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Biedma Ramos","email":"info@dbr.io","url":"https://dbr.io"},"license":"MIT","homepage":"https://github.com/danibram/mocker-data-generator#readme","keywords":["mock","data","faker","fakerjs","chance","chancejs","casual","randexp","json","fake","mocks","massive","generator"],"repository":{"type":"git","url":"git+https://github.com/danibram/mocker-data-generator.git"},"description":"A simplified way to generate mock data, builds using a simple schema and with the FakerJs","maintainers":[{"name":"danibram","email":"dbiedma.r@gmail.com"}],"readme":"# mocker-data-generator [![Tweet](https://img.shields.io/twitter/url/http/shields.io.svg?style=social)](https://twitter.com/intent/tweet?text=Im%20testing%20mocker-data-generator%20is%20awesome!&via=danibram&url=http://bit.ly/2ziE8qT&hashtags=mock,javascript,developers)\n\n[![npm version](https://img.shields.io/npm/v/mocker-data-generator.svg?style=flat-square)][npm-home-module][![GitHub license](https://img.shields.io/npm/dt/mocker-data-generator.svg?style=flat-square)][npm-home-module]\n\n[![Linux Build status][travis-badge]][travis-link][![Windows Build status][appveyor-badge]][appveyor-link][![Codecov coverage][codecov-badge]][codecov-link][![Codecov coverage][coveralls-badge]][coveralls-link]\n\n[![GitHub license](https://img.shields.io/github/license/danibram/mocker-data-generator.svg?style=flat-square)][npm-home-module][![Awesome license](https://img.shields.io/badge/bateries-included-orange.svg?style=flat-square)][npm-home-module]\n\n[![Support link][paypal-badge]][paypal-link]\n\nA simplified way to generate massive mock data based on a schema, using the awesome fake/random data generators like ([Faker-JS](https://fakerjs.dev/), ChanceJs, CasualJs and RandExpJs), all in one tool to generate your fake data for testing.\n\nNow the library has been migrated 100% to typescript typing are included.\n\nYou can test online here: [https://danibram.github.io/mocker-data-generator/](https://danibram.github.io/mocker-data-generator/)\n\n## Getting started\n\nInstall the module and the awesome generator you want:\n`npm install mocker-data-generator @faker-js/faker`\n\nImport it. As of v4 the package is a **dual ESM + CommonJS** build with zero\nruntime dependencies, running in modern Node (`>=20`) and in the browser — you\nbring your own generator:\n\n```javascript\n// ESM / TypeScript\nimport mocker from 'mocker-data-generator'\nimport { faker } from '@faker-js/faker'\n\n// CommonJS\nconst mocker = require('mocker-data-generator').default\n```\n\nIn the browser you can also load the pre-bundled, minified ESM build straight\nfrom a CDN, with no bundler required:\n\n```html\n<script type=\"module\">\n    import mocker from 'https://unpkg.com/mocker-data-generator'\n</script>\n```\n\nThen use it:\n\n```javascript\nvar user = {\n    firstName: {\n        faker: 'person.firstName()'\n    },\n    lastName: {\n        faker: 'person.lastName()'\n    },\n    country: {\n        faker: 'location.country()'\n    },\n    createdAt: {\n        faker: 'date.past()'\n    },\n    username: {\n        function: function () {\n            return (\n                this.object.lastName.substring(0, 5) +\n                this.object.firstName.substring(0, 3) +\n                Math.floor(Math.random() * 10)\n            )\n        }\n    }\n}\nvar group = {\n    description: {\n        faker: 'lorem.paragraph()'\n    },\n    users: [\n        {\n            function: function () {\n                return this.generators.faker.helpers.arrayElement(this.db.user)\n                    .username\n            },\n            length: 10,\n            fixedLength: false\n        }\n    ]\n}\nvar conditionalField = {\n    type: {\n        values: ['HOUSE', 'CAR', 'MOTORBIKE']\n    },\n    'object.type==\"HOUSE\",location': {\n        faker: 'location.city()'\n    },\n    'object.type==\"CAR\"||object.type==\"MOTORBIKE\",speed': {\n        faker: 'number.int()'\n    }\n}\n\n// Using traditional callback Style\n\nmocker()\n    .addGenerator('faker', faker)\n    .schema('user', user, 2)\n    .schema('group', group, 2)\n    .schema('conditionalField', conditionalField, 2)\n    .build(function (error, data) {\n        if (error) {\n            throw error\n        }\n        console.log(util.inspect(data, { depth: 10 }))\n\n        // This returns an object\n        // {\n        //      user:[array of users],\n        //      group: [array of groups],\n        //      conditionalField: [array of conditionalFields]\n        // }\n    })\n\n// Using promises\n\nmocker()\n    .addGenerator('faker', faker)\n    .schema('user', user, 2)\n    .schema('group', group, 2)\n    .schema('conditionalField', conditionalField, 2)\n    .build()\n    .then(\n        data => {\n            console.log(util.inspect(data, { depth: 10 }))\n            // This returns an object\n            // {\n            //      user:[array of users],\n            //      group: [array of groups],\n            //      conditionalField: [array of conditionalFields]\n            // }\n        },\n        err => console.error(err)\n    )\n\n// Synchronously\n\n// This returns an object\n// {\n//      user:[array of users],\n//      group: [array of groups],\n//      conditionalField: [array of conditionalFields]\n// }\nvar data = mocker()\n    .addGenerator('faker', faker)\n    .schema('user', user, 2)\n    .schema('group', group, 2)\n    .schema('conditionalField', conditionalField, 2)\n    .buildSync()\n\nconsole.log(util.inspect(data, { depth: 10 }))\n```\nNOTE:\nFor the demo above you will also need to import util i.e.\n`var util = require('util') or import util from 'util'`\n\n## Documentation\n\nData generation goes with model based composed by generators, the generators can have access to the data generated and to the entity generated. **_Generators run synchronously, take care of the related entities!!_**\n\n### Methods\n\n*   **_addGenerator(name, generator, runFn)_**: Add a new generator, now generators are not included in the package, so you have to add whathever generator you want.\n\n    *   name (String): key of the generator this should match with the key in the schema.\n    *   generator (library): Library if the generator\n    *   runFN (function) (Optional) (generator: any, input: any) => any : It compose a exec function for the selected generator, only for custom generators, see randexp in the examples folder\n\n*   **_schema(name, schema, generationType)_**: Add a new schema, you must specify this params:\n\n    *   name (String): Name of the schema.\n    *   schema (JSON): The schema you define\n    *   generationType (integer or JSON): In this field you specify how you will generate this schema. 3 ways:\n        *   Integer to specify how many objects of this schema you want.\n        *   JSON with this object `{max: '<maximunValues>'}` you can also optionally pass min `{max: '<maximunValues>', min: '<minimumValues>'`, this will generate a range of objects of this schema, between (0 and max) or (min and max) randomly.\n        *   JSON with this object `{uniqueField: '<yourUniqueField>'}` this means that this field (<yourUniqueField>) is an array and you want to generate entities with this unique values\n\n*   **_reset()_**: Clean the internal DB.\n*   **_restart()_**: Clean the internal DB and all the schemas inside.\n*   **_build(callback)_**: This methods start to produce the data and wrap it to the callback function, the callback funtion have 2 parameters, error and data generated.\n-   **_buildSync()_**: Synchronous version of `build(callback)`. Returns generated data or throws an error.\n\n### Schema definition\n\n#### Every schema should contains the specified fields. Key can be 2 types:\n\n*   **_Normal string_** key: indicates the key.\n*   **_Commaseparated string_** key: indicates that there is a conditional, before the comma you must specify a conditional (you have all level fields generated in this moment), then you must specify the field if the conditional is true see the example.\n\n#### Inside every value you can put:\n\n*   **_static_**: For fixed fields\n\n    ```javascript\n    {\n        static: 'hello im fixed field'\n    }\n    ```\n\n*   **_self_**: get himself object, and evaluate the string, so you can get calculated fields.