Forem: Joel

Generate Realistic Mock Data with ease in VS Code with this Super Extension

Joel — Fri, 18 Apr 2025 12:13:20 +0000

Ever built an app and wasted hours manually seeding test data or faking API responses? Whether you're testing a UI, simulating an API, or populating a dev database, mock data is essential. But creating it shouldn't be a chore.

That’s where the Mock Data Generator VS Code extension comes in.

This extension is built to simplify and automate the creation of mock data across different databases and model types. No more hardcoding test users, faking API responses by hand, or wasting time creating scripts to seed your local dev database. This tool does all that and more right from your VS Code workspace.

In this article, I’ll explain the extension's purpose, why it was built, and how you can use it to boost your dev workflow.

Why This Extension?

As a developer working with microservices and multiple database types, I constantly needed realistic mock data to seed databases for development, test APIs before real data exists, simulate various edge cases, or build isolated frontend components. This part of the development can be boring and time-consuming. Existing solutions were either too simple with lorem ipsums everywhere, too rigid, required writing scripts, or lacked flexibility for diverse schemas. The Mock Data Generator, a powerful yet lightweight VS Code extension, was created to bridge these gaps. It lets you create realistic, customizable, and model-aware mock data in seconds right inside your coding environment.

Common Use Cases

Seeding development databases (MongoDB, PostgreSQL, SQL Server, and more)
Testing application features with real-world-like data
Creating JSON or SQL output for frontend/backend integration
Validating model relationships and constraints
It supports multiple ORMs, database types, and can infer from TypeScript interfaces.
Auto-detecting schema from Typescript, Mongoose, and ORM models

Core Features at a Glance

Here’s what makes this extension stand out:

Supports Multiple ORMs & Databases: Works with MongoDB, PostgreSQL, SQL Server, and more.
Hashed Passwords for Auth Testing: Bcrypt support for password fields.
Mock Directly to Database: Push generated data straight into MongoDB or SQL databases.
Intelligent Field Detection: Recognizes fields like email, password, createdAt, and generates appropriate values.
Relation Mapping: Automatically generates related data between models (e.g., users and posts).
Customizability: Developers can define mock rules and overrides via config files.
Intelligent Model Detection: Reads only true models and ignores non-models like enums, request, and response classes...
Supports both local and remote databases

Using the Extension

Step 1: Install the Extension
Search for Mock Data Generator in the VS Code Extensions Marketplace

Step 2: Run the Extension
Create or open a project, and access extension features via the Command Palette (Ctrl+Shift+P or Cmd+Shift+P). Run Mock Data Generator. This will give you a drop-down menu of options.

Step 3: Generate Mock Data
Select the Generate Mock Data option to start generating your mock data. Enter the number of mock data you want to generate. The default is 10, however, this can also be customized in the configuration settings

Step 5: Select your Output Format
Select your output format to complete the mock data generation process, or select the Database option to populate your test database directly. This will require a connection string.

Boom! You’ll get generated data tailored to your models and config. If you selected 'Database', the data will be populated directly into the database, or a file will be created containing your mock data if other output options are selected.

Try it out!

Tired of manually faking data or writing the same seed scripts over and over? The Mock Data Generator extension takes that pain away.

With just a few clicks, you can generate rich, realistic mock data tailored to your models, no boilerplate scripts, no lorem ipsum nonsense.

Whether you're building out UI components, testing API flows, or seeding a development database, this tool gives you data that feels real.

Install it now on VS Code and give your projects a serious productivity boost.
Spend less time mocking and more time building.

Kickstarting Your Tech Journey: Essential Software Engineering Best Practices for Success

Joel — Sun, 08 Sep 2024 06:43:41 +0000

Hello and welcome to the start of an exciting journey into the world of technology! I’m thrilled to have you here as we dive into the essential software engineering best practices that are the secret sauce to building reliable, maintainable, and scalable code. Ready to set a strong foundation? Let’s get started!

Why Best Practices Matter
In the ever-changing tech landscape, you might wonder why best practices matter. Picture this: You’re building a house. Would you start without a blueprint or a solid foundation? Of course not! Similarly, in software development, best practices are your blueprint, ensuring that your code isn’t just functional but robust and adaptable.

Key Best Practices to Embrace

1. Write Clean, Maintainable Code
Imagine your code as a storybook. Would you want to read a book with messy handwriting and confusing plot twists? Of course not! Here’s how to keep your code clean and readable:

Descriptive Naming: Think of meaningful names as clear signposts guiding you through your code. Instead of temp1 or data, use names like userList or orderDetails.
Modular Design: Break your code into bite-sized chunks. Just like you wouldn’t want to eat a whole pizza in one bite, avoid huge functions by creating smaller, reusable modules.

2. Leverage Version Control
Version control is like a time machine for your code. Imagine being able to travel back in time to fix a bug or see how your project evolved. Tools like Git make this possible:

Collaboration: Think of Git as a giant collaborative whiteboard where you and your team can draw, erase, and revise without losing track of what’s been done.
History: It’s like keeping a diary of your project’s life. You can look back at past versions to understand changes or recover lost work.

3. Embrace Testing
Testing is like having a safety net. Imagine walking a tightrope without one—pretty nerve-wracking, right? Testing ensures that your code doesn’t fall into the abyss:

Unit Tests: These are like individual safety checks for each part of your code. If one part fails, you know exactly where to look.
Integration Tests: They check if different parts of your project work together smoothly, like making sure all the ingredients in your recipe blend perfectly.
Automated Testing: Imagine having a robot that continuously tests your code while you focus on building new features. That’s the power of automation!

4. Prioritize Documentation
Good documentation is like having a map for your code. Without it, navigating a large project can be like wandering through a maze without a compass:

Code Comments: Think of comments as notes in the margins of your codebook. They help explain tricky parts or decisions.
Readme Files: A clear, concise Readme file is like a guidebook for your project, detailing how to get started and what the project does.

5. Apply Design Principles

Design principles are like the golden rules of software development. They help ensure that your code is not only functional but also elegant and adaptable:

SOLID Principles: These principles help you build software that’s easy to manage and extend. For example, the Single Responsibility Principle ensures that each class or module has one job, making it easier to understand and modify.
DRY (Don’t Repeat Yourself): Avoid redundancy by reusing code. It’s like not reinventing the wheel every time you build something.

Putting It All Together
Adopting these best practices might seem like a lot at first, but they’re crucial for crafting robust software. Start small—focus on implementing one or two practices, and gradually build on them. Tools like linters and CI/CD pipelines can also help automate and enforce these best practices, making your life easier.

Looking Ahead
In future posts, we’ll connect these best practices to more advanced topics like AWS cloud services and machine learning. Understanding these fundamentals will provide a solid base as we explore how to leverage cloud technologies and AI in your projects.

Thank you for joining me on this journey! I’m excited to share more insights and practical tips as we delve deeper into the fascinating world of technology. Stay tuned!