Quick Answer: Modern developers have a rich ecosystem of dummy data tools — from classic Lorem Ipsum text generators and Lorem Picsum image placeholders to powerful libraries like @faker-js/faker and Falso, plus self-hosted Docker mock API servers like Mockoon, Smocker, and JSON Server.
Let’s be honest — every developer has been there. You’re building a shiny new UI, your components are looking gorgeous, but your app is staring back at you with… nothing. Empty cards, blank profiles, sad little boxes where content should be. You need data, and you need it now.
Whether you need placeholder text, random images, realistic fake user profiles, or a full-blown mock API server running in Docker, the ecosystem in 2026 has you covered. Let’s walk through every category of dummy data tooling, from the classics to the cutting edge.
TL;DR — What Should You Use?
Need | Best Pick | Runner-Up |
|---|---|---|
Placeholder text | ||
Placeholder images (photos) | ||
Fake data (JS/TS) | ||
Fake data (lightweight) | ||
Mock API (Docker) | ||
Quick REST from JSON | ||
Bulk synthetic data |
Lorem Ipsum: The OG Placeholder Text
Lorem Ipsum has been the go-to placeholder text since the 1500s (yeah, seriously — a typesetter scrambled a passage from Cicero and the rest is history). In 2026, it’s still everywhere, but the tooling around it has gotten way more sophisticated.
Classic Online Generators
If you just need to grab some filler text and paste it into your mockup, these are your best bets:
- Lipsum.com — The original. No frills, just paragraphs of classic Lorem Ipsum. It’s been around forever and it just works.
- LoremIpsum.io — A cleaner, modern interface with a built-in generator plus plugins for writing, design, and blogging tools.
- Blind Text Generator — Goes beyond just Lorem Ipsum. Offers multiple placeholder text styles including Kafka, Pangram, and other fun alternatives.
- Website Planet Generator — Free, one-click text creator built specifically for web designers and content marketers.
AI-Enhanced Text Generation
Here’s where it gets interesting in 2026. Originality.ai offers an AI-powered text generation tool that generates topic-aware, multilingual text in various writing styles and formats. Unlike traditional Lorem Ipsum, it can produce text that actually looks like real content for your specific niche — way more useful for client presentations or realistic prototyping.
Developer-Friendly Approaches
For devs who want Lorem Ipsum inside their code, there are npm packages that make it dead simple:
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npm install lorem-ipsum |
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import { loremIpsum } from 'lorem-ipsum'; // Generate 3 paragraphs const text = loremIpsum({ count: 3, format: 'html', units: 'paragraphs' }); console.log(text); |
WordPress developers also have access to the Lorem Ipsum Generator plugin, which adds a button right into the WYSIWYG editor toolbar plus shortcodes for adding configurable placeholder text.
Lorem Picsum and Placeholder Image Services
Quick Answer: Lorem Picsum serves real Unsplash photos as placeholders via a dead-simple URL API, while Placehold.co generates customizable colored boxes — both are free, no API key needed.
Empty image containers are the bane of every frontend developer’s existence. Thankfully, the placeholder image ecosystem is thriving in 2026.
Lorem Picsum — The King of Placeholder Photos
Lorem Picsum is hands-down the most popular placeholder image service. It serves real photographs sourced from Unsplash, which means your mockups look genuinely good instead of screaming “THIS IS A PLACEHOLDER.”
No API key required. Just construct a URL:
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<!-- Random image, 400x300 --> <img src="https://picsum.photos/400/300" alt="placeholder"> <!-- Square image, 200x200 --> <img src="https://picsum.photos/200" alt="placeholder"> <!-- Specific image by ID --> <img src="https://picsum.photos/id/237/400/300" alt="placeholder"> <!-- Seeded (consistent) random image --> <img src="https://picsum.photos/seed/myproject/400/300" alt="placeholder"> <!-- Grayscale filter --> <img src="https://picsum.photos/400/300?grayscale" alt="placeholder"> <!-- Blur effect (1-10) --> <img src="https://picsum.photos/400/300?blur=2" alt="placeholder"> <!-- WebP format --> <img src="https://picsum.photos/400/300.webp" alt="placeholder"> |
The /seed/ parameter is a game-changer — it ensures you get the same image every time the page loads, so your layouts stay consistent during development while still looking random.
