Skip to main content

Useful implementations of data structures and design patterns for AI knowledge bases.

Project description

DataKnobs

Description

Useful implementations of data structures and design patterns for knowledge bases and AI, or the knobs and levers for fine-tuning and leveraging your data.

This repo also serves as a template or sandbox for development, experimentation, and testing of general data structures, algorithms, and utilities for DS, AI, ML, and NLP.

Provides connectors for other popular text and data processing packages like:

  • numpy and pandas
  • nltk
  • wordnet
  • postgres
  • elasticsearch

General project information

The purpose of this project is:

  • To provide dependable implementations of useful data structures.
  • To show examples of design patterns and ways to apply AI concepts.
  • To prototype tools for delivering a robust DS/AI/ML/NLP utilities library package.
  • To facilitate interactive development, demonstration, visualization, and testing of the library components via jupter notebooks and/or scripts.

Installation and Usage

% pip install dataknobs
% python
>>> import dataknobs as dk
>>> ...

Development

Development machine prerequisites

The following minimum configuration should exist for development:

  • tox
  • pyenv
    • pyenv install 3.9
  • poetry

With optional:

  • docker
  • bash

By convention, a data directory can be leveraged for development that is mounted as a shared volumne in Docker as /data. This has the default of $HOME/data, but can be overridden with the DATADIR environment variable.

Development quickstart guide

  • In a terminal, clone the repo and cd into the project directory.

Testing

  • Tests and Lint: "tox"
  • Just unit tests: "tox -e tests"
  • Just lint: "tox -e lint"

Using docker

  • Development:
% tox -e dev
# poetry shell
# python
  • Notebook:
    • execute "tox -e nb"
      • copy/paste url into browser

Using virtual environments

  • Development:

    • Manual: source ".project_vars", poetry install, poetry shell
    • Automated: execute "bin/start_dev.sh" (requires "/bin/bash" on your machine)
  • Notebook:

    • execute "bin/start_notebook.sh"
      • copy/paste url into browser

Project details


Download files

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

Source Distribution

dataknobs-0.0.14.tar.gz (79.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dataknobs-0.0.14-py3-none-any.whl (91.7 kB view details)

Uploaded Python 3

File details

Details for the file dataknobs-0.0.14.tar.gz.

File metadata

  • Download URL: dataknobs-0.0.14.tar.gz
  • Upload date:
  • Size: 79.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.1 CPython/3.13.2 Linux/6.10.14-linuxkit

File hashes

Hashes for dataknobs-0.0.14.tar.gz
Algorithm Hash digest
SHA256 3a29d70098a5d48869f09bf3a0b4efb8e3f110b2c3df1940c6ec412a56dc2488
MD5 c86660dcb75b35d59ecd52593e47a8e0
BLAKE2b-256 4e143e61cf48280b67a97243ce27fb5b88264ef115637d8f8e7fe86cbde7453b

See more details on using hashes here.

File details

Details for the file dataknobs-0.0.14-py3-none-any.whl.

File metadata

  • Download URL: dataknobs-0.0.14-py3-none-any.whl
  • Upload date:
  • Size: 91.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.1 CPython/3.13.2 Linux/6.10.14-linuxkit

File hashes

Hashes for dataknobs-0.0.14-py3-none-any.whl
Algorithm Hash digest
SHA256 a51ccb1bf17191013fd4a9a3962b9fde97747fb2078b5e105a17e50d28f02241
MD5 b344e2e6d4b06008b3897372966496ce
BLAKE2b-256 fac7871878d941cf23d6b0aead70e88c29888e7a1c3de2c5d22b129398add799

See more details on using hashes here.

Supported by

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