DEV Community: Alok Verma

# I Built a .gitignore Generator Because Setting Up a Project Should Be Simpler

Alok Verma — Mon, 12 Oct 2026 04:43:42 +0000

Every developer has probably done this at some point.

You create a new project, initialize Git, and then realize you still need to create a .gitignore file.

If you're working with a familiar stack, you probably know which files and directories to exclude. But when you're starting a new project, switching technologies, or working with an unfamiliar tool, things get a little less obvious.

Should node_modules be ignored? What about build output, environment files, IDE settings, caches, or framework-specific directories?

You can write the file yourself, copy one from another project, or search GitHub for an existing template.

I wanted to make that process a little easier, so I built DotGitIgnore.com.

What does it do?

DotGitIgnore is a free .gitignore generator for developers.

The idea is simple: choose the technologies, languages, frameworks, or tools you're using, and generate a .gitignore file that you can use in your project.

Instead of starting from an empty file or digging through repositories to find the right template, you can put together the rules you need in one place.

You can explore the available templates and build a file suited to your project without having to remember every generated directory or temporary file for every technology you use.

It's a small tool, but it's meant to solve a real problem that comes up during everyday development.

The tricky part wasn't the interface

The basic interface for a tool like this is relatively straightforward.

The more interesting challenge is the template collection behind it.

Different languages and frameworks have different conventions. Even within the same ecosystem, the files you want Git to ignore can vary depending on your workflow.

A template that works well for one project might not be enough for another. And blindly combining every possible ignore rule would make the output unnecessarily large and difficult to understand.

That meant thinking about how templates should be organized, how users should discover them, and how the generated output should remain useful rather than simply including as many rules as possible.

I also wanted to build around existing community-maintained templates instead of pretending I needed to invent every rule from scratch.

The goal is to make those resources easier to discover and use.

Building it as a proper web project

I didn't want the project to be only a working generator with a single page.

I also wanted to think about the less visible parts of running a useful developer tool: page structure, performance, discoverability, maintainability, and making sure the site remains straightforward to use.

That led me to work on things like:

A growing template collection: Making it easier to find ignore rules for different technologies and development environments.
A focused generator experience: Helping users get from selecting templates to the generated file without unnecessary steps.
Search-friendly template pages: Giving individual templates a clear purpose and making them easier to discover.
A lightweight experience: Keeping the tool centered on its primary job instead of burying it under features that don't help developers generate a .gitignore.

I'm also exploring ways to make the collection useful for newer AI-assisted development workflows, where projects may include tools and files that traditional templates don't always cover.

There's more to SEO than creating a page for every keyword

One unexpected part of building a public developer tool is thinking about how people will find it.

A developer might search for a general .gitignore generator. Someone else might be looking specifically for a template for Python, Next.js, Java, or a particular IDE.

Supporting those different needs makes sense, but simply creating hundreds of similar pages isn't a great strategy on its own.

Each page should help someone accomplish something.

That means thinking about useful content, internal navigation, canonical URLs, and how the generator itself connects to the template pages. It also means resisting the temptation to create pages just to make the site look bigger.

I'm still working through these challenges, and it's been a useful lesson in the difference between building something that works and building something people can actually discover and use.

Why build something this small?

I like projects that solve a problem developers already understand.

A .gitignore generator isn't a groundbreaking idea, and that isn't the point. Existing tools are useful, but there's still room to build a good experience, learn from the process, and make something that fits naturally into a developer's workflow.

For me, DotGitIgnore is also an opportunity to learn more about building and maintaining a real web product beyond the initial coding phase.

That includes handling a growing template collection, testing changes, thinking about search visibility, and figuring out which features genuinely make the product better.

The work doesn't end when the generator produces the expected output. That's when the next set of questions starts.

Give it a try

If you're starting a new project or just want a quicker way to create your ignore rules, take a look:

https://dotgitignore.com

I'd also love to hear how other developers manage their .gitignore files.

Do you usually copy a template from an existing project, use GitHub's templates, maintain your own reusable file, or generate one whenever you start something new?

I'm curious what works best for everyone.

Thanks for reading!

# Building an Overtime Pay Calculator Turned Out to Be More Complicated Than I Expected

Alok Verma — Mon, 12 Oct 2026 04:01:12 +0000

I've been working on a project called OvertimePayRate.com, and one thing I've learned so far is that a calculator can look simple on the surface while hiding a surprising amount of complexity underneath.

The idea sounds straightforward.

Enter your pay rate, add your overtime hours, select your state, and get an estimate of your overtime pay.

Pretty simple, right?

Well, not exactly.

The problem isn't the math

Calculating time-and-a-half is relatively easy. If someone earns $20 per hour, the usual overtime rate of 1.5× would be $30 per hour.

The harder part is figuring out which rules should apply in the first place.

Overtime rules in the US can vary by state. Federal requirements, state-specific provisions, salary thresholds, exemptions, and different work situations can all affect the calculation.

A basic calculator can give someone a number in seconds, but that doesn't necessarily mean the number reflects their circumstances.

That's what made this project interesting to me. I didn't want to build just another form with a few multiplication operations behind it. I wanted to explore how to make the result more useful while being honest about its limitations.

What I'm building

OvertimePayRate.com is an overtime pay calculator focused on workers in the United States.

The goal is to let users estimate their overtime pay without having to navigate a complicated spreadsheet or search through a dozen pages just to get started.

Some of the things I'm working on include:

State-specific calculations: Overtime rules aren't identical everywhere, so state selection needs to matter.
Occupation-based inputs: A person's work situation can affect which rules need closer examination.
A rule-based calