A lightweight generator for realistic Indian demographic data based on Census 2011 statistics.
Project description
Indian Fake Data Generator (Python Edition)
A fast, zero-dependency python library that creates realistic mock Indian profile data based on Census 2011 statistics.
Unlike other tools that make impossible combinations (like a Sikh named Mohammed Sharma from Mizoram), this tool links religion, state, caste, gender, and occupation together so the generated people make logical sense.
What It Can Do
- Linked Census Data: Correctly links Religion ➔ State ➔ Caste ➔ Gender ➔ Education ➔ Job ➔ Assets.
- Extra Features: Creates credit and health scores, builds a short text bio, and structures custom LLM Agent Personas.
- No Dependencies: Built entirely using Python's standard library to keep things extremely fast and lightweight.
- Deterministic: Generates the exact same profiles for identical seed numbers.
Installation
pip install indian-fakedata
Quick Start
from indian_fakedata import generate, generate_enriched
# 1. Basic Generation
profiles = generate(count=10)
# 2. Enriched Generation (with outcomes, bios, and LLM agent personas)
enriched_profiles = generate_enriched(count=5)
for p in enriched_profiles:
print(f"Name: {p['fields']['full_name']}")
print(f"Bio: {p['narrative']}")
Saving Datasets (JSON, JSONL, CSV)
Easily format or write your generated data to standard formats:
from indian_fakedata import generate_enriched, save_profiles
# 1. Generate a list of profiles
profiles = generate_enriched(count=100)
# 2. Save directly to a file (JSON, JSONL, or CSV)
save_profiles(profiles, "./output/data.json", "json")
save_profiles(profiles, "./output/data.jsonl", "jsonl")
save_profiles(profiles, "./output/data.csv", "csv") # Automatically flattens outcomes/personas
License
MIT © Abhay Mourya
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