\n\n    *   **_eval_** (Optional): Also now you can pass, eval to true, to use like in versions < 2.6.0\n\n\n    ```javascript\n    {\n        self: 'id'\n    }   //will get the id of the generated entity\n\n    {\n        self: 'id',\n        eval: true\n    }   // will get the first user id\n    ```\n\n*   **_db_**: get the db, and evaluate the string, so you can access to this entities.\n\n    *   **_eval_** (Optional): Also now you can pass, fast to true, eval to true, to use like in versions < 2.6.0\n\n\n    ```javascript\n    {\n        db: 'user[0].id'\n    }   // will get the first user id\n\n    {\n        db: 'user[0].id',\n        eval: true\n    }   // will get the first user id\n    ```\n\n*   **_eval_**: evaluate the current string, remember that all context are injected (generators, db the actual object). With this eval field, **_you must pass an exactly JSON syntax_**:\n\n    ```javascript\n    {\n        eval: 'object.id'\n    }\n\n    // OR\n\n    {\n        eval: 'db.user[0]'\n    }\n\n    // OR\n\n    {\n        eval: 'faker.lorem.words()'\n    }\n    ```\n\n*   **_hasOne_**: You can pass 2 parameters:\n\n    *   **_hasOne_**: the name of the related entity, get one random.\n    *   **_get_** (Optional): String that will be evaluated over the random related entity.\n    *   **_eval_** (Optional): Only affects if get is passed, the get param only support dotted paths, with eval=true you can use an eval string, this impacts on the performance\n\n        ```javascript\n            {\n                hasOne: 'user'\n            }   // this populate the field with one random user\n\n            // OR:\n\n            {\n                hasOne: 'user',\n                get: 'id'\n            }   // this populate the field with one id of a random user\n\n\n            // OR:\n\n            {\n                hasOne: 'user',\n                get: 'id',\n                eval: true\n            }   // this populate the field with one id of a random user with eval string\n        ```\n\n*   **_hasMany_**: You can pass 4 parameters:\n\n    *   **_hasMany_**: the name of the related entity, get one random.\n    *   **_amount_** (Optional): Fixed number of related entities to get.\n    *   **_min_** (Optional): Minimum entities to get, buy default is 1, if you want the chance to have empty arrays please specify min to 0.\n    *   **_max_** (Optional): Maximum entities to get.\n    *   **_get_** (Optional): String that will be evaluated over the random related entity.\n    *   **_eval_** (Optional): Get will only support dotted paths, with eval= true you can get from an evaluable string\n    *   **_unique_** (Optional): hasMany will get unique values from the entity (Make sure that you have many unique data in the source)\n\n        ```javascript\n            // In this case we will get 1 user (hasMany)\n            {\n                hasMany: 'user'\n            }   // this populate the field with one random user\n\n            // OR:\n\n\n            {\n                hasMany: 'user',\n                amount: 1, //optional\n            }   // In this case we will get 1 (amount) user (hasMany)\n\n            // OR:\n\n            {\n                hasMany: 'user',\n                max: 3 // optional\n            }   // In this case we will get as max 3 (max) users (hasMany)\n\n            // OR:\n\n\n            {\n                hasMany: 'user',\n                min: 1 //optional\n                max: 3 //optional\n            }   // In this case we will get bettween min 1 (min) and max 3 (max) users (hasMany)\n\n            // OR:\n\n            {\n                hasMany: 'user',\n                get: 'id'\n            }   // In this case we will get the id (get) from 1 random user (hasMany)\n        ```\n\n*   **_incrementalId_**: For incremental numeric ids, pass the start number to increment. If you put incrementalId = true it takes from 0 the ids.