lk-geimfari/mimesis

Mimesis is a Python library for generating fake but realistic data in multiple languages and locales.

Python

4,847

2,700 commits

updated Oct 6, 2026

See the code

README

Mimesis

Mimesis: The Fake Data Generator

Test Coverage Package version Package version Supported Python versions


Documentation: https://mimesis.name/


Mimesis (/mɪˈmiːsɪs) is a Python library for generating fake but realistic data in multiple languages and locales. It can generate names, addresses, dates, phone numbers, emails, financial data, and many other types of values.

It is commonly used to populate test databases, mock API responses, generate JSON or XML fixtures, create sample datasets, and anonymize production data. Mimesis provides a simple, consistent API that makes it easy to generate realistic data for development and testing.

The key features are:

  • Multilingual: Supports 47 different locales.
  • Extensibility: Supports custom data providers and custom field handlers.
  • Ease of use: Features a simple design and clear documentation for straightforward data generation.
  • Performance: Widely recognized as the fastest data generator among Python solutions.
  • Data variety: Includes various data providers designed for different use cases.
  • Schema-based generators: Offers schema-based data generators to effortlessly produce data of any complexity.
  • Relational data: Supports generating related datasets with foreign keys and nested schemas.
  • Intuitive: Great editor support. Fully typed, so you get autocompletion almost everywhere.

Installation

To install Mimesis, use pip:

~ pip install mimesis

Documentation

You can find the complete documentation on the Read the Docs.

It is divided into several sections:

You can improve it by sending pull requests to this repository.

Usage

Import a data provider that corresponds to the data type you need.

For example, the Person provider gives access to personal information, including name, surname, email, and other related fields:

from mimesis import Person
from mimesis.locales import Locale

person = Person(Locale.EN)

person.full_name()
# Output: 'Brande Sears'

person.email(domains=['example.com'])
# Output: 'roccelline1878@example.com'

person.email(domains=['mimesis.name'], unique=True)
# Output: 'f272a05d39ec46fdac5be4ac7be45f3f@mimesis.name'

person.telephone(mask='1-4##-8##-5##3')
# Output: '1-436-896-5213'

License

Mimesis is licensed under the MIT License. See LICENSE for more information.

data
dataframe
datascience
dummy
factory
factory-boy
fake
fixtures
generator
json-generator
mimesis
mock
pandas
polars
python
relational
schema
syntetic
synthetic-data
testing

lk-geimfari/mimesis

Mimesis is a Python library for generating fake but realistic data in multiple languages and locales.

Python

4,847

2,700 commits

updated Oct 6, 2026

See the code

README

Mimesis

Mimesis: The Fake Data Generator

Test Coverage Package version Package version Supported Python versions


Documentation: https://mimesis.name/


Mimesis (/mɪˈmiːsɪs) is a Python library for generating fake but realistic data in multiple languages and locales. It can generate names, addresses, dates, phone numbers, emails, financial data, and many other types of values.

It is commonly used to populate test databases, mock API responses, generate JSON or XML fixtures, create sample datasets, and anonymize production data. Mimesis provides a simple, consistent API that makes it easy to generate realistic data for development and testing.

The key features are:

  • Multilingual: Supports 47 different locales.
  • Extensibility: Supports custom data providers and custom field handlers.
  • Ease of use: Features a simple design and clear documentation for straightforward data generation.
  • Performance: Widely recognized as the fastest data generator among Python solutions.
  • Data variety: Includes various data providers designed for different use cases.
  • Schema-based generators: Offers schema-based data generators to effortlessly produce data of any complexity.
  • Relational data: Supports generating related datasets with foreign keys and nested schemas.
  • Intuitive: Great editor support. Fully typed, so you get autocompletion almost everywhere.

Installation

To install Mimesis, use pip:

~ pip install mimesis

Documentation

You can find the complete documentation on the Read the Docs.

It is divided into several sections:

You can improve it by sending pull requests to this repository.

Usage

Import a data provider that corresponds to the data type you need.

For example, the Person provider gives access to personal information, including name, surname, email, and other related fields:

from mimesis import Person
from mimesis.locales import Locale

person = Person(Locale.EN)

person.full_name()
# Output: 'Brande Sears'

person.email(domains=['example.com'])
# Output: 'roccelline1878@example.com'

person.email(domains=['mimesis.name'], unique=True)
# Output: 'f272a05d39ec46fdac5be4ac7be45f3f@mimesis.name'

person.telephone(mask='1-4##-8##-5##3')
# Output: '1-436-896-5213'

License

Mimesis is licensed under the MIT License. See LICENSE for more information.

data
dataframe
datascience
dummy
factory
factory-boy
fake
fixtures
generator
json-generator
mimesis
mock
pandas
polars
python
relational
schema
syntetic
synthetic-data
testing

Project health

Overall

4.6/10

Maintained

10/10

Code review

2/10
OpenSSF Scorecard

Latest release

22.2.0 · Sep 23, 2026

Releases this year

5

Significant stargazers

(top 24 of 26)

Ash Vardanian

1,452 followers · starred Jul 2022

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1,094 followers · starred Mar 2025

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1,185 followers · starred Mar 2017

Itamar Turner-Trauring

407 followers · starred Jul 2020