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Status](https://readthedocs.org/projects/dammy/badge/?version=latest)](https://dammy.readthedocs.io/en/latest/?badge=latest)\n![Travis (.org)](https://img.shields.io/travis/ibonn/dammy)\n[![Codacy Badge](https://api.codacy.com/project/badge/Grade/c321b2ee18234712aff9ce2ca69ae6eb)](https://www.codacy.com/manual/ibonn/dammy?utm_source=github.com\u0026amp;utm_medium=referral\u0026amp;utm_content=ibonn/dammy\u0026amp;utm_campaign=Badge_Grade)\n[![Maintainability](https://api.codeclimate.com/v1/badges/141299ec4d7519f889d6/maintainability)](https://codeclimate.com/github/ibonn/dammy/maintainability)\n[![PyPI download month](https://img.shields.io/pypi/dm/dammy.svg)](https://pypi.python.org/pypi/dammy/)\n[![PyPI download week](https://img.shields.io/pypi/dw/dammy.svg)](https://pypi.python.org/pypi/dammy/)\n[![PyPI download day](https://img.shields.io/pypi/dd/dammy.svg)](https://pypi.python.org/pypi/dammy/)\n\nGenerate fake/dummy data for any purpose\n\n## Table of contents\n\n* [Introduction](#introduction)\n* [Features](#features)\n* [Example](#example)\n* [Installation](#installation)\n* [Release history](#release-history)\n\n## Introduction\n\ndammy is a powerful and simple tool to generate fake data. You can use it to mock classes, populate databases and and much more.\nYou can check the full documentation [here](https://dammy.readthedocs.io/en/latest/).\n\n## Features\n* Generate anything within the set of prebuilt objects (Person names, country names, car manufacturers and models, random dates...)\n* Compose more complex data easily (Full profiles, complete databases, )\n* The possibility to expand the previous set with little to no code\n* Completely intuitive, you will learn to use it in less than 10 minutes\n* Export the generated data to SQL\n\n## Example\n\nIf you wanted to generate 1000 random people, just define what a person looks like and dammy will handle the rest\n\n``` python\nfrom dammy import EntityGenerator\nfrom dammy.functions import cast\nfrom dammy.stdlib import RandomName, RandomString, RandomDateTime, RandomInteger, CountryName\n\nclass Person(EntityGenerator):\n    first_name = RandomName().upper()\n    password = RandomString(5)\n    birthday = RandomDateTime(start=datetime(1980, 1, 1), end=datetime(2000, 12, 31), date_format='%d/%m/%Y')\n    favorite_number = RandomInteger(0, 10)\n    age = cast((datetime.now() - birthday).days / 365.25, int)\n    country = CountryName()\n\n# Generate 1000 random people\nfor i in range(0, 1000):\n    print(Person())\n```\n\nWhich will output:\n```\n{'identifier': 1, 'uid': '9XCha', 'first_name': 'ZAYN', 'blood': 'A+', 'birthday': '24/01/1982', 'favorite_number': 5, 'age': 38, 'country': 'Denmark'}\n{'identifier': 2, 'uid': 'bbYbw', 'first_name': 'MALIHA', 'blood': 'AB+', 'birthday': '01/12/1981', 'favorite_number': 1, 'age': 38, 'country': 'Syrian Arab Republic'}\n{'identifier': 3, 'uid': 'aGF49', 'first_name': 'ANGEL', 'blood': 'AB+', 'birthday': '18/08/1992', 'favorite_number': 1, 'age': 27, 'country': 'Macedonia, the Former Yugoslav Republic of'}\n{'identifier': 4, 'uid': 'Lcr0J', 'first_name': 'REUBEN', 'blood': '0-', 'birthday': '07/11/1997', 'favorite_number': 4, 'age': 22, 'country': 'Dominican Republic'}\n{'identifier': 5, 'uid': 'P7mD4', 'first_name': 'MAMADOU', 'blood': 'A+', 'birthday': '02/01/1987', 'favorite_number': 7, 'age': 33, 'country': 'Palau'}\n{'identifier': 6, 'uid': 'ykdeL', 'first_name': 'BATSHEVA', 'blood': 'A+', 'birthday': '11/01/1983', 'favorite_number': 5, 'age': 37, 'country': 'Seychelles'}\n{'identifier': 7, 'uid': 'h9HjQ', 'first_name': 'JIMENA', 'blood': 'A-', 'birthday': '23/10/1985', 'favorite_number': 0, 'age': 34, 'country': 'China'}\n{'identifier': 8, 'uid': 'rjt92', 'first_name': 'YERIK', 'blood': 'AB+', 'birthday': '29/10/1991', 'favorite_number': 5, 'age': 28, 'country': 'Libya'}\n{'identifier': 9, 'uid': 'vL0DE', 'first_name': 'YISRAEL', 'blood': 'AB+', 'birthday': '25/03/1989', 'favorite_number': 8, 'age': 30, 'country': 'Spain'}\n{'identifier': 10, 'uid': 'CsrhX', 'first_name': 'JOSHUA', 'blood': 'AB+', 'birthday': '20/09/1999', 'favorite_number': 1, 'age': 20, 'country': 'Svalbard and Jan Mayen'}\n...\n```\n\nIt also supports relationships between tables, so you can generate data to populate databases\n``` python\nfrom dammy import EntityGenerator\nfrom dammy.db import AutoIncrement, PrimaryKey, ForeignKey\nfrom dammy.stdlib import RandomName, RandomString, RandomDateTime, RandomInteger, CountryName\n\n# Define what a person looks like\nclass Person(EntityGenerator):\n    id_pk = PrimaryKey(id=AutoIncrement())\n    first_name = RandomName().upper()\n    password = RandomString(5)\n    birthday = RandomDateTime(start=datetime(1980, 1, 1), end=datetime(2000, 12, 31), date_format='%d/%m/%Y')\n    favorite_number = RandomInteger(0, 10)\n    age = cast((datetime.now() - birthday).days / 365.25, int)\n    country = CountryName()\n\n# Define what a car looks like\nclass Car(EntityGenerator):\n    id_pk = PrimaryKey(id=AutoIncrement())\n    manufacturer_name = CarBrand()\n    model = CarModel(car_brand=manufacturer_name)\n    owner = ForeignKey(Person, 'identifier')\n```\n\nAnd the data can be exported to SQL\n``` python\nfrom dammy import DatasetGenerator\n\n# Generate a dataset with 20000 cars and 94234 people\ndataset = DatasetGenerator((Car, 20000), (Person, 94234)).generate()\ndataset.get_sql(save_to='cars_with_owners.sql')\n```\n## Installation\nTo install the latest stable release of dammy using pip\n```\npip install dammy\n```\n\nYou can also install the latest development release by cloning the repository and installing it with pip\n```\ngit clone https://github.com/ibonn/dammy.git dammy\ncd dammy\npip install -e .\n```\n\n## Release history\n* 1.2.0-alpha\n    * dammy.seed() added to seed the random number generator\n    * RandomFloat, CreditCard and IPv4Address added to stdlib\n    * Localization support enabled\n    * Deprecated ForeignKey.get_reference() removed\n    * Deprecated DatasetGenerator.get_sql() removed\n    * Minor bugs fixed\n* 1.1.0\n    * Iterators added\n    * ForeignKey.get_reference() deprecated. 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