\n\n    ```javascript\n    {\n        incrementalId: 0\n    }\n    ```\n\n*   **_function_**: No params are passed, only context (`this`), in this you have `{db, object, faker, chance}`, and you can use faker or chance functions, object (the specified model), db (actual data generated)\n\n    ```javascript\n          { function: function(){\n\n              // this.db\n              // this.object\n              // this.generators\n\n              return yourValue\n          } }\n\n          // OR:\n\n          { function(){\n\n              // this.db\n              // this.object\n              // this.generators\n\n              return yourValue\n          } }\n    ```\n\n*   **_[Array]_**: you can pass an array that indicates an array of data you can create, passing in the first field the generator (function, faker, or array(not Tested)), and in the second field pass a config object (length, fixedLentgh)\n\n    *   **_length_**: to know how many values\n    *   **_fixedLength_** (Optional): true to create always same amount of values in the array, false to generate a random number between 0 and 'length' value. False by default.\n    *   **_concat_** (Optional): An stringuified array ex: '[object.id, db.users.id]'. This should be an evaluable string to concat with the array that are generating. Also takes in mind that if you have a fixedLength, should not increase the length.\n    *   **_strictConcat_** (Optional): true to remove duplicates in the concatenated string array, when it is calculated. False by default.\n\n        ```javascript\n        [{\n           // Any generator\n               // Faker\n           [name of the generator injected]: 'path inside the generator'\n               // If faker is injected with .addGenerator('faker', faker) then you can use:\n           faker: 'helpers.arrayElement(db.users).userId'\n               // Function that has included index, length and self that refers at the actual array generation\n           function: function (index, length, self){ return /**/ }\n\n           // Array config\n           length: 10,\n           fixedLength: true\n\n           // Concat\n           concat: '[db.users[0].userId, db.users[1].userId]'\n           strictConcat: true\n        }]\n        ```\n\n### Custom generators\n\nIt happens!Mocker now is independant of the generators so I hope this will give you more freedom. This is an example that you can check on the examples folder, where 2 generators are used:\n\n```javascript\n    var mocker = require('../build/main').default\n    var { faker } = require('@faker-js/faker')\n    var Randexp = require('randexp')\n    var util = require('util')\n\n    var user = {\n        firstName: {\n            faker: 'person.firstName()'\n        },\n        notes: {\n            randexp: /hello+ (world|to you)/\n        }\n    }\n\n    mocker()\n        .addGenerator('faker', faker)\n        .addGenerator('randexp', Randexp, function (generator, input) {\n            return new generator(input).gen()\n        })\n        .schema('user', user, 2)\n        .build(function (error, data) {\n            if (error) {\n                throw error\n            }\n            console.log(util.inspect(data, { depth: 10 }))\n        })\n```\n\n### Optional fields\n\n*   **_[virtual]_**: Boolean, if you pass this option, this mean that this field will not appear at the output entity. But you can use during the generation.\n\n```javascript\n    {\n        // Any generator\n            // Faker\n        [name of the generator injected]: 'path inside the generator'\n            // If faker is injected with .addGenerator('faker', faker) then you can use:\n        faker: 'helpers.arrayElement(db.users).userId'\n            // Static\n        static: 'any static field'\n            // Function\n        function: function (){ return /**/ }\n\n        // With the virtual option\n        virtual: true\n\n    }\n```\n\n### Data generation\n\nInitialize mocker with the config, and then generate any entity with promises style, use generate function that accepts the name of the model and the amount of data to generate. Like the example:\n\n```javascript\nmocker()\n    .addGenerator('faker', faker)\n    .schema('user', user, 2)\n    .schema('group', group, 2)\n    .schema('conditionalField', conditionalField, 2)\n    .build(function(err, data) {\n        console.log(util.inspect(data, { depth: 10 }))\n        // This returns an object\n        // {\n        //      user:[array of users],\n        //      group: [array of groups],\n        //      conditionalField: [array of conditionalFields]\n        // }\n    })\n```\n\nYou can also pass instead of the number, an object with the a config, from now `{uniqueField}`. If this field exists tells to the generator that instead of init a fixed length of data, generate an amount of data depending of the values of the field you will specify. You have 2 way to deal with this, check the examples See the output of this example:\n\n```javascript\n//\n// First way, using an 'values' embedded object\n//\n\nvar cat = {\n    name: {\n        values: ['txuri', 'pitxi', 'kitty']\n    }\n}\nvar m = mocker()\n    .addGenerator('faker', faker)\n    .schema('cat', cat, 10)\n    .schema('cat2', cat, { uniqueField: 'name' })\n    .build(function(err, data) {\n        console.log(util.inspect(data, { depth: 10 }))\n    })\n\n//\n// Second way, without 'values' embedded.\n//\n\nvar cat = {\n    name: ['txuri', 'pitxi', 'kitty']\n}\nvar m = mocker()\n    .addGenerator('faker', faker)\n    .schema('cat', cat, 10)\n    .schema('cat2', cat, { uniqueField: 'name' })\n    .build(function(err, data) {\n        console.log(util.inspect(data, { depth: 10 }))\n    })\n```\n\n### _eval_ Option (Beta):\n\nIn version >= 2.6.0, eval option was introduced to run mocker-data-generator like olders versions, so by default is running without eval: `faker`, `chance`, `casual`, `hasMany`, `hasOne`, `db` and `self`. This means that this methods loose habilities, when eval is not passed, but this are the speed results with eval active (old way) and without (new way)\n\n```\nfaker eval old:  0.969ms\nfaker now:       0.215ms\nchance eval old: 0.559ms\nchance now:      0.099ms\ncasual eval old: 0.360ms\ncasual now:      0.026ms\n```\n\n### More, Coming soon\n\n## Online API\n\nYou can visit the repo url here: [https://github.com/danibram/mocker-api-tester](https://github.com/danibram/mocker-api-tester)\n\nOr visit the api directly: [https://mocker-api.herokuapp.com/](https://mocker-api.herokuapp.com/)\n\n## Development\n\nRun `npm install;npm run dev` to watch the project, webpack compile the code automatically. Run `npm build` to build the normal and minified version.\n\n## Why not use json-schema-faker?\n\njson-schema-faker is awesome and works really nice, but i need a simplified and fast way to generate mock data for my projects, so i created this.\n\n## Credits\n\nI couldn't do this without this awesome libraries, so thanks to all:\n\n*   Faker: [[https://github.com/faker-js/faker](https://github.com/faker-js/faker)]\n*   Chance: [[https://github.com/victorquinn/chancejs](https://github.com/victorquinn/chancejs)]\n*   Casual: [[https://github.com/boo1ean/casual](https://github.com/boo1ean/casual)]\n*   RandExpJs: [[https://github.com/fent/randexp.js](https://github.com/fent/randexp.js)]\n*   typescript-starter: [[https://github.com/bitjson/typescript-starter](https://github.com/bitjson/typescript-starter)]\n\n## License\n\nLicensed under the MIT license. 2022\n\n[paypal-badge]: https://img.shields.io/badge/❤%20support-paypal-blue.svg?style=flat-square\n[paypal-link]: https://www.paypal.me/danibram\n[https://github.com/faker-js/faker]: https://github.com/faker-js/faker\n[https://github.com/victorquinn/chancejs]: https://github.com/victorquinn/chancejs\n[https://github.com/boo1ean/casual]: https://github.com/boo1ean/casual\n[https://github.com/fent/randexp.js]: https://github.com/fent/randexp.js\n[coveralls-link]: https://coveralls.io/github/danibram/mocker-data-generator\n[coveralls-badge]: https://img.shields.io/coveralls/danibram/mocker-data-generator.svg?style=flat-square&label=coveralls%20coverage\n[codecov-badge]: https://img.shields.io/codecov/c/github/danibram/mocker-data-generator.svg?style=flat-square&label=codecov%20coverage\n[codecov-link]: https://codecov.io/github/danibram/mocker-data-generator\n[npm-home-module]: https://www.npmjs.com/package/mocker-data-generator\n[appveyor-badge]: https://img.shields.io/appveyor/ci/danibram/mocker-data-generator.svg?style=flat-square&label=windows\n[appveyor-link]: https://ci.appveyor.com/project/danibram/mocker-data-generator\n[travis-link]: https://travis-ci.org/danibram/mocker-data-generator\n[travis-badge]: https://img.shields.io/travis/danibram/mocker-data-generator.svg?style=flat-square&label=linux\n","readmeFilename":"README.md","users":{"danibram":true,"stephanlv":true,"aitorllj93":true,"electblake":true,"mcalavera81":true}}