lk-geimfari/mimesis

Health v2 · maintenance only

Adoption not part of the score

4839 stars · 361 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Mimesis is a Python library for generating fake but realistic data across 47 locales, covering names, addresses, dates, financial data, and more. It supports schema-based and relational data generation, making it suitable for populating test databases, mocking APIs, and creating sample datasets.

Use cases

• generate fake user data for tests
• populate a test database with realistic records
• mock API responses with dummy JSON
• create sample pandas or polars dataframes
• anonymize production data
• generate localized fake data in multiple languages
• build relational fixtures with foreign keys

When to choose

• you need fast, multilingual fake data generation in Python
• you want schema-based or relational synthetic datasets
• you need typed APIs with good editor autocompletion
• you are replacing Faker for performance reasons

When to avoid

• you need fake data in a language other than Python
• you need production-grade real data rather than synthetic data
• you require a plugin ecosystem as large as Faker's

Facets

library · maturity stable

data-generation testing mocking serialization developer-tools testing data-science python cross-platform fake-data faker-alternative fixtures synthetic-data multilingual locales schema-based pandas polars data-anonymization automation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="lk-geimfari/mimesis")