Mimesis: Fake Data Generator.
Project description
Mimesis: The Fake Data Generator
Description
Mimesis (/mɪˈmiːsɪs, Ancient Greek: μίμησις, mīmēsis) is a high-performance fake data generator for Python, which provides data for a variety of purposes in a variety of languages. The fake data could be used to populate a testing database, create fake API endpoints, create JSON and XML files of arbitrary structure, anonymize data taken from production and etc.
Installation
To install mimesis, simply use pip:
pip install mimesisPython compatibility
Mimesis supports Python 3.8 (also PyPy 3.8), 3.9, and 3.10.
The Mimesis 4.1.3 is the last to support Python 3.6 and 3.7.
Supported Features
Easy: Designed to be easy to use and learn.
Multilingual: Supports data for a lot of languages.
Performance: The fastest data generator available for Python.
Data variety: Supports a lot of data providers for a variety of purposes.
Country-specific data providers: Provides data specific only for some countries.
Extensibility: You can create your own data providers and use them with Mimesis.
Generic data provider: The simplified access to all the providers from a single object.
Zero hard dependencies: Does not require any modules other than the Python standard library.
Schema-based generators: Provides an easy mechanism to generate data by the schema of any complexity.
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
This library is really easy to use and everything you need is just import an object which represents a type of data you need (we call such object a Provider).
In the example below we import provider Person, which represents data related to personal information, such as name, surname, email and etc:
>>> from mimesis import Person
>>> from mimesis.locales import Locale
>>> person = Person(Locale.EN)
>>> person.full_name()
'Brande Sears'
>>> person.email(domains=['example.com'])
'roccelline1878@example.com'
>>> person.email(domains=['mimesis.name'], unique=True)
'f272a05d39ec46fdac5be4ac7be45f3f@mimesis.name'
>>> person.telephone(mask='1-4##-8##-5##3')
'1-436-896-5213'More about the other providers you can read in our documentation.
Locales
Mimesis currently includes support for 34 different locales. You can specify a locale when creating providers and they will return data that is appropriate for the language or country associated with that locale.
Let’s take a look how it works:
>>> from mimesis import Person
>>> from mimesis.locales import Locale
>>> from mimesis.enums import Gender
>>> de = Person(locale=Locale.DE)
>>> en = Person(locale=Locale.EN)
>>> de.full_name(gender=Gender.FEMALE)
'Sabrina Gutermuth'
>>> en.full_name(gender=Gender.MALE)
'Layne Gallagher'Providers
Mimesis support over twenty different data providers available, which can produce data related to people, food, computer hardware, transportation, addresses, internet and more.
You can generate a lot of extremely detailed data:
>>> from mimesis import Internet
>>> from mimesis.enums import URLScheme
>>> internet = Internet()
>>> internet.url(scheme=URLScheme.WSS, subdomains=["chat"])
'wss://chat.system.io/'See API Reference and Data Providers for more info.
How to Contribute
Take a look at contributing guidelines.
Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug.
Fork the repository on GitHub to start making your changes to the your_branch branch.
Add yourself to the list of contributors.
Send a pull request and bug the maintainer until it gets merged and published.
Useful links
I have a Telegram channel where I daily post news, announces and all the open-source goodies I found, so subscribe: @software_dev_channel.
Disclaimer
The authors of Mimesis do not assume any responsibility for how you use it or how you use data generated with it. This library was designed with good intentions to make testing easier. Do not use the data generated with Mimesis for illegal purposes.
License
Mimesis is licensed under the MIT License. See LICENSE for more information.
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