PostgreSQL connection pooling for Django.
Project description
Django-PostgresPool2
This is simple PostgreSQL connection pooling for Django. You can use it as an alternative for PgBouncer. This is a fork of the original django-postgrespool.
Installation
Installing Django-PostgresPool2 is simple, with pip:
$ pip install django-postgrespool2
Usage
Using Django-PostgresPool2 is simple, just set django_postgrespool2
as your connection engine:
DATABASES = {
"default": {
"ENGINE": "django_postgrespool2",
"NAME": "yourdb",
"USER": "user",
"PASSWORD": "some_password",
"HOST": "localhost",
}
}
If you're using the environ module:
import environ
env = environ.Env()
DATABASES = {"default": env.db("DATABASE_URL", engine="django_postgrespool2")}
Everything should work as expected.
Configuration
Optionally, you can provide pool class to construct the pool (default sqlalchemy.pool.QueuePool
) or additional options to pass to SQLAlchemy's pool creation.
List of possible values DATABASE_POOL_CLASS
is here
DATABASE_POOL_CLASS = 'sqlalchemy.pool.QueuePool'
DATABASE_POOL_ARGS = {
'max_overflow': 10,
'pool_size': 5,
'recycle': 300,
}
Here's a basic explanation of two of these options:
- pool_size – The minimum number of connections to maintain in the pool.
- max_overflow – The maximum overflow size of the pool. This is not the maximum size of the pool.
- recycle - Number of seconds between connection recycling, which means upon checkout, if this timeout is surpassed the connection will be closed and replaced with a newly opened connection.
The total number of "sleeping" connections the pool will allow is pool_size
. The total simultaneous connections the pool will allow is pool_size + max_overflow
.
As an example, databases in the Heroku Postgres starter tier have a maximum connection limit of 20. In that case your pool_size
and max_overflow
, when combined, should not exceed 20.
Check out the official SQLAlchemy Connection Pooling docs to learn more about the optoins that can be defined in DATABASE_POOL_ARGS
.
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