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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=["numbers"]
)

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"]
)

Create a Proficiency Score, by name

A Proficiency Score represents a person's level of proficiency in a specific topic.

from openproficiency import ProficiencyScore, ProficiencyScoreName

proficiency_score = ProficiencyScore(
    topic_id="addition",
    score=ProficiencyScoreName.PROFICIENT
)

Create a Proficiency Score, numerically

All score are internally numeric from 0.0 to 1.0, even if set using the score name (above).

from openproficiency import ProficiencyScore

proficiency_score = ProficiencyScore(
    topic_id="arithmetic",
    score=0.8 # Same as 'ProficiencyScoreName.PROFICIENT'
)

Issue a Transcript Entry

A Transcript Entry associates a proficiency score to a user and is claimed by an issuer.

from openproficiency import TranscriptEntry

# Create a transcript entry
entry = TranscriptEntry(
    user_id="first.last@my-email.com",
    topic_id="arithmetic",
    score=0.9,
    issuer="example.com"
)

# Access the transcript entry information
print(entry.user_id)  # john-doe
print(entry.proficiency_score.score)  # 0.9
print(entry.issuer)  # university-of-example
print(entry.timestamp)  # datetime object

# Convert to JSON for storage or transmission
entry_json = entry.to_json()

How to Develop

This project is open to pull requests.

Please see the contribution guide to get started.

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objects for managing proficiency across knowledge domains

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