semvec/pypi-packages huggingface dataset:
django-postgrespool-lab 0.3.0
Postgres Connection Pooling for Django.
License: MIT

Django-PostgresPool
===================

This is a simple Postgres Connection Pooling backend for Django 1.4+, powered by the lovely and beautiful SQLAlchemy.


Usage
-----

Using Django-PostgresPool is simple, just set ``django_postgrespool`` as your connection engine:

::

    DATABASES = {
        'default': {
            'ENGINE': 'django_postgrespool'


If you're using the `dj-database-url <https://crate.io/packages/dj-database-url/>`_ module:

::

    import dj_database_url

    DATABASES['default'] = dj_database_url.config()
    DATABASES['default']['ENGINE'] = 'django_postgrespool'

If you're using `south <http://south.aeracode.org>`_:

::

    SOUTH_DATABASE_ADAPTERS = {
        'default': 'south.db.postgresql_psycopg2'
    }


Everything should work as expected.


Installation
------------

Installing Django-PostgresPool is simple, with pip::

    $ pip install django-postgrespool

Configuration
-------------

Optionally, you can provide additional options to pass to SQLAlchemy's pool creation::

    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.

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 <https://postgres.heroku.com>`_ 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 <http://docs.sqlalchemy.org/en/latest/core/pooling.html#sqlalchemy.pool.QueuePool.__init__>`_ docs to learn more about the optoins that can be defined in ``DATABASE_POOL_ARGS``.

Django 1.3 Support
------------------

django-postgrespool currently supports Django 1.4 and greater. See `this ticket <https://github.com/kennethreitz/django-postgrespool/pull/9>`_ for 1.3 support.
jicgeometry 0.6.0
Basic Python geometry package with no external dependencies.
License: MIT
Keywords: geometry

JIC Geometry
============

.. image:: https://badge.fury.io/py/jicgeometry.svg
   :target: http://badge.fury.io/py/jicgeometry
   :alt: PyPi package

.. image:: https://travis-ci.org/JIC-CSB/jicgeometry.svg?branch=master
   :target: https://travis-ci.org/JIC-CSB/jicgeometry
   :alt: Travis CI build status (Linux)

.. image:: https://ci.appveyor.com/api/projects/status/skvp3sa9f5htpnkf?svg=true
   :target: https://ci.appveyor.com/project/tjelvar-olsson/jicgeometry
   :alt: AppVeyor CI build status (Windows)

.. image:: http://codecov.io/github/JIC-CSB/jicgeometry/coverage.svg?branch=master
   :target: http://codecov.io/github/JIC-CSB/jicgeometry?branch=master
   :alt: Code Coverage

.. image:: https://readthedocs.org/projects/jicgeometry/badge/?version=latest
   :target: https://readthedocs.org/projects/jicgeometry?badge=latest
   :alt: Documentation Status

Python package for basic geometry operations.

- Documentation: http://jicgeometry.readthedocs.org/en/latest/
- GitHub: https://github.com/JIC-CSB/jicgeometry
- PyPI: https://pypi.python.org/pypi/jicgeometry
- Free software: MIT License

Features
--------

- Lightweight: no dependencies outside Python's standard library
- Cross-platform: Linux, Mac and Windows are all supported
- Works with with Python 2.7, 3.2, 3.3, and 3.4


Quick Guide
-----------

To install ``jicgeometry``::

    sudo pip install jicgeometry

Create some points::

    >>> from jicgeometry import Point2D
    >>> p1 = Point2D(6, 1)
    >>> p2 = Point2D(3, 5)

Find the distances between two points::

    >>> p1.distance(p2)
    5.0

Add/subtract points from each other::

    >>> p1 + p2
    <Point2D(x=9, y=6, dtype=int)>

Scale points using multiplication/division::

    >>> p1 / 2.0
    <Point2D(x=3.00, y=0.50, dtype=float)>

Treat points as vectors::

    >>> p1.unit_vector
    <Point2D(x=0.99, y=0.16, dtype=float)>
    >>> round(p1.magnitude, 4)
    6.0828


History
-------

0.6.0
^^^^^

- Added Point3D class


0.5.0
^^^^^

- Initial upload to PyPi