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https://github.com/lk-geimfari/mimesis

Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.
https://github.com/lk-geimfari/mimesis

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

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Mimesis is a powerful Python library that empowers developers to generate massive amounts of synthetic data efficiently.

Lists

README 

        
Mimesis: The Fake Data Generator

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.. image:: https://raw.githubusercontent.com/lk-geimfari/mimesis/master/.github/images/logo.png

     :target: https://github.com/lk-geimfari/mimesis



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Description

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.. image:: https://github.com/lk-geimfari/mimesis/actions/workflows/test.yml/badge.svg?branch=master

     :target: https://github.com/lk-geimfari/mimesis/actions/workflows/test.yml?query=branch%3Amaster

     :alt: Github Actions Test



.. image:: https://readthedocs.org/projects/mimesis/badge/?version=latest

     :target: https://mimesis.name/en/latest/

     :alt: Documentation Status



.. image:: https://codecov.io/gh/lk-geimfari/mimesis/branch/master/graph/badge.svg

     :target: https://codecov.io/gh/lk-geimfari/mimesis

     :alt: Code Coverage



.. image:: https://img.shields.io/pypi/v/mimesis?color=bright-green

     :target: https://pypi.org/project/mimesis/

     :alt: PyPi Version



.. image:: https://img.shields.io/pypi/dm/mimesis

     :target: https://pypi.org/project/mimesis/

     :alt: PyPI - Downloads



.. image:: https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%20pypy-brightgreen

     :target: https://pypi.org/project/mimesis/

     :alt: Python version



Mimesis (`/mɪˈmiːsɪs `_) is a robust data generator for Python that can produce a wide range of fake data in various languages. This tool is useful for populating testing databases, creating fake API endpoints, filling pandas ``DataFrames``, generating JSON and XML files with custom structures, and anonymizing production data, among other purposes.



Installation

------------



To install mimesis, simply use pip:



.. code:: bash



    pip install mimesis



To work with Mimesis on Python versions 3.8 and 3.9, the final compatible version is Mimesis 11.1.0.

Install this specific version to ensure compatibility.



Features

--------



- **Multilingual**: Supports 35 different locales.

- **Extensibility**: Supports custom data providers.

- **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.



Documentation

-------------



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



It is divided into several sections:



-  `About Mimesis`_

-  `Quickstart`_

-  `Locales`_

-  `Data Providers`_

-  `Structured Data Generation`_

-  `Random and Seed`_

-  `Tricks and Tips`_

-  `API Reference`_

-  `Additional Information`_

-  `Changelog`_



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



Usage

-----



The library is exceptionally user-friendly, and it only requires you to import a **Data Provider** object that corresponds to the desired data type.



For instance, the `Person `_ provider can be imported to access personal information, including name, surname, email, and other related fields:



.. code:: python



    >>> from mimesis import Person

    >>> from mimesis.locales import Locale

    >>> person = Person(Locale.EN)



    >>> person.full_name()

    'Brande Sears'



    >>> person.email(domains=['example.com'])

    '[email protected]'



    >>> person.email(domains=['mimesis.name'], unique=True)

    '[email protected]'



    >>> person.telephone(mask='1-4##-8##-5##3')

    '1-436-896-5213'



You can learn more about other providers and locales in our `documentation`_.



How to Contribute

-----------------



1. Take a look at `contributing guidelines`_.

2. Check for open issues or open a fresh issue to start a discussion

   around a feature idea or a bug.

3. Fork the repository on GitHub to start making your changes to the

   *your_branch* branch.

4. Add yourself to the list of `contributors`_.

5. Send a pull request and bug the maintainer until it gets merged and

   published.



License

-------



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

information.



.. _Locales: https://mimesis.name/en/master/locales.html

.. _LICENSE: https://github.com/lk-geimfari/mimesis/blob/master/LICENSE

.. _API Reference: https://mimesis.name/en/master/api.html

.. _Data Providers: https://mimesis.name/en/master/getting_started.html#data-providers

.. _Read the Docs: https://mimesis.name/en/master/

.. _About Mimesis: https://mimesis.name/en/latest/about.html

.. _Quickstart: https://mimesis.name/en/master/quickstart.html

.. _Structured Data Generation: https://mimesis.name/en/master/schema.html

.. _Random and Seed: https://mimesis.name/en/master/random_and_seed.html

.. _Tricks and Tips: https://mimesis.name/en/master/tips.html

.. _Additional Information: https://mimesis.name/en/master/index.html#additional-information

.. _Changelog: https://mimesis.name/en/master/index.html#changelog

.. _documentation: https://mimesis.name/en/latest/getting_started.html#data-providers

.. _contributing guidelines: https://github.com/lk-geimfari/mimesis/blob/master/CONTRIBUTING.rst

.. _contributors: https://github.com/lk-geimfari/mimesis/blob/master/CONTRIBUTORS.rst