Skip to main content

Query Engine API for Distributed AtomSpace

Project description

Hyperon DAS

A data manipulation API for Distributed Atomspace (DAS). It allows queries with pattern matching capabilities and traversal of the Atomspace hypergraph.

References and Guides

Installation

Before you start, make sure you have Python >= 3.10 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 git@github.com:singnet/das-query-engine.git
    cd das-query-engine
    
  3. Install project dependencies using Poetry:

    poetry install
    

    Note: If perhaps you are running over SSH, poetry install might stuck checking the keyring, you can verify this by running poetry install -vvv, then the command will be stuck on the following lines:

    Checking if keyring is available
    [keyring:keyring. backend] Loading KWallet |  
    [keyring:keyring.backend] Loading SecretService |  
    [keyring:keyring. backend] Loading Windows |  
    [keyring: keyring.backend] Loading chainer |  
    [keyring:keyring.backend] Loading libsecret |  
    [keyring:keyring.backend] Loading macOS |  
    Using keyring backend 'SecretService Keyring'
    

    If that is the case, deactivate keyring and run poetry install again:

    poetry config keyring.enabled false
    poetry install
    
  4. Activate the virtual environment created by Poetry:

    poetry shell
    

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

Tests

In the main project directory, you can run the command below to run the unit tests

make unit-tests

Likewise, to run performance tests

make performance-tests

Generating atoms and checking the performance. This test typically takes more than 60 seconds to run with the default settings. Arguments allowed in OPTIONS:

  • --node_count (default: "100"): Number of nodes in the knowledge base
  • --word_count (default: "8"): Number of words in a node's name
  • --word_length (default: "3"): Number of characters in each word of node's name
  • --alphabet_range (default: "2-5"): Determines the range for the alphabet size.
  • --word_link_percentage (default: 0.1): Percentage of word links.
  • --letter_link_percentage (default: 0.1): Percentage of letter links.
  • --seed (default: 11): Sets the random seed for reproducibility (int/float).
  • --repeat (default: 1): (Test only) Repeats test n times to collect average/std deviation of execution time.
  • --mongo_host_port (default: "localhost:15927"): (Test only) Mongo hostname and port. eg: localhost:1234.
  • --mongo_credentials (default: ***:*** ): (Test only) Mongo username and password. eg: user:pass.
  • --redis_host_port (default: "localhost:15926"): (Test only) Redis hostname and port. eg: localhost:1234.
  • --redis_credentials (default: ":"): (Test only) Redis username and password. eg: user:pass.
  • --redis_cluster (default: False): (Test only) Redis cluster configuration.
  • --redis_ssl (default: False): (Test only) Sets Redis SSL.
make benchmark-tests OPTIONS="--word_link_percentage=0.01"

or create a MeTTa file using the same options:

make benchmark-tests-metta-file OPTIONS="--word_link_percentage=0.01"

You can do the same to run integration tests

make integration-tests

The integration tests use a remote testing server hosted on Vultr, at the address 45.63.85.59, port 8080. The loaded knowledge base is the animal base, which contains the Nodes and Links listed below:

(: Similarity Type)
(: Concept Type)
(: Inheritance Type)
(: "human" Concept)
(: "monkey" Concept)
(: "chimp" Concept)
(: "snake" Concept)
(: "earthworm" Concept)
(: "rhino" Concept)
(: "triceratops" Concept)
(: "vine" Concept)
(: "ent" Concept)
(: "mammal" Concept)
(: "animal" Concept)
(: "reptile" Concept)
(: "dinosaur" Concept)
(: "plant" Concept)
(Similarity "human" "monkey")
(Similarity "human" "chimp")
(Similarity "chimp" "monkey")
(Similarity "snake" "earthworm")
(Similarity "rhino" "triceratops")
(Similarity "snake" "vine")
(Similarity "human" "ent")
(Inheritance "human" "mammal")
(Inheritance "monkey" "mammal")
(Inheritance "chimp" "mammal")
(Inheritance "mammal" "animal")
(Inheritance "reptile" "animal")
(Inheritance "snake" "reptile")
(Inheritance "dinosaur" "reptile")
(Inheritance "triceratops" "dinosaur")
(Inheritance "earthworm" "animal")
(Inheritance "rhino" "mammal")
(Inheritance "vine" "plant")
(Inheritance "ent" "plant")
(Similarity "monkey" "human")
(Similarity "chimp" "human")
(Similarity "monkey" "chimp")
(Similarity "earthworm" "snake")
(Similarity "triceratops" "rhino")
(Similarity "vine" "snake")
(Similarity "ent" "human")

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hyperon_das-0.9.13.tar.gz (37.8 kB view details)

Uploaded Source

Built Distribution

hyperon_das-0.9.13-py3-none-any.whl (45.2 kB view details)

Uploaded Python 3

File details

Details for the file hyperon_das-0.9.13.tar.gz.

File metadata

  • Download URL: hyperon_das-0.9.13.tar.gz
  • Upload date:
  • Size: 37.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.6 Linux/6.8.0-1014-azure

File hashes

Hashes for hyperon_das-0.9.13.tar.gz
Algorithm Hash digest
SHA256 0b7913644580c49294aaf8aa70f2ffa04bda4261fa2f44b78aae45ef01d8d723
MD5 064b1dc8cbbb8641ce3d798844ba34d8
BLAKE2b-256 ae1503002c9a6af48672a54bd4c79e3448c874ec7fefe0ca0e14f4140b358881

See more details on using hashes here.

File details

Details for the file hyperon_das-0.9.13-py3-none-any.whl.

File metadata

  • Download URL: hyperon_das-0.9.13-py3-none-any.whl
  • Upload date:
  • Size: 45.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.6 Linux/6.8.0-1014-azure

File hashes

Hashes for hyperon_das-0.9.13-py3-none-any.whl
Algorithm Hash digest
SHA256 b830200ae5d69dd20319627e0a208f5e21869a2a99df6cafb5a1bb2658b142db
MD5 9136d7ad473ad147a054869ece6736d9
BLAKE2b-256 964919dfeca54177be99be0db3a01b357e1498926d48caa1735df85a329841c0

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page