Tips and Tricks

Creating objects

If your app requires data in one particular language, it’s preferable to use class Generic(), giving access to all class providers through a single object, rather than through multiple separate class providers. Using Generic() will allow you to get rid of several extra lines of code.


from mimesis import Person, Datetime, Text, Code
from mimesis.locales import Locale

person = Person(Locale.RU)
datetime = Datetime(Locale.RU)
text = Text(Locale.RU)
code = Code(Locale.RU)


from mimesis import Generic
from mimesis.locales import Locale
generic = Generic(locale=Locale.EN)

# Output: 'sherley3354'
# Output: '14-05-2007'

Still correct:

from mimesis import Person
from mimesis.locales import Locale

p_en = Person(Locale.EN)
p_sv = Person(Locale.SV)

Also correct:

from mimesis import Person

person = Person(Locale.EN)
with person.override_locale(Locale.SV)

It means that importing class providers separately makes sense only if you limit yourself to the data available through the class you imported, otherwise it’s better to use Generic().

Inserting data into database

If you need to generate data and import it into a database we strongly recommend generating data in chunks rather than 600k at once. Keep in mind the possible limitations of databases, ORM, etc. The smaller the generated data chunks are, the faster the process will go. Below you can see an abstract example of a Django command which uses Mimesis to bootstrap database.


~ python fill_fake_db --count=1000 --locale=de

Very bad:

~ python fill_fake_db --count=600000 --locale=de

Romanization of Cyrillic data

If your locale belongs to the family of Cyrillic languages, but you need romanized locale-specific data, then you can use function romanize() which help you romanize your data.

Example of usage for romanization of Russian full name:

from mimesis.shortcuts import romanize
from mimesis.locales import Locale

romanize("Вероника Денисова", locale=Locale.RU)
# Output: 'Veronika Denisova'

At this moment it works only for Russian (ru), Ukrainian (uk) and Kazakh (kk):

Dummy API Endpoints

You can create dummy API endpoints when you have not data, but need them and know the structure of the endpoint’s response.

Let’s define the structure of the dummy response.

from mimesis.schema import Field, Schema
from mimesis.locales import Locale
from mimesis.enums import Gender

_ = Field(Locale.EN)
dummy_users = Schema(
    lambda: {
        'id': _('uuid'),
        'name': _('name', gender=Gender.MALE),
        'surname': _('surname', gender=Gender.MALE),
        'email': _('email'),
        'age': _('age'),
        'username': _('username', template='UU_d'),
        'occupation': _('occupation'),
        "address": {
            "street": _('street_name'),
            "city": _('city'),
            "zipcode": _('zip_code'),

Now, you can return unique response with JSON for each request.

Django/DRF Dummy API Endpoint

Basically you need just create simple view, which returns JsonResponse:

from dummy_endpoints import dummy_users

def users(request):
    dummy_data = dummy_users.create(iterations=1)
    return JsonResponse(dummy_data)

For DRF the same, but in terms of DRF:

from dummy_endpoints import dummy_users

class Users(APIView):
    def get(self, request):
        data = dummy_users.create(iterations=1)
        return Response(data)


    "id": "a46313ab-e218-41cb-deee-b9afd755a4dd",
    "name": "Wally",
    "surname": "Stein",
    "email": "",
    "age": 51,
    "username": "SystemicZeuzera_1985",
    "occupation": "Travel Courier",
    "address": {
      "street": "Lessing",
      "city": "Urbandale",
      "zipcode": "03983"

Flask Dummy API Endpoint

The same way as above:

from dummy_endpoints import dummy_users

def users():
    dummy_data = dummy_users.create(iterations=1)
    return jsonify(dummy_data)


    "id": "f2b326e3-4ce7-1ae9-9e6d-34a28fb70106",
    "name": "Johnny",
    "surname": "Waller",
    "email": "",
    "age": 47,
    "username": "CaterpillarsSummational_1995",
    "occupation": "Scrap Dealer",
    "address": {
      "street": "Tonquin",
      "city": "Little Elm",
      "zipcode": "30328"

Integration with third-party libraries