# Fake Random User Generator (`moving_beacon-owner1/fake-random-user-generator`) Actor Generates realistic fake user profiles using the RandomUser.me API. Perfect for populating test databases, prototyping UIs, load testing, and demo data. No API key required. - **URL**: https://apify.com/moving\_beacon-owner1/fake-random-user-generator.md - **Developed by:** [Jamshaid Arif](https://apify.com/moving_beacon-owner1) (community) - **Categories:** Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 🎭 Fake Random User Generator — Apify Actor Generates **realistic fake user profiles** using the [RandomUser.me](https://randomuser.me/) API. Perfect for populating test databases, prototyping UIs, load testing, and demo data. No API key required. ### Features - **Bulk generation** — up to 5,000 users per run. - **21 nationalities** — AU, BR, CA, CH, DE, DK, ES, FI, FR, GB, IE, IN, IR, MX, NL, NO, NZ, RS, TR, UA, US. - **Gender filter** — male only, female only, or mixed. - **Age range** — filter by minimum/maximum age (smart over-fetching to hit the target count). - **Password rules** — control character sets (upper, lower, number, special) and length range. - **Field selection** — include or exclude specific data categories. - **Reproducible seeds** — same seed = identical users every run. - **3 output formats** — flat (spreadsheet-ready), nested (JSON-native), minimal (essentials only). - **Sequential IDs** — optional auto-incrementing ID on each record. ### Input Example ```json { "userCount": 500, "gender": "both", "nationalities": ["US", "GB", "DE", "FR"], "minAge": 25, "maxAge": 45, "passwordCharsets": ["upper", "lower", "number", "special"], "passwordMinLength": 12, "passwordMaxLength": 20, "outputFormat": "flat", "seed": "my-test-seed", "addSequentialId": true } ```` ### Output Fields #### Flat Format (default) | Field | Example | |---|---| | `id` | `1` | | `gender` | `female` | | `title` | `Ms` | | `first_name` | `Sarah` | | `last_name` | `Johnson` | | `full_name` | `Ms Sarah Johnson` | | `email` | `sarah.johnson@example.com` | | `phone` | `(555) 123-4567` | | `cell` | `(555) 987-6543` | | `nationality` | `US` | | `street_number` | `4280` | | `street_name` | `Maple Ave` | | `city` | `Portland` | | `state` | `Oregon` | | `country` | `United States` | | `postcode` | `97201` | | `latitude` | `45.5231` | | `longitude` | `-122.6765` | | `timezone_offset` | `-8:00` | | `timezone_description` | `Pacific Time` | | `username` | `goldenfish842` | | `password` | `xK9#mPq2vL` | | `password_md5` | `a1b2c3d4…` | | `password_sha1` | `e5f6a7b8…` | | `password_sha256` | `c9d0e1f2…` | | `uuid` | `7c8d9e0f-…` | | `date_of_birth` | `1988-03-15T12:00:00.000Z` | | `age` | `37` | | `registered_date` | `2015-06-20T08:30:00.000Z` | | `registered_age` | `10` | | `id_name` | `SSN` | | `id_value` | `123-45-6789` | | `picture_large` | `https://randomuser.me/api/portraits/women/42.jpg` | | `picture_medium` | `https://…/med/women/42.jpg` | | `picture_thumbnail` | `https://…/thumb/women/42.jpg` | #### Minimal Format Only: `full_name`, `email`, `phone`, `cell`, `gender`, `age`, `city`, `state`, `country`, `postcode`, `username`, `nationality`. #### Nested Format Original RandomUser.me JSON structure with `name{}`, `location{}`, `login{}`, `dob{}`, `registered{}`, `id{}`, `picture{}` sub-objects. ### Use Cases - **QA / Testing** — populate a staging database with thousands of realistic profiles. - **UI Prototyping** — fill dashboards, user lists, and admin panels with demo data. - **Load Testing** — generate large datasets for performance benchmarking. - **Workshops & Tutorials** — demo data for teaching data analysis or web development. - **Privacy-Safe Demos** — present realistic-looking data without any real PII. # Actor input Schema ## `userCount` (type: `integer`): How many fake user profiles to generate (1–5000). ## `gender` (type: `string`): Generate only male, only female, or mixed profiles. ## `nationalities` (type: `array`): Select one or more nationalities. Leave empty for all. ## `includeFields` (type: `array`): Only include these fields in the output. Leave empty to include all. ## `excludeFields` (type: `array`): Remove these fields from output. Ignored if 'Include Fields' is set. ## `minAge` (type: `integer`): Only generate users older than this age. Leave empty for no minimum. ## `maxAge` (type: `integer`): Only generate users younger than this age. Leave empty for no maximum. ## `passwordCharsets` (type: `array`): Which character types to use in generated passwords. ## `passwordMinLength` (type: `integer`): Minimum length of generated passwords. ## `passwordMaxLength` (type: `integer`): Maximum length of generated passwords. ## `outputFormat` (type: `string`): How to structure each user record in the dataset. ## `seed` (type: `string`): Set a seed string to get reproducible results. Same seed = same users every run. ## `addSequentialId` (type: `boolean`): Add a sequential numeric ID (1, 2, 3…) to each user record. ## Actor input object example ```json { "userCount": 100, "gender": "both", "nationalities": [], "includeFields": [], "excludeFields": [], "passwordCharsets": [ "upper", "lower", "number" ], "passwordMinLength": 8, "passwordMaxLength": 16, "outputFormat": "flat", "addSequentialId": true } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("moving_beacon-owner1/fake-random-user-generator").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("moving_beacon-owner1/fake-random-user-generator").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call moving_beacon-owner1/fake-random-user-generator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=moving_beacon-owner1/fake-random-user-generator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fake Random User Generator", "description": "Generates realistic fake user profiles using the RandomUser.me API. Perfect for populating test databases, prototyping UIs, load testing, and demo data. No API key required.", "version": "0.0", "x-build-id": "wbCRBJTmFULSA7Ckd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/moving_beacon-owner1~fake-random-user-generator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-moving_beacon-owner1-fake-random-user-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/moving_beacon-owner1~fake-random-user-generator/runs": { "post": { "operationId": "runs-sync-moving_beacon-owner1-fake-random-user-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/moving_beacon-owner1~fake-random-user-generator/run-sync": { "post": { "operationId": "run-sync-moving_beacon-owner1-fake-random-user-generator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "userCount" ], "properties": { "userCount": { "title": "Number of Users", "minimum": 1, "maximum": 5000, "type": "integer", "description": "How many fake user profiles to generate (1–5000).", "default": 100 }, "gender": { "title": "Gender", "enum": [ "both", "male", "female" ], "type": "string", "description": "Generate only male, only female, or mixed profiles.", "default": "both" }, "nationalities": { "title": "Nationalities", "type": "array", "description": "Select one or more nationalities. Leave empty for all.", "items": { "type": "string", "enum": [ "AU", "BR", "CA", "CH", "DE", "DK", "ES", "FI", "FR", "GB", "IE", "IN", "IR", "MX", "NL", "NO", "NZ", "RS", "TR", "UA", "US" ], "enumTitles": [ "Australia", "Brazil", "Canada", "Switzerland", "Germany", "Denmark", "Spain", "Finland", "France", "United Kingdom", "Ireland", "India", "Iran", "Mexico", "Netherlands", "Norway", "New Zealand", "Serbia", "Turkey", "Ukraine", "United States" ] }, "default": [] }, "includeFields": { "title": "Include Fields", "type": "array", "description": "Only include these fields in the output. Leave empty to include all.", "items": { "type": "string", "enum": [ "gender", "name", "location", "email", "login", "dob", "registered", "phone", "cell", "id", "picture", "nat" ], "enumTitles": [ "Gender", "Name", "Location/Address", "Email", "Login/Username", "Date of Birth", "Registration Date", "Phone", "Cell/Mobile", "National ID", "Profile Picture URLs", "Nationality" ] }, "default": [] }, "excludeFields": { "title": "Exclude Fields", "type": "array", "description": "Remove these fields from output. Ignored if 'Include Fields' is set.", "items": { "type": "string", "enum": [ "gender", "name", "location", "email", "login", "dob", "registered", "phone", "cell", "id", "picture", "nat" ], "enumTitles": [ "Gender", "Name", "Location/Address", "Email", "Login/Username", "Date of Birth", "Registration Date", "Phone", "Cell/Mobile", "National ID", "Profile Picture URLs", "Nationality" ] }, "default": [] }, "minAge": { "title": "Minimum Age", "minimum": 0, "maximum": 120, "type": "integer", "description": "Only generate users older than this age. Leave empty for no minimum." }, "maxAge": { "title": "Maximum Age", "minimum": 0, "maximum": 120, "type": "integer", "description": "Only generate users younger than this age. Leave empty for no maximum." }, "passwordCharsets": { "title": "Password Character Sets", "type": "array", "description": "Which character types to use in generated passwords.", "items": { "type": "string", "enum": [ "upper", "lower", "number", "special" ], "enumTitles": [ "Uppercase (A-Z)", "Lowercase (a-z)", "Numbers (0-9)", "Special (!@#$…)" ] }, "default": [ "upper", "lower", "number" ] }, "passwordMinLength": { "title": "Password Min Length", "minimum": 1, "maximum": 64, "type": "integer", "description": "Minimum length of generated passwords.", "default": 8 }, "passwordMaxLength": { "title": "Password Max Length", "minimum": 1, "maximum": 64, "type": "integer", "description": "Maximum length of generated passwords.", "default": 16 }, "outputFormat": { "title": "Output Format", "enum": [ "flat", "nested", "minimal" ], "type": "string", "description": "How to structure each user record in the dataset.", "default": "flat" }, "seed": { "title": "Seed (optional)", "type": "string", "description": "Set a seed string to get reproducible results. Same seed = same users every run." }, "addSequentialId": { "title": "Add Sequential ID", "type": "boolean", "description": "Add a sequential numeric ID (1, 2, 3…) to each user record.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```