Need to browse what’s available? The /v2/list endpoint returns image metadata (30 items per page by default), and you can paginate with ?page= and ?limit= parameters. Get info on a specific image with /id/{id}/info.
Placehold.co — Custom Text Placeholders
Placehold.co takes a different approach. Instead of real photos, it generates clean colored boxes with optional text — perfect when you need to clearly communicate dimensions or indicate where specific content types will go.
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<!-- Basic placeholder --> <img src="https://placehold.co/600x400" alt="600x400"> <!-- Custom colors (background/text) --> <img src="https://placehold.co/600x400/1a1a2e/e94560" alt="dark themed"> <!-- Custom text --> <img src="https://placehold.co/600x400?text=Hero+Banner" alt="hero banner"> <!-- Custom font --> <img src="https://placehold.co/600x400?font=roboto" alt="roboto font"> <!-- PNG format (default is SVG) --> <img src="https://placehold.co/600x400.png" alt="png placeholder"> <!-- WebP format --> <img src="https://placehold.co/600x400.webp" alt="webp placeholder"> |
Supported formats: SVG (default), PNG, JPEG, GIF, WebP, and AVIF. The minimum image size is 10×10 pixels.
Other Notable Placeholder Image Services
Service | Type | Best For |
|---|---|---|
Creative Commons photos | Category-specific images (animals, food, etc.) | |
Kitten photos | Making your team smile during code review | |
Text-based boxes | Ad dimensions, screen ratios, custom aspect ratios | |
50+ styles, gradients | Branded-looking placeholders with patterns |
Heads up: LoremFlickr had a rocky 2024 when Flickr started enforcing strict API limits and blocked the service entirely. In late 2025, restrictions were lifted again, but keep an eye on it — it could happen again. For mission-critical prototyping, stick with Lorem Picsum or Placehold.co.
Going Offline: Client-Side Placeholders
For offline development or privacy-sensitive projects, you can generate placeholders client-side with Canvas or SVG:
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function createPlaceholder(width, height, text) { const canvas = document.createElement('canvas'); canvas.width = width; canvas.height = height; const ctx = canvas.getContext('2d'); // Background ctx.fillStyle = '#e2e8f0'; ctx.fillRect(0, 0, width, height); // Text ctx.fillStyle = '#64748b'; ctx.font = '16px sans-serif'; ctx.textAlign = 'center'; ctx.textBaseline = 'middle'; ctx.fillText(text || `${width}x${height}`, width / 2, height / 2); return canvas.toDataURL(); } |
Faker.js and Fake Data Generation Libraries
Quick Answer: @faker-js/faker v10 is the community-maintained powerhouse for generating realistic fake data — names, emails, addresses, and more across 70+ locales. Falso and Chance.js offer lighter alternatives.
If you’ve been around long enough, you remember the Faker.js drama of early 2022 when the original maintainer Marak Squires intentionally sabotaged the library. The good news? The community rallied, forked it, and @faker-js/faker is now healthier than ever.
@faker-js/faker — The Full Package
As of 2026, @faker-js/faker is at version 10.3.0 and it’s an absolute unit. Over 70 locales, hundreds of data generators, and a clean API that makes generating realistic data a breeze.
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npm install @faker-js/faker |
Note: Faker v10 requires Node.js 20 or above.
