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Mimesis is a fast and easy to use library for Python, which helps generate mock data for a variety of purposes (see "Data providers") in a variety of languages (see "Locales"). This data can be particularly useful during software development and testing. The library was written with the use of tools from the standard Python library, and therefore, it does not have any side dependencies.

Mimesis is very simple to use, and the below examples should help you get started. Complete documentation for Mimesis is available here.

To install mimesis, simply:

➜  ~ pip install mimesis

Also you can install it manually:

(env) ➜  python3 setup.py install

As we said above, this library is really easy to use:

>>> import mimesis
>>> person = mimesis.Personal(locale='en')

>>> person.full_name(gender='female')
'Antonetta Garrison'

>>> person.occupation()
'Backend Developer'

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:

>>> from mimesis import Personal

>>> de = Personal('de')
>>> ic = Personal('is')

>>> de.full_name()
'Sabrina Gutermuth'

>>> ic.full_name()
'Rósa Þórlindsdóttir'

Mimesis currently includes support for 30 different locales. See details for more information.

When you only need to generate data for a single locale, use the Generic() provider, and you can access all providers of Mimesis from one object.

>>> import mimesis
>>> g = mimesis.Generic('es')

>>> g.datetime.month()
'Agosto'

>>> g.food.fruit()
'Limón'

Mimesis support over twenty different data providers available, which can produce data related to food, people, computer hardware, transportation, addresses, and more. See details for more information.

Mimesis offers a number of advantages over other similar libraries, such as Faker:

• Performance. Mimesis is significantly faster than other similar libraries.
• Completeness. Mimesis strives to provide many detailed providers that offer a variety of data generators.
• Simplicity. Mimesis does not require any modules other than the Python standard library.

See here for an example of how we compare performance with other libraries.

You can use Mimesis during development and testing of applications built on a variety of frameworks. Here is an example of integration with a Flask application:

class Patient(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    full_name = db.Column(db.String(100))
    blood_type = db.Column(db.String(64))

    def __init__(self, **kwargs):
        super(Patient, self).__init__(**kwargs)

    @staticmethod
    def populate(count=500, locale=None):
        import mimesis

        person =  mimesis.Personal(locale=locale)

        for _ in range(count):
            patient = Patient(
                full_name=person.full_name('female'),
                blood_type=person.blood_type(),
            )

            db.session.add(patient)
            try:
                db.session.commit()
            except IntegrityError:
                db.session.rollback()

Just run shell mode and do following:

>>> Patient().populate(count=1000, locale='en')

Mimesis support generating data by schema:

>>> from mimesis.schema import Schema
>>> schema = Schema('en')

>>> schema.load(schema={
...     "id": "cryptographic.uuid",
...     "name": "text.word",
...     "version": "development.version",
...     "owner": {
...         "email": "personal.email",
...         "token": "cryptographic.token",
...         "creator": "personal.full_name"
...     }
... }).create(iterations=2)

>>> # or you can load data from json file:
>>> schema.load(path='schema.json').create(iterations=2)

Result:

[
  {
    "id": "790cce21-5f75-2652-2ee2-f9d90a26c43d",
    "name": "container",
    "owner": {
      "email": "[email protected]",
      "token": "0bf924125640c46aad2a860f40ec4b7f33a516c497957abd70375c548ed56978",
      "creator": "Ileen Ellis"
    },
    "version": "4.11.6"
  },
  ...
]

You also can add custom provider to Generic(), using add_provider() method:

>>> import mimesis
>>> generic = mimesis.Generic('en')

>>> class SomeProvider(object):
...     class Meta:
...         name = "some_provider"
...
...     def hello(self):
...         return "Hello!"

>>> class Another(object):
...     def bye(self):
...         return "Bye!"

>>> generic.add_provider(SomeProvider)
>>> generic.add_provider(Another)

>>> generic.some_provider.hi()
'Hello!'

>>> generic.another.bye()
'Bye!'

or multiple custom providers using method add_providers():

>>> generic.add_providers(SomeProvider, Another)

Some countries have data types specific to that country. For example social security numbers (SSN) in the United States of America (en), and cadastro de pessoas físicas (CPF) in Brazil (pt-br). If you would like to use these country-specific providers, then you must import them explicitly:

>>> from mimesis import Generic
>>> from mimesis.builtins import BrazilSpecProvider

>>> generic = Generic('pt-br')
>>> generic.add_provider(BrazilSpecProvider)
>>> generic.brazil_provider.cpf()
'696.441.186-00'

If your locale belongs to the family of Cyrillic languages, but you need latinized locale-specific data, then you can use special decorator which help you romanize your data. At this moment it's works only for Russian and Ukrainian:

>>> from mimesis.decorators import romanized

>>> @romanized('ru')
... def russian_name():
...     return 'Вероника Денисова'

>>> russian_name()
'Veronika Denisova'

The authors assume no responsibility for how you use this library data generated by it. This library is designed only for developers with good intentions. Do not use the data generated with Mimesis for illegal purposes.

Your contributions are always welcome! Please take a look at the contribution guidelines first. Here you can look at list of our contributors.

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