Asyncpg.pool creates more connections than its max_size

Dieses Issue hat noch niemand übernommen.

* **asyncpg version**:0.29.0
* **PostgreSQL version**: "PostgreSQL 16.0 (Debian 16.0-1.pgdg120+1) on aarch64-unknown-linux-gnu, compiled by gcc (Debian 12.2.0-14) 12.2.0, 64-bit"
* **Do you use a PostgreSQL SaaS? If so, which? Can you reproduce
the issue with a local PostgreSQL install?**: Nope, using Dockerized container
* **Python version**: 3.11.5
* **Platform**: MacBook-Air Darwin Kernel Version 21.1.0: Wed Oct 13 17:33:24 PDT 2021; root:xnu-8019.41.5~1/RELEASE_ARM64_T8101 arm64
* **Do you use pgbouncer?**: Nope
* **Did you install asyncpg with pip?**: Yes
* **If you built asyncpg locally, which version of Cython did you use?**: n/a
* **Can the issue be reproduced under both asyncio and
[uvloop](https://github.com/magicstack/uvloop)?**:Nope

I have a singleton for a Database entity, which is then used to write some primitive data. When I run the write function 1000 times concurrently using `asyncio.gather()`, the database reports that there is more connections than the `max_size` of the `asyncpg.pool`. For example, when I was testing there were 857 active db connections, but only 62 active pool connections. No other clients/operations were running during the test. When I use uvloop to do the same thing, it just crashes with `ConnectionResetError: [Errno 54] Connection reset by peer` if I try to run more tasks than the size of the pool.

Is this a normal pool behavior?

I use code below (the write function is simplified though):

The database code:
```
class Database:
_instance = None
_pool = None
db_params = {
'host': os.getenv('DATABASE_HOST'),
'port': os.getenv('DATABASE_PORT'),
'database': os.getenv('DATABASE_NAME'),
'user': os.getenv('DATABASE_USER'),
'password': os.getenv('DATABASE_PASSWORD')
}

def __new__(cls, *args, **kwargs):
if cls._instance is None:
cls._instance = super(Database, cls).__new__(cls)
#print(cls._instance)
return cls._instance

@classmethod
async def get_pool(cls):
if cls._pool is None:
cls._pool = await asyncpg.create_pool(**cls.db_params, min_size=1, max_size=150)
#print(cls._pool)
return cls._pool

@classmethod
async def write(cls, result):
pool = await cls.get_pool()
try:
async with pool.acquire() as connection:
result = await connection.execute('''
INSERT INTO tables.results(
result
) VALUES($1)
''', result)
return
except Exception as e:
raise e
```
The demo write code

```
async def fake_result(i):
print(f'generating fake result {i}')
await db.write(i)
return

async def run_functions_concurrently():
tasks = [fake_result(i) for i in range(1000)]
await asyncio.gather(*tasks)

def main():
asyncio.run(run_functions_concurrently())

if __name__ == "__main__":
main()
```

Beginne mit asyncpg.create_pool, pool.acquire und dem im Issue gezeigten Write-Pfad. Reproduziere run_functions_concurrently mit 1000 gesammelten Tasks und vergleiche die aktiven Verbindungen von PostgreSQL mit der pool-Größe max_size von 150. Als erledigt gilt, festzustellen, ob die Anzahl der Verbindungen erwartet wird, und das beobachtete Verhalten zu dokumentieren oder zu korrigieren.

Vom Indexierungsmodell aus dem Issue-Text verfasst.