personalitygen 0.1.1

Generate and manage simulated human-like personalities based on the Big Five model.

personalitygen

personalitygen generates and manages simulated human-like personalities based on the Big Five (OCEAN) model. It is designed for simulation, storytelling, and testing scenarios where you want plausible, varied personality profiles without running surveys.

Intent and scope

• Generate full Big Five profiles with sub-trait components and aggregate scores.
• Bias outputs by life stage using tuned Gaussian distributions (child, young adult, adult).
• Derive a conflict-resolution style from trait weights, plus mapped concern-for-self/others.
• Support deterministic generation by accepting a seeded random source.
• Stay lightweight and dependency-free (pure Python).

This package is not a clinical assessment tool and does not implement questionnaires or scoring rubrics.

Model overview

• Big Five traits: openness, conscientiousness, extraversion, agreeableness, neuroticism.
• Each trait is composed of three sub-traits and a weighted aggregate score.
• Life stage influences distribution means and standard deviations for sampling.
• Conflict-resolution style is selected from avoiding, obliging, integrating, dominating, or compromising based on trait scores.

Usage

from personalitygen import BigFivePersonality, LifeStage

personality = BigFivePersonality.random(LifeStage.ADULT)
print(personality.trait_configuration)
print(personality.conflict_resolution_configuration)

If you want deterministic output, pass a seeded random number generator:

import random
from personalitygen import BigFiveTraitConfiguration, LifeStage

rng = random.Random(42)
traits = BigFiveTraitConfiguration.random(LifeStage.YOUNG_ADULT, rng=rng)
print(traits)

Development

pdm install --group dev
pdm run test