapper
>>>>>
>>>>> http://www.sqlalchemy.org/
>>>>>
>>>>> To post example code, please provide an MCVE: Minimal, Complete, and
>>>>> Verifiable Example. See http://stackoverflow.com/help/mcve for a full
>>>>> description.
>>>>> ---
>>>>> You received this message because you are subscribed to the Google
>>>>> Groups "sqlalchemy" group.
>>>>> To unsubscribe from this group and stop receiving emails from it, send
>>>>> an email to [email protected].
>>>>>
>>>>> To view this discussion on the web visit
>>>>> https://groups.google.com/d/msgid/sqlalchemy/b407388e-fc54-4b3f-8376-f86f6de5c530n%40googlegroups.com
>>>>>
>>>>> <https://groups.google.com/d/msgid/sqlalchemy/b407388e-fc54-4b3f-8376-f86f6de5c530n%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>> .
>>>>>
>>>>>
>>>>>
--
SQLAlchemy -
The Python SQL Toolkit and Object Relational Mapper
http://www.sqlalchemy.org/
To post example code, please provide an MCVE: Minimal, Complete, and Verifiable
Example. See http://stackoverflow.com/help/mcve for a full description.
---
You received this message because you are subscribed to the Google Groups
"sqlalchemy" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to [email protected].
To view this discussion on the web visit
https://groups.google.com/d/msgid/sqlalchemy/ba09c7c2-567b-4999-9e96-bf4b6caeb165n%40googlegroups.com.
