Odtnhj

I am saving a user's database connection. On the first time they enter in their credentials, I do something like the following:

self.conn = MySQLdb.connect (
 host = 'aaa',
 user = 'bbb',
 passwd = 'ccc',
 db = 'ddd',
 charset='utf8'
)
cursor = self.conn.cursor()
cursor.execute("SET NAMES utf8")
cursor.execute('SET CHARACTER SET utf8;')
cursor.execute('SET character_set_connection=utf8;')

I then have the conn ready to go for all the user's queries. However, I don't want to re-connect every time the view is loaded. How would I store this "open connection" so I can just do something like the following in the view:

def do_queries(request, sql):
 user = request.user
 conn = request.session['conn']
 cursor = request.session['cursor']
 cursor.execute(sql)

Update: it seems like the above is not possible and not good practice, so let me re-phrase what I'm trying to do:

I have a sql editor that a user can use after they enter in their credentials (think of something like Navicat or SequelPro). Note this is NOT the default django db connection -- I do not know the credentials beforehand. Now, once the user has 'connected', I would like them to be able to do as many queries as they like without me having to reconnect every time they do this. For example -- to re-iterate again -- something like Navicat or SequelPro. How would this be done using python, django, or mysql? Perhaps I don't really understand what is necessary here (caching the connection? connection pooling? etc.), so any suggestions or help would be greatly appreciated.

You could use an IoC container to store a singleton provider for you. Essentially, instead of constructing a new connection every time, it will only construct it once (the first time ConnectionContainer.connection_provider() is called) and thereafter it will always return the previously constructed connection.

You'll need the dependency-injector package for my example to work:

import dependency_injector.containers as containers
import dependency_injector.providers as providers


class ConnectionProvider():
 def __init__(self, host, user, passwd, db, charset):
 self.conn = MySQLdb.connect(
 host=host,
 user=user,
 passwd=passwd,
 db=db,
 charset=charset
 )


class ConnectionContainer(containers.DeclarativeContainer):
 connection_provider = providers.Singleton(ConnectionProvider,
 host='aaa',
 user='bbb',
 passwd='ccc',
 db='ddd',
 charset='utf8')


def do_queries(request, sql):
 user = request.user
 conn = ConnectionContainer.connection_provider().conn
 cursor = conn.cursor()
 cursor.execute(sql)

I've hardcoded the connection string here, but it is also possible to make it variable depending on a changeable configuration. In that case you could also create a container for the configuration file and have the connection container read its config from there. You then set the config at runtime. As follows:

import dependency_injector.containers as containers
import dependency_injector.providers as providers

class ConnectionProvider():
 def __init__(self, connection_config):
 self.conn = MySQLdb.connect(**connection_config)

class ConfigContainer(containers.DeclarativeContainer):
 connection_config = providers.Configuration("connection_config")

class ConnectionContainer(containers.DeclarativeContainer):
 connection_provider = providers.Singleton(ConnectionProvider, ConfigContainer.connection_config)

def do_queries(request, sql):
 user = request.user
 conn = ConnectionContainer.connection_provider().conn
 cursor = conn.cursor()
 cursor.execute(sql)


# run code
my_config = 
 'host':'aaa',
 'user':'bbb',
 'passwd':'ccc',
 'db':'ddd',
 'charset':'utf8'


ConfigContainer.connection_config.override(my_config)
request = ...
sql = ...

do_queries(request, sql)

I don't see why do you need a cached connection here and why not just reconnect on every request caching user's credentials somewhere, but anyway I'll try to outline a solution that might fit your requirements.

I'd suggest to look into a more generic task first - cache something between subsequent requests your app needs to handle and can't serialize into django's sessions.
In your particular case this shared value would be a database connection (or multiple connections).
Lets start with a simple task of sharing a simple counter variable between requests, just to understand what's actually happening under the hood.

Amaizingly but neither answer has mentioned anything regarding a web server you might use!
Actually there are multiple ways to handle concurrent connections in web apps:

1. Having multiple processes, every request comes into one of them at random


2. Having multiple threads, every request is handled by a random thread
   


3. p.1 and p.2 combined


4. Various async techniques, when there's a single process + event loop handling requests with a caveat that request handlers shouldn't block for a long time

From my own experience p.1-2 are fine for majority of typical webapps.
Apache1.x could only work with p.1, Apache2.x can handle all of 1-3.

Lets start with the following django app and run a single-process gunicorn webserver.
I'm going to use gunicorn because it's fairly easy to configure it unlike apache (personal opinion :-)

views.py

import time

from django.http import HttpResponse

c = 0

def main(self):
 global c
 c += 1
 return HttpResponse('val: n'.format(c))


def heavy(self):
 time.sleep(10)
 return HttpResponse('heavy done')

urls.py

from django.contrib import admin
from django.urls import path

from . import views

urlpatterns = [
 path('admin/', admin.site.urls),
 path('', views.main, name='main'),
 path('heavy/', views.heavy, name='heavy')
]

Running it in a single process mode:

gunicorn testpool.wsgi -w 1

Here's our process tree - there's only 1 worker that would handle ALL requests

pstree 77292
-+= 77292 oleg /Users/oleg/.virtualenvs/test3.4/bin/python /Users/oleg/.virtualenvs/test3.4/bin/gunicorn testpool.wsgi -w 1
 --- 77295 oleg /Users/oleg/.virtualenvs/test3.4/bin/python /Users/oleg/.virtualenvs/test3.4/bin/gunicorn testpool.wsgi -w 1

