Skip to main content

A simple library for managing proficiency topics and topic lists

Project description

OpenProficiency - Python Library

This library provides class objects for managing proficiency across knowledge domains.

Features

  • Topic Class: A defined unique area of knowledge composed of subtopics and built upon pretopics (prerequisite topics).
  • TopicList Class: A collection of related topics covering one knowledge domain.

Installation

pip install openproficiency

Quick Start

Create a Topic

A Topic is an area of knowledge that a person gains proficiency in. If it has subtopics, the person can alternately gain proficiency in the parent topic by gaining proficiency in the subtopics.

from openproficiency import Topic

# Create a simple topic and what composes it
topic_arithmetic = Topic(
    id="arithmetic",
    description="Basic operations for numeric calculations",
    subtopics=["addition", "subtraction"]
    pretopics=['writing']
)

Add a subtopic to an existing topic

# Specific other topics that compose the parent topic
topic_arithmetic.add_subtopic("multiplication")
topic_arithmetic.add_subtopic("division")

Add a pretopic to an existing topic

A Pretopic (prerequisite topic) is a topic that must be understood before a person can begin understanding the parent topic.

# Specify prerequisites to understand first
topic_arithmetic.add_pretopic("integers")
topic_arithmetic.add_pretopic("decimals")
topic_arithmetic.add_pretopic("fractions")

Create a Topic List

A topic list is a collection of topics that describe a specific knowledge domain.

from openproficiency import Topic, TopicList

# Create an empty topic list
topic_list = TopicList(
    owner="core-fundamentals",
    name="math",
    description="Math topics through basic calculus"
)

# Add topics to the list
t_arithmetic = Topic(
    id="arithmetic",
    description="Basic operations for numeric calculations",
    subtopics=[
        "addition",
        "subtraction",
        "multiplication",
        "division
    ]
)
topic_list.add_topic(t_arithmetic)

t_algebra = Topic(
    id="algebra",
    description="Basic operations for numeric calculations",
    subtopics=[
        "variables",
        "constants",
        "single-variable-equations",
        "multiple-variable-equations"
    ],
    pretopics=[ "arithmetic" ]
)

How to Develop

This project is open to pull requests.

Please see the contribution guide to get started.

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

openproficiency-0.0.1.tar.gz (12.8 kB view details)

Uploaded Source

Built Distribution

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

openproficiency-0.0.1-py3-none-any.whl (6.4 kB view details)

Uploaded Python 3

File details

Details for the file openproficiency-0.0.1.tar.gz.

File metadata

  • Download URL: openproficiency-0.0.1.tar.gz
  • Upload date:
  • Size: 12.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for openproficiency-0.0.1.tar.gz
Algorithm Hash digest
SHA256 4e3ca5acc395d5f678adab29380b347a4722d819056ce4664aa3b79cf6ee8728
MD5 c6c1c857720fedbb6b581a72cdaa83b6
BLAKE2b-256 579c5c79e896358a48d4f044ca7655c89c6c5c86a1ca4d92709c1241f0d6b708

See more details on using hashes here.

File details

Details for the file openproficiency-0.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for openproficiency-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 35dad09ecec35b2174f6efdd0daf51621f712c81802316a77cd52ce4ad20fb49
MD5 eab71c00d6903f564c7ef0e1955f917e
BLAKE2b-256 cbca7e152adedf334540aef6448c3356169bb8b44b1ec3b287f64be7c6de071f

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