MyNQL 0.2

My Network Query Language

Concept

A good foundation is a simple concept:

• Nodes have the format table.id

• Connections have a distance

You may already have tables like: customers, merchants, products, places, areas, promotions, interests. Most of the times in a relational database there is an id/key, so with table.id all entries can be addressed.

Teach the MyNQL network relations between two table1.id1 <-> table2.id2 you know, and then ask the network about all the (indirect) relations you like to know.

This is very simple, but also very powerful! You define a starting point, and search for the closest matches of a desired table. When you add more connections your questions will stay the same, only the results will improve. If you like to see a real live example look this example, here is an example with a Computer Store.

Install

git clone https://github.com/livinter/MyNQL.git
python setup.py install

Teach the Network

You can do relations between those nodes using:

• connect - connect two nodes

• delete - delete a connection

The nodes will be created when they have connections, and remove if they have no more connections.

Optional you can specify a distance between nodes.

Ask the network

• select - gives you the best related nodes from a specified category

To calculate how good two nodes are connected, all the different ways are taken into consideration up to a radius you specify.

Design

Imagen you have

Table customer

Id	Name
101	jose	…
102	maria	…
103	juan	…

And you want to discover new relations.

First you teach your network.

from MyNQL import MyNQL
mynql = MyNQL('store')

mynql.connect('customer.juan', 'product.jeans')
mynql.connect('customer.juan',  'product.socks')
mynql.connect('customer.maria', 'product.socks')

If the colum Name is unique you can use it as a key, otherwise you would need colum Id, and your code would look like this:

mynql.connect("customer.103', 'product.12')

Now you can ask questions from other points of view. You always specify a starting point, and the category where you want to know the best matches:

>>> mynql.select('customer.maria', 'product')
['socks', 'jeans']

Maria is more connected to socks, as she has a direct connection, but also a bit to jeans as there exist an indirect connection through Juan.

>>> mynql.select('product.jeans', 'product')
['socks']

Any combination is valid. For example you can ask about how one product is related to other.

Back-end

Storage is done in memory, but if you want to use MySQL, SQLite or Postgresql as a backend take a look at test/pee_example.py. This will keep a copy of all updates in your database.