Skip to main content

Mimesis: mock data for developers.

Project description

http://bit.ly/2D9cp18

Mimesis

Mimesis is a fast and easy to use the library for Python programming language, which helps generate mock data for a variety of purposes in a variety of languages. This data can be particularly useful during software development and testing. For example, it could be used to populate a testing database for a web application with user information such as email addresses, usernames, first names, last names, etc.

Documentation

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

Installation

To install mimesis, simply use pip (or pipenv):

  ~ pip install mimesis

Getting started

As we said above, this library is really easy to use. A simple usage example is given below:

>>> from mimesis import Personal
>>> from mimesis.enums import Gender
>>> person = Personal('en')

>>> person.full_name(gender=Gender.FEMALE)
'Antonetta Garrison'

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

>>> for template in ('U_d', 'U-d', 'l_d', 'l-d'):
...     person.username(template=template)

'Adders_1893'
'Abdel-1888'
'constructor_1884'
'chegre-2051'

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. Mimesis currently includes support for 33 different locales.

Data Providers

List of supported data providers available here

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mimesis-1.0.5.tar.gz (2.4 MB view details)

Uploaded Source

Built Distribution

mimesis-1.0.5-py3-none-any.whl (2.4 MB view details)

Uploaded Python 3

File details

Details for the file mimesis-1.0.5.tar.gz.

File metadata

  • Download URL: mimesis-1.0.5.tar.gz
  • Upload date:
  • Size: 2.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for mimesis-1.0.5.tar.gz
Algorithm Hash digest
SHA256 3b8e376f1377c40d99db4cdf4d3ed9bb2ebfe7343b653e41738126dcb9aaaac9
MD5 6de7c0634a297e4392ef22d3519a3621
BLAKE2b-256 abc78d83b926b32f511ac71131e15b70993e069f4fa0e3d644177c4daf72c1f7

See more details on using hashes here.

File details

Details for the file mimesis-1.0.5-py3-none-any.whl.

File metadata

File hashes

Hashes for mimesis-1.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 17637710c2e830bdf90f3d65f2f2aaa77f42cc31fec323c6181bb75500d9bd64
MD5 6b63467ee5d14f7aff8e537ae946be00
BLAKE2b-256 5229598e583adc8199d1c93c1fc541862a5bfd1ab15f9cdc3b89bd5d12ba30c5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page