hyperon-das 0.3.6

Query Engine API for Distributed AtomSpace

Hyperon DAS

Hi! This package is a query engine API for Distributed AtomSpace (DAS). When is possible execute queries using Pattern Matcher

Table of Contents

• Hyperon DAS
  • Table of Contents
  • Installation
    • Using-pip
    • Using-Poetry
  • Usage
    • Redis and MongoDB
      • Create a client API
    • In Memory
  • Tests

Installation

Before you start, make sure you have Python >= 3.8.5 and Pip installed on your system.

You can install and run this project using different methods. Choose the one that suits your needs.

Using-pip

Run the following command to install the project using pip::

pip install hyperon-das

Using-Poetry

If you prefer to manage your Python projects with Poetry, follow these steps:

1. Install Poetry (if you haven't already):

   pip install poetry
   

2. Clone the project repository:

   git clone [e-mail]:singnet/das-query-engine.git
   cd das-query-engine
   

3. Install project dependencies using Poetry:

   poetry install
   

4. Activate the virtual environment created by Poetry:

   poetry shell
   

Now you can run the project within the Poetry virtual environment.

Usage

So far we have two ways of making queries using the API. One that uses database persistence and another that doesn't. The way to create and execute the query is exactly the same, the only difference is when you need to instantiate the API class. Below you can see more details.

Redis and MongoDB

If you want to use data persistence, you must have Redis and MongoDB running in your environment and you must have the following variables configured with their respective values:

Example:

DAS_MONGODB_HOSTNAME=172.17.0.2
DAS_MONGODB_PORT=27017
DAS_MONGODB_USERNAME=mongo
DAS_MONGODB_PASSWORD=mongo
DAS_REDIS_HOSTNAME=127.0.0.1
DAS_REDIS_PORT=6379

TIP: You can change the values in the environment file, which is in the root directory and run the command below:

source environment

Create a client API

from hyperon_das import DistributedAtomSpace

api = DistributedAtomSpace('redis_mongo')

In Memory

This way you don't need anything just instantiate the class as shown below:

1. A simple query which is a AND operation on two links whose targets are variables.

   from hyperon_das import DistributedAtomSpace
   from hyperon_das.pattern_matcher import And, Variable, Link
   from hyperon_das.utils import QueryOutputFormat
   
   api = DistributedAtomSpace('ram_only')
   
   api.add_link({
       'type': 'Evaluation',
       'targets': [
           {'type': 'Predicate', 'name': 'Predicate:has_name'},
           {
               'type': 'Evaluation',
               'targets': [
                   {'type': 'Predicate', 'name': 'Predicate:has_name'},
                   {
                       'type': 'Set',
                       'targets': [
                           {'type': 'Reactome', 'name': 'Reactome:R-HSA-164843'},
                           {'type': 'Concept', 'name': 'Concept:2-LTR circle formation'},
                       ]
                   },
               ],
           },
       ],
   })
   
   expression =  Link("Evaluation",  ordered=True,  targets=[Variable("V1"), Variable("V2")])
   
   resp = api.pattern_matcher_query(expression, {'return_type': QueryOutputFormat.JSON, 'toplevel_only': True})
   
   print(resp)
   

   [
       {
           "V1": {
               "type": "Predicate",
               "name": "Predicate:has_name",
               "is_link": false,
               "is_node": true
           },
           "V2": {
               "type": "Evaluation",
               "targets": [
                   {
                       "type": "Predicate",
                       "name": "Predicate:has_name"
                   },
                   {
                       "type": "Set",
                       "targets": [
                           {
                               "type": "Reactome",
                               "name": "Reactome:R-HSA-164843"
                           },
                           {
                               "type": "Concept",
                               "name": "Concept:2-LTR circle formation"
                           }
                       ]
                   }
               ],
               "is_link": true,
               "is_node": false
           }
       }
   ]
   

2. Add Node and And Link (It's possible only using Ram Only)

   api.count_atoms() # (0, 0)
   
   nodes = [
       {
           'type': 'Reactome',
           'name': 'Reactome:R-HSA-164843',
       },
       {
           'type': 'Concept',
           'name': 'Concept:2-LTR circle formation',
       }
   ]
   
   for node in nodes:
       api.add_node(node)
   
   api.count_atoms() # (2, 0)
   
   link = {
       'type': 'Evaluation',
       'targets': [
           {
               'type': 'Predicate',
               'name': 'Predicate:has_name'
           },
           {
               'type': 'Evaluation',
               'targets': [
                   {
                       'type': 'Predicate',
                       'name': 'Predicate:has_name'
                   },
                   {
                       'type': 'Set',
                       'targets': [
                           {
                               'type': 'Reactome',
                               'name': 'Reactome:R-HSA-164843',
                           },
                           {
                               'type': 'Concept',
                               'name': 'Concept:2-LTR circle formation',
                           },
                       ]
                   },
               ],
           },
       ],
   }
   
   api.add_link(link)
   
   api.count_atoms() # (3, 3)
   

   Note1: in this example I add 2 nodes and 1 a link, but in the end I have 3 nodes and 3 links. Therefore, it is possible to add nested links and as links are composed of nodes, if the link node doesn't exist in the system it's added.

   Note2: For these methods to work well, both nodes and links must be a dict with the structure shown above, i.e, for nodes you need to send, at least, the parameters type and name and for links type and targets

Tests

You can run the command below to run the unit tests

make test-coverage