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    faker-schema

Generate fake data using joke2k's faker and your own schema


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faker-schema

Generate fake data using joke2k's faker <https://github.com/joke2k/faker>__ and your own schema.

Installation

.. code:: bash

pip install faker-schema

Usage

Getting started ^^^^^^^^^^^^^^^

.. code:: python

from faker_schema.faker_schema import FakerSchema

schema = {'employee_id': 'uuid4', 'employee_name': 'name', 'employee address': 'address',
          'email_address': 'email'}
faker = FakerSchema()
data = faker.generate_fake(schema)
print(data)
# {'employee_id': '956f0cf3-a954-5bff-0aaf-ee0e1b7e1e1b', 'employee_name': 'Adam Wells',
#  'employee address': '189 Kyle Springs Suite 110\nNorth Robin, OR 73512',
#  'email_address': 'jmcgee@gmail.com'}

Available Schema Types ^^^^^^^^^^^^^^^^^^^^^^

This library is dependent on faker <https://github.com/joke2k/faker>__ for availabble schema types. Faker provides a wide variety of data types via providers. For a list of available providers, checkout Providers <http://faker.readthedocs.io/en/master/providers.html>__ and Community Providers <http://faker.readthedocs.io/en/master/communityproviders.html>__

Once you know what types you want to generate your fake data, you can start defining your own schema

Defining your schema ^^^^^^^^^^^^^^^^^^^^

The expected schema is a dictionary, where the keys are field names and the values are the types of the fields. The schema dictionay can have nested dictionaries and lists too.

Loading schemas ^^^^^^^^^^^^^^^

faker-schema currently provides two ways of loading your schema:

  • JSON file
  • JSON string

.. code:: python

import json

from faker_schema.faker_schema import FakerSchema
from faker_schema.schema_loader import load_json_from_file, load_json_from_string

schema = load_json_from_file('path_to_json_file')
faker = FakerSchema()
data = faker.generate_fake(schema)

# OR

json_string = '{"employee_id"": "uuid4", "employee_name": "name"", "employee address":
                "address", "email_address": "email"}'

schema = load_json_from_string(json_string)
faker = FakerSchema()
data = faker.generate_fake(schema)

You can define your own way of loading a schema, convert it to a Python dictionary and pass it to the FakerSchema instance. The aim was to de-couple schema loading/generation from fake data generation. If you want to contribute more schema loading techniques, please open a GitHub issue or send a pull request.

Using different locales ^^^^^^^^^^^^^^^^^^^^^^^

The Faker <https://github.com/joke2k/faker>__ library provides a list of different locales <https://github.com/joke2k/faker#localization>__. You can choose your required locale from that list and provid it to the FakerSchema instance

.. code:: python

from faker_schema.faker_schema import FakerSchema

schema = {'employee_id': 'uuid4', 'employee_name': 'name', 'employee address': 'address',
          'email_address': 'email'}
faker = FakerSchema(locale='it_IT')
data = faker.generate_fake(schema)
print(data)
# {'employee_id': '47f8bb04-fc05-25c9-73cc-e8a22f29ee4e', 'employee_name': 'Caio Negri',
#  'employee address': 'Stretto Davis 34\nDamico lido, 54802 Vibo Valentia (TR)',
#  'email_address': 'nunzia19@libero.it'}

More Schema Examples ^^^^^^^^^^^^^^^^^^^^

Nested Dictionary ^^^^^^^^^^^^^^^^^

.. code:: python

from faker_schema.faker_schema import FakerSchema

schema = {'EmployeeInfo': {'ID': 'uuid4', 'Name': 'name', 'Contact': {'Email': 'email',
          'Phone Number': 'phone_number'}, 'Location': {'Country Code': 'country_code',
          'City': 'city', 'Country': 'country', 'Postal Code': 'postalcode',
          'Address': 'street_address'}}}
faker = FakerSchema()
data = faker.generate_fake(schema)
# {'EmployeeInfo': {'ID': '0751f889-0d83-d05f-4eeb-16f575c6b4a3', 'Name': 'Stacey Williams',
#  'Contact': {'Email':'jpatterson@yahoo.com', 'Phone Number': '1-077-859-6393'},
#  'Location': {'Country Code': 'IE', 'City': 'Dyermouth', 'Country':
#  'United States Minor Outlying Islands', 'Postal Code': '84239',
#  'Address': '94806 Joseph Plaza Apt. 783'}}}

Nested List ^^^^^^^^^^^

.. code:: python

from faker_schema.faker_schema import FakerSchema

schema = {'Employer': 'name', 'EmployeList': [{'Name': 'name'}, {'Name': 'name'},
          {'Name': 'name'}]}
faker = FakerSchema()
data = faker.generate_fake(schema)
# {'Employer': 'Faith Knapp', 'EmployeList': [{'Name': 'Douglas Bailey'},
# {'Name': 'Karen Rivera'}, {'Name': 'Linda Vance MD'}]}

Generating a certain number of fake data from given schema ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. code:: python

from faker_schema.faker_schema import FakerSchema

schema = {'employee_id': 'uuid4', 'employee_name': 'name', 'employee address': 'address',
          'email_address': 'email'}
faker = FakerSchema()
data = faker.generate_fake(schema, iterations=4)
print(data)
# [{'employee_id': 'e07a7964-9636-bca6-2a58-4a69ac126dc5', 'employee_name':
# 'Charlene Blankenship', 'employee address': '0431 Edward Mountains Suite 697\nPort Douglas,
# TX 96239-7277', 'email_address': 'ashley86@yahoo.com'}, {'employee_id':
# '42b02262-3e0c-cf40-8257-4a0af122dddb', 'employee_name': 'Cheryl Stevens',
# 'employee address': '48066 Eric Lake\nPhillipshire, MO 57224', 'email_address':
# 'lisa05@nash.info'}, {'employee_id': '41efbcc4-bb32-9260-b2b3-8fac29782e01',
# 'employee_name': 'Dennis Campbell', 'employee address':
# '52418 Diana Mills Suite 590\nEast Mackenzie, HI 16222', 'email_address':
# 'jennifer39@gmail.com'}, {'employee_id': '80bf12ff-2f3a-6db6-f3a6-14cb50076a46',
# 'employee_name': 'Jimmy Avery', 'employee address':
# '6867 Eddie Forest Apt. 735\nBranditon, IL 32717', 'email_address': 'ashley64@griffin.com'}]

BYOP (Bring Your Own Provider) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

If you are using a community provider or you created your own provider, you can use those with faker-schema as well. I will use the provider, faker\_web <https://github.com/thiagofigueiro/faker_web>__ as an example.

After installing <https://github.com/thiagofigueiro/faker_web#usage>__ faker_web,

.. code:: python

from faker import Faker
from faker_schema import FakerSchema
from faker_web import WebProvider

fake = Faker()
fake.add_provider(WebProvider)

faker = FakerSchema(faker=fake)
headers_schema = {'Content-Type': 'content_type', 'Server': 'server_token'}
fake_headers = faker.generate_fake(headers_schema)
print(fake_headers)
# {'Content-Type': 'application/json', 'Server': 'Apache/2.0.51 (Ubuntu)'} 

Development

Running tests


-  Using make

.. code:: bash

    make test

-  Using nose

.. code:: bash

    nosetests 

-  Using nose with coverage

.. code:: bash

    nosetests --with-coverage --cover-package=faker_schema --cover-erase -v --cover-html

Running flake8
  • Using make

.. code:: bash

make flake8
  • Using flake8

.. code:: bash

flake8 --max-line-length 99 faker_schema/ tests/

Author

Usman Ehtesham Gul (ueg1990 <https://github.com/ueg1990>__) - uehtesham90@gmail.com

Contribute

If you want to add any new features, or improve existing one or if you find bugs, please open a GitHub issue or feel free to send a pull request. If you have any questions or need help/mentoring with contributions, feel free to contact me via email

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