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import { faker } from '@faker-js/faker'; // Generate a realistic user profile const user = { id: faker.string.uuid(), name: faker.person.fullName(), email: faker.internet.email(), avatar: faker.image.avatar(), address: { street: faker.location.streetAddress(), city: faker.location.city(), state: faker.location.state(), zip: faker.location.zipCode(), country: faker.location.country() }, phone: faker.phone.number(), company: faker.company.name(), jobTitle: faker.person.jobTitle(), bio: faker.lorem.paragraph(), registeredAt: faker.date.past() }; console.log(user); // Generate an array of users const users = faker.helpers.multiple(() => ({ name: faker.person.fullName(), email: faker.internet.email(), role: faker.helpers.arrayElement(['admin', 'editor', 'viewer']) }), { count: 50 }); // Locale support -- generate German data import { fakerDE } from '@faker-js/faker'; console.log(fakerDE.person.fullName()); // "Max Mustermann" console.log(fakerDE.location.city()); // "Berlin" |
The breadth of data types is impressive: locations, finance (credit cards, IBAN, Bitcoin addresses), commerce (products, prices), dates, images, lorem text, colors, databases, git commits, vehicles, music, science… you name it.
Falso — The Tree-Shakable Alternative
Falso (from the ngneat team) was born during the original Faker.js meltdown, and it’s carved out a solid niche. With 205 generator functions, full TypeScript support, and — crucially — tree-shakable imports, it’s a fantastic choice when bundle size matters.
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npm install @ngneat/falso |
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// Import only what you need -- tree-shakable! import { randFullName, randEmail, randPost, randTodo } from '@ngneat/falso'; // Single values console.log(randFullName()); // "John Smith" console.log(randEmail()); // "john.smith@example.com" // Generate arrays const names = randFullName({ length: 10 }); // Entity generators -- full objects out of the box const post = randPost(); // { id: '...', title: '...', body: '...', category: '...', ... } const todos = randTodo({ length: 5 }); // [{ id: '...', title: '...', completed: true }, ...] |
The flat import structure (randFullName vs faker.person.fullName()) means your bundler can eliminate unused generators, which can make a real difference in frontend apps.
Chance.js — Lightweight and Flexible
Chance.js has been around for ages and focuses on being minimal and flexible. It’s great when you don’t need the full kitchen sink of Faker but want more than Math.random().
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npm install chance |
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import Chance from 'chance'; const chance = new Chance(); // Basic generators chance.name(); // "Emily Davis" chance.email(); // "emily@example.com" chance.age(); // 34 (between 0 and 120) chance.country(); // "US" chance.sentence(); // "Wic namnas vu..." // With options chance.name({ gender: 'female' }); chance.integer({ min: 1, max: 100 }); chance.floating({ min: 0, max: 100, fixed: 2 }); // Utility helpers chance.pickone(['red', 'green', 'blue']); chance.shuffle([1, 2, 3, 4, 5]); |
Smock-It — When You Need Serious Volume
If you need to generate massive datasets, Smock-It is purpose-built for bulk data generation, scaling up to 300,000 unique records. It comes with a built-in data library that generates not just random but truly unique records — no duplicates.
Comparison: Fake Data Libraries
Library | Bundle Size | TypeScript | Tree-Shakable | Locales | Best For |
|---|---|---|---|---|---|
Large | Yes | Partial | 70+ | Full-featured data generation | |
Small (tree-shake) | Yes | Yes | Limited | Frontend apps, bundle-conscious | |
Small | Community types | No | Limited | Lightweight, flexible random data | |
Tiny | Yes | Yes (ESM) | No | Minimal footprint projects | |
Medium | Yes | No | No | Bulk data (up to 300k records) |
Docker-Based Mock API Servers
Quick Answer: Mockoon, Smocker, JSON Server, and Imposter all offer Docker images for self-hosted mock API servers — perfect for CI/CD pipelines, team development, and offline testing.
Sometimes placeholder text and fake data libraries aren’t enough. You need an actual API endpoint that responds with realistic data. Here’s where Docker-based mock servers shine — spin them up in seconds, share them with your team, and tear them down when you’re done.
JSON Server — Fake REST API in 30 Seconds
JSON Server is probably the fastest way to go from “I need a REST API” to “I have a REST API.” Create a JSON file, point JSON Server at it, and boom — you’ve got full CRUD endpoints with pagination, filtering, and sorting.