Trying to use our app:

curl 'http://127.0.0.1:8000'
val: 1

curl 'http://127.0.0.1:8000'
val: 2

curl 'http://127.0.0.1:8000'
val: 3

As you can see you can easily share the counter between subsequent requests.
The problem here is that you can only serve a single request in parallel. If you request for /heavy/ in one tab, / won't work until /heavy is done

Lets now use 2 worker processes:

gunicorn testpool.wsgi -w 2

This is how the process tree would look like:

 pstree 77285
-+= 77285 oleg /Users/oleg/.virtualenvs/test3.4/bin/python /Users/oleg/.virtualenvs/test3.4/bin/gunicorn testpool.wsgi -w 2
 |--- 77288 oleg /Users/oleg/.virtualenvs/test3.4/bin/python /Users/oleg/.virtualenvs/test3.4/bin/gunicorn testpool.wsgi -w 2
 --- 77289 oleg /Users/oleg/.virtualenvs/test3.4/bin/python /Users/oleg/.virtualenvs/test3.4/bin/gunicorn testpool.wsgi -w 2

Testing our app:

curl 'http://127.0.0.1:8000'
val: 1

curl 'http://127.0.0.1:8000'
val: 2

curl 'http://127.0.0.1:8000'
val: 1

The first two requests has been handled by the first worker process, and the 3rd one - by the second worker process that has its own memory space so you see 1 instead of 3.
Notice your output may differ because process 1 and 2 are selected at random. But sooner or later you'll hit a different process.

That's not very helpful for us because we need to handle multiple concurrent requests and we need to somehow get our request handled by a specific process that can't be done in general case.

Most pooling technics coming out of the box would only cache connections in the scope of a single process, if your request gets served by a different process - a NEW connection would need to be made.

Lets move to threads

gunicorn testpool.wsgi -w 1 --threads 2

Again - only 1 process

pstree 77310
-+= 77310 oleg /Users/oleg/.virtualenvs/test3.4/bin/python /Users/oleg/.virtualenvs/test3.4/bin/gunicorn testpool.wsgi -w 1 --threads 2
 --- 77313 oleg /Users/oleg/.virtualenvs/test3.4/bin/python /Users/oleg/.virtualenvs/test3.4/bin/gunicorn testpool.wsgi -w 1 --threads 2

Now if you run /heavy in one tab you'll still be able to query / and your counter will be preserved between requests!
Even if the number of threads is growing or shrinking depending on your workload it should still work fine.

Problems: you'll need to synchronize access to the shared variable like this using python threads synchronization technics (read more).
Another problem is that the same user may need to to issue multiple queries in parallel - i.e. open multiple tabs.

To handle it you can open multiple connections on the first request when you have db credentials available.

If a user needs more connections than your app might wait on lock until a connection becomes available.

Back to your question

You can create a class that would have the following methods:

from contextlib import contextmanager

class ConnectionPool(object):

 def __init__(self, max_connections=4):
 self._pool = dict()
 self._max_connections = max_connections

 def preconnect(self, session_id, user, password):
 # create multiple connections and put them into self._pool
 # ...

 @contextmanager
 def get_connection(sef, session_id):
 # if have an available connection:
 # mark it as allocated
 # and return it
 try:
 yield connection
 finally:
 # put it back to the pool
 # ....
 # else
 # wait until there's a connection returned to the pool by another thread

pool = ConnectionPool(4)

def some_view(self):
 session_id = ...
 with pool.get_connection(session_id) as conn:
 conn.query(...)

This is not a complete solution - you'll need to somehow delete outdated connections not used for a long time.

If a user comes back after a long time and his connection have been closed, he'll need to provide his credentials again - hopefully it's ok from your app's perspective.

Also keep in mind python threads have its performance penalties, not sure if this is an issue for you.

I haven't checked it for apache2 (too much configuration burden, I haven't used it for ages and generally use uwsgi), but it should work there too - would be happy to hear back from you
if you manage to run it )

And also don't forget about p.4 (async approach) - unlikely will you be able to use it on apache, but it's worth investigation - keywords: django + gevent, django + asyncio. It has its pros/cons and may greatly affect your app implementation so it's hard to suggest any solution without knowing your app requirements in detail

This is not a good idea to do such a thing synchronously in web app context. Remember that your application may needs to work in multi process/thread fashion, and you could not share connection between processes normally. So if you create a connection for your user on a process, there is no guaranty to receive query request on the same one. May be a better idea is to have a single process background worker which handles connections in multiple threads (a thread per session) to make queries on database and retrieve result on web app. Your application should assign a unique ID to each session and the background worker track each thread using session ID. You may use celery or any other task queues supporting async result. So the design would be something like below:

 |<--| |<--------------| |<--|
user (id: x) | | webapp | | queue | | worker (thread x) | | DB
 |-->| |-->| |-->| |-->|

Also you could create a queue for each user until they have an active session, as a result you could run a separate background process for each session.

I actually shared my solution to this exact issue. What I did here was create a pool of connections that you can specify the max with, and then queued query requests async through this channel. This way you can leave a certain amount of connections open, but it will queue and pool async and keep the speed you are used to.

This requires gevent and postgres.

Python Postgres psycopg2 ThreadedConnectionPool exhausted