ProxyPatternPool 1.1

Generic Proxy and Pool Classes for Python

Proxy Pattern Pool

Generic Proxy and Pool Classes for Python.

This module provides two classes:

• Proxy implements the proxy pattern, i.e. all calls to methods on the proxy are forwarded to an internally wrapped object. This allows to solve the classic chicken-and-egg importation and initialization possibly circular-dependency issue with Python modules:

  # File "database.py"
  db = Proxy()
  
  def init_app(config):
      db.set_obj(initialization from config)
  

  # File "app.py"
  import database
  from database import db  # db is a proxy to nothing
  …
  # delayed initialization
  database.init_app(config)
  
  # db is now a proxy to the initialized object
  

• Pool implements a thread-safe pool of things which can be used to store expensive-to-create objects such as database connections. The above proxy object creates a pool automatically depending on its parameters.

Documentation

The Proxy class manages accesses to one or more objects, possibly using a Pool, depending on the expected scope of said objects.

The Proxy constructors expects the following parameters:

• obj one single object SHARED between all threads.
• fun one function called for object creation, each time it is needed, for THREAD and VERSATILE scopes.
• scope object scope as defined by Proxy.Scope:
  • SHARED one shared object (process level)
  • THREAD one object per thread
  • VERSATILE one object per sub-thread (eg greenlets) default is SHARED or THREAD depending on whether an object of a function was passed for the object.
• set_name the name of a function to set the proxy contents, default is set. This parameter allows to avoid collisions with the proxied methods. It is used as a prefix to have set_obj and set_fun functions which allow to reset the internal obj or fun.
• max_size maximum size of pool of objects kept. None means no pooling, 0 means unlimited pool size (the default).
• max_use how many times an object should be reused. default is 0 which means unlimited.
• close name of the function to call when discarding an object, default is None means nothing is called.

When max_size is not None, a Pool is created to store the created objects so as to reuse them. It is the responsability of the user to return the object when not needed anymore by calling _ret_obj explicitely. This is useful for code which keeps creating new threads, eg werkzeug. For a database connection, a good time to do that is just after a commit.

The Pool class manage a pool of objects in a thread-safe way. Its constructor expects the following parameters:

• fun how to create a new object; the function is passed the creation number.
• max_size size of pool, 0 for unlimited.
• max_use after how many usage to discard an object.
• close method to call when discarding an object, default is None.

Objects are created on demand by calling fun when needed.

Example

Here is an example of a flask application with blueprints and a shared resource.

First, a shared module holds a proxy to a yet unknown object:

# file "Shared.py"
from ProxyPatternPool import Proxy 
stuff = Proxy()
def init_app(stuff):
    stuff.set_obj(stuff)

This shared object is used by module with a blueprint:

# file "SubStuff.py"
from Flask import Blueprint
from Shared import stuff
sub = Blueprint(…)

@sub.get("/stuff)
def get_stuff():
    return str(stuff), 200

Then the application itself can load and initialize both modules in any order without risk of having some unitialized stuff imported:

# file "App.py"
from flask import Flask
app = Flask("stuff")

from SubStuff import sub
app.register_blueprint(sub, url_prefix="/sub")

import Shared
Shared.init_app("hello world!")

License

This code is Public Domain.

Versions

1.1 on 2022-11-12

Minor fixes for mypy. Test with Python 3.12. Improved documentation.

1.0 on 2022-10-29

Add some documentation.

0.1 on 2022-10-28

Initial release with code extracted from FlaskSimpleAuth.

TODO

• __enter__ and __exit__?