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// db.json { "users": [ { "id": 1, "name": "Alice Johnson", "email": "alice@example.com", "role": "admin" }, { "id": 2, "name": "Bob Smith", "email": "bob@example.com", "role": "editor" }, { "id": 3, "name": "Carol Davis", "email": "carol@example.com", "role": "viewer" } ], "posts": [ { "id": 1, "title": "Getting Started", "body": "Welcome to our blog...", "userId": 1 }, { "id": 2, "title": "Advanced Tips", "body": "Let's dive deeper...", "userId": 2 } ], "comments": [ { "id": 1, "body": "Great post!", "postId": 1 } ] } |
Docker Compose setup:
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version: '3.8' services: json-server: image: williamyeh/json-server container_name: mock-api ports: - "3000:3000" volumes: - ./db.json:/data/db.json command: --watch /data/db.json --host 0.0.0.0 restart: unless-stopped |
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docker compose up -d # Now you've got endpoints: # GET /users # GET /users/1 # POST /users # PUT /users/1 # PATCH /users/1 # DELETE /users/1 # GET /users?role=admin (filtering) # GET /posts?_page=1&_limit=10 (pagination) # GET /posts?_sort=title (sorting) |
Power move: Combine JSON Server with Faker.js to auto-generate your db.json:
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// generate-db.js import { faker } from '@faker-js/faker'; import { writeFileSync } from 'fs'; const users = faker.helpers.multiple(() => ({ id: faker.string.uuid(), name: faker.person.fullName(), email: faker.internet.email(), avatar: faker.image.avatar(), role: faker.helpers.arrayElement(['admin', 'editor', 'viewer']), createdAt: faker.date.past().toISOString() }), { count: 100 }); const posts = faker.helpers.multiple(() => ({ id: faker.string.uuid(), title: faker.lorem.sentence(), body: faker.lorem.paragraphs(3), userId: faker.helpers.arrayElement(users).id, tags: faker.helpers.multiple(() => faker.lorem.word(), { count: 3 }), publishedAt: faker.date.recent().toISOString() }), { count: 200 }); writeFileSync('db.json', JSON.stringify({ users, posts }, null, 2)); console.log('Generated 100 users and 200 posts!'); |
There’s even a dedicated Docker image — docker-json-server-faker — that bundles JSON Server with Faker and Lodash, so you can programmatically generate data using JavaScript files right inside the container.
Mockoon — The Developer-Friendly Mock Server
Mockoon is a step up from JSON Server. It gives you a beautiful desktop GUI for designing your mock APIs, plus a CLI and Docker image for deploying them anywhere. Design locally, deploy as a container — pretty slick workflow.
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# Quick start with Docker docker run -d \ --name mockoon \ -p 3000:3000 \ --mount type=bind,source=./mockoon-data.json,target=/data,readonly \ mockoon/cli:latest \ -d data -p 3000 |
Docker Compose with Mockoon:
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version: '3.8' services: mockoon: image: mockoon/cli:latest container_name: mockoon-api ports: - "3000:3000" - "3001:3001" volumes: - ./mock-apis:/data:ro command: --data /data/my-api.json --port 3000 restart: unless-stopped environment: - API_VERSION=v2 |
The real killer feature? Mockoon can generate a self-contained Dockerfile from your mock configuration:
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# Generate a Dockerfile from your mock config npx mockoon-cli dockerize --data ./my-api.json --output ./Dockerfile # Build and run -- no additional params needed docker build -t my-mock-api . docker run -d -p 3000:3000 my-mock-api |
Environment variables, request logging, response rules based on query params or request body, CORS support, latency simulation — Mockoon has it all. Plus, you can pass environment variables using the --env-var flag in your Docker CMD.
Smocker — Lightweight and Go-Powered
Smocker takes a different approach. It’s a lightweight HTTP mock server and proxy written in Go, with a slick React-based UI for managing your mocks. Two ports: 8080 for the mock server, 8081 for the admin UI.
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version: '3.8' services: smocker: image: ghcr.io/smocker-dev/smocker container_name: smocker ports: - "8080:8080" # Mock server - "8081:8081" # Admin UI restart: unless-stopped |
Mocks are defined in YAML or JSON and can be registered through the API or the UI:
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# Register a mock via YAML - request: method: GET path: /api/users response: status: 200 headers: Content-Type: application/json body: > [ {"id": 1, "name": "Alice", "email": "alice@example.com"}, {"id": 2, "name": "Bob", "email": "bob@example.com"} ] - request: method: GET path: /api/users/1 response: status: 200 headers: Content-Type: application/json body: > {"id": 1, "name": "Alice", "email": "alice@example.com"} |
Smocker supports three mock types: Static (fixed responses), Dynamic (using Go templates), and Lua-scripted responses for maximum flexibility. The fact that it’s a single Go binary means it starts up almost instantly.
Imposter — OpenAPI-First Mocking
Imposter is perfect if you’re already working with OpenAPI/Swagger specs. Feed it your spec file, and it automatically creates mock endpoints that serve the example responses defined in your specification.
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version: '3.8' services: imposter: image: outofcoffee/imposter-openapi container_name: imposter-mock ports: - "8080:8080" volumes: - ./config:/opt/imposter/config restart: unless-stopped |
Key features that set it apart:
- Reads OpenAPI v2 (Swagger) and v3 specifications
- Serves response examples embedded in your spec
- Validates incoming requests against your API spec
- Supports script-driven responses in JavaScript or Groovy
- Can proxy real endpoints and replay their responses
- Runs in Docker, Kubernetes, AWS Lambda, or standalone JVM
You can also build self-contained Docker images that bundle the engine with your config, making mocks fully portable.
MockServer — Enterprise-Grade Mocking
MockServer is the heavyweight option for teams that need robust HTTP/HTTPS mocking with advanced features like request verification, expectation matching, and proxy recording.
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version: '3.8' services: mockserver: image: mockserver/mockserver:latest container_name: mockserver ports: - "1080:1080" environment: MOCKSERVER_INITIALIZATION_JSON_PATH: /config/expectations.json volumes: - ./config:/config restart: unless-stopped |
Comparison: Docker Mock API Servers
Tool | Language | GUI | OpenAPI Support | Best For |
|---|---|---|---|---|
Node.js | No | No | Quick CRUD from a JSON file | |
Node.js | Yes (desktop) | Import/Export | Design-first mocking with GUI | |
Go | Yes (web UI) | No | Lightweight, fast startup, team use | |
Java/Kotlin | No | Full (v2 + v3) | OpenAPI-first development | |
Java | No | Partial | Enterprise, verification, proxying |
The All-in-One Docker Stack: Putting It All Together
Here’s my favorite setup — a single Docker Compose file that gives you a mock API with fake data, all ready to go:
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version: '3.8' services: # Mock REST API from JSON json-server: image: williamyeh/json-server container_name: mock-rest-api ports: - "3000:3000" volumes: - ./data/db.json:/data/db.json command: --watch /data/db.json --host 0.0.0.0 restart: unless-stopped # Programmable mock server with admin UI smocker: image: ghcr.io/smocker-dev/smocker container_name: mock-programmable ports: - "8080:8080" - "8081:8081" restart: unless-stopped # OpenAPI-based mock (if you have a spec) imposter: image: outofcoffee/imposter-openapi container_name: mock-openapi ports: - "9090:8080" volumes: - ./openapi:/opt/imposter/config restart: unless-stopped |
Run docker compose up -d and you’ve got three different mock servers running simultaneously — each serving a different purpose. JSON Server handles your basic CRUD needs, Smocker handles dynamic/programmable mocks, and Imposter mocks your OpenAPI spec. Mix and match based on your project.
Bonus: Synthetic Data Generation
If you need to go beyond simple fake data into full synthetic datasets (think: realistic but privacy-safe data for testing ML models or populating staging databases), a few tools are worth knowing about:
- Synth — An open-source, data-as-code tool with a CLI workflow for generating consistent data at scale. Define your schema in a declarative format and generate as much data as you need.
- SDV (Synthetic Data Vault) — One of the OG open-source synthetic data solutions, great for tabular, relational, and time series data.
- Argilla Synthetic Data Generator — Uses LLMs to generate training datasets. Includes Docker configurations for easy deployment.
Perfect For: Quick Reference Guide
- Building a frontend prototype? Lorem Picsum + @faker-js/faker + JSON Server
- Testing a microservices architecture? Mockoon or Imposter with Docker Compose
- Running CI/CD pipeline tests? Smocker or MockServer (programmable, API-driven mocks)
- Demoing to a client? Lorem Picsum (realistic photos) + Faker.js (realistic data) + Mockoon (configurable API)
- Offline/air-gapped development? JSON Server with pre-generated db.json + client-side Canvas placeholders
- Bundle-size sensitive frontend? Falso (tree-shakable) + Placehold.co (SVG, tiny payload)
FAQ
Is Lorem Ipsum still used in 2026?
Absolutely. Lorem Ipsum is still the go-to placeholder text for mockups, prototypes, and layout testing. The tooling has evolved with AI-enhanced generators, but the classic Latin text remains the industry standard.
What happened to the original Faker.js?
The original maintainer Marak Squires intentionally sabotaged the library in early 2022. The community forked it as @faker-js/faker, which is now actively maintained and at version 10.3.0 with over 70 locales and hundreds of data generators.
Does Lorem Picsum require an API key?
Nope. Lorem Picsum is completely free and requires no API key. Just construct a URL like https://picsum.photos/400/300 and you get a random placeholder image. It sources real photos from Unsplash.
What’s the difference between Faker.js and Falso?
@faker-js/faker is the full-featured option with 70+ locales and a massive API surface. Falso is lighter, fully tree-shakable, and TypeScript-first — making it better for frontend apps where bundle size matters. Faker has more generators, Falso has smaller bundles.
Can I self-host a placeholder image server with Docker?
There’s no official Lorem Picsum Docker image, but you can generate placeholder images client-side with Canvas or SVG, or use Placehold.co’s API. For fully offline setups, pre-download images and serve them from a simple Nginx Docker container.
What’s the fastest way to create a mock REST API?
JSON Server. Create a db.json file with your data, run it in Docker with the williamyeh/json-server image, and you instantly have full CRUD endpoints with pagination, filtering, and sorting. Takes about 30 seconds.
Which mock API server works best with OpenAPI specs?
Imposter is the best choice for OpenAPI-first development. It reads your Swagger v2 or OpenAPI v3 spec, automatically creates mock endpoints, and serves the example responses from your specification. Runs in Docker, Kubernetes, or AWS Lambda.
How do I generate fake data for a Docker-based mock API?
Use @faker-js/faker to generate a db.json file with realistic data, then serve it with JSON Server in Docker. There’s even a docker-json-server-faker image that bundles both together, letting you generate data with JavaScript right inside the container.
Is Chance.js better than Faker.js?
They serve different needs. Chance.js is lighter and more flexible for basic random data generation. Faker.js is the full package with locale support, entity generators, and a massive API. Use Chance.js for simplicity, Faker.js for comprehensiveness.
Can I use placeholder data generators in CI/CD pipelines?
Yes, and Docker-based solutions make this easy. Smocker and MockServer are particularly good for CI/CD because they support programmatic mock registration via API calls, so your test scripts can set up exactly the mocks they need.
What Node.js version does Faker.js v10 require?
Faker v10 requires Node.js version 20 or above. If you’re stuck on an older Node version, you’ll need to use Faker v9 or switch to an alternative like Falso or Chance.js which have lower requirements.
What’s the best placeholder image service for production prototypes?
Lorem Picsum for realistic photos (it uses real Unsplash images), or Placehold.co for labeled dimension placeholders. Lorem Picsum’s seed feature ensures consistent images across page loads, which is great for client demos.
