ueg1990/faker-schema — 93 Stars

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#faker #python #schema

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Python 97.9%

Makefile 2.1%

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README

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 fakerschema.fakerschema import FakerSchema

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

This library is dependent on faker <https://github.com/joke2k/faker>__ for available 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 fakerschema.fakerschema import FakerSchema from fakerschema.schemaloader import loadjsonfromfile, loadjsonfromstring

schema = loadjsonfromfile('pathtojsonfile') faker = FakerSchema() data = faker.generate_fake(schema)

# OR

jsonstring = '{"employeeid"": "uuid4", "employee_name": "name"", "employee address": "address", "email_address": "email"}'

schema = loadjsonfromstring(jsonstring) 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 provide it to the FakerSchema instance

.. code:: python

from fakerschema.fakerschema import FakerSchema

schema = {'employeeid': 'uuid4', 'employeename': 'name', 'employee address': 'address', 'email_address': 'email'} faker = FakerSchema(locale='it_IT') data = faker.generate_fake(schema) print(data) # {'employeeid': '47f8bb04-fc05-25c9-73cc-e8a22f29ee4e', 'employeename': '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 fakerschema.fakerschema import FakerSchema

schema = {'EmployeeInfo': {'ID': 'uuid4', 'Name': 'name', 'Contact': {'Email': 'email', 'Phone Number': 'phonenumber'}, 'Location': {'Country Code': 'countrycode', '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 fakerschema.fakerschema 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 fakerschema.fakerschema import FakerSchema

schema = {'employeeid': 'uuid4', 'employeename': 'name', 'employee address': 'address', 'email_address': 'email'} faker = FakerSchema() data = faker.generate_fake(schema, iterations=4) print(data) # [{'employeeid': 'e07a7964-9636-bca6-2a58-4a69ac126dc5', 'employeename': # 'Charlene Blankenship', 'employee address': '0431 Edward Mountains Suite 697\nPort Douglas, # TX 96239-7277', 'emailaddress': 'ashley86@yahoo.com'}, {'employeeid': # '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/fakerweb>__ as an example.

After installing <https://github.com/thiagofigueiro/fakerweb#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) headersschema = {'Content-Type': 'contenttype', 'Server': 'server_token'} fakeheaders = faker.generatefake(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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