mimesis
Mimesis: Fake Data Generator.
What it is and what it does
Mimesis is a pure-Python library for generating realistic but fake data across many locales and data types. It has no runtime dependencies and installs as a single wheel, making it lightweight for development and testing workflows. The library provides a consistent API for generating names, addresses, emails, phone numbers, financial data, and other values in 47 different locales, with full type hints for editor autocompletion.
It is designed for populating test databases, mocking API responses, generating JSON or XML fixtures, creating sample datasets, and anonymizing production data. Beyond simple value generation, Mimesis supports schema-based data generation for complex structures and relational data generation with foreign keys and nested schemas, making it suitable for both simple mock data and sophisticated test-data pipelines.
Use it for:
- Populate test databases with realistic names, addresses, and contact information across multiple locales.
- Generate mock API responses and JSON fixtures for integration and contract testing.
- Create sample datasets for development without exposing real production data.
- Build factory_boy plugins to generate test objects with realistic field values.
- Anonymize production data by replacing sensitive information with generated fake equivalents.
- Generate relational test data with consistent foreign keys and nested structures.
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Mimesis generates realistic fake data across 47 locales—names, addresses, emails, phone numbers, financial records, and more—for populating test databases, mocking APIs, and creating fixtures without external dependencies.
Yes. Mimesis is actively maintained, has no dependencies, supports modern Python versions, carries a permissive MIT license, and solves a common testing need with a mature API. It is well-suited for any project requiring realistic fake data for testing, mocking, or fixtures. No known security vulnerabilities.
Install
mimesis on PyPI
pip
pip install mimesisuv
uv add mimesispoetry
poetry add mimesisInstalling mimesis
Before you install
Low friction: pure Python wheel with no runtime dependencies. Active maintenance (last commit 2026-08-05, release 29 days ago) and strong community signal (4840 GitHub stars). Supports Python 3.10–3.14 and PyPy.
License in practice
MIT license (permissive) places no restrictions on use, modification, or distribution in commercial or private projects.
Quickstart
from mimesis import Person
from mimesis.locales import Locale
person = Person(Locale.EN)
print(person.full_name())
print(person.email(domains=['example.com']))
Requires Python 3.10 or later.
Verify before relying
- Whether the documented 47 locales and data providers remain current in version 21.0.0.
- Performance comparison claims ('fastest data generator among Python solutions') lack independent benchmarking in the fact sheet.
Package facts
| License | MIT (permissive) |
| Python support | supports the current Python release (>=3.10) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | none |
| Maintenance | actively maintained — 29 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,602,524/month — #2,973 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: mimesis-21.0.0-py3-none-any.whl
Keywords: data, database, dataframe, datascince, dummy, factory, factory_boy, fake, faker, fixtures, generate, mimesis, mock, pandas, polars, populate, pytest, schema, testing
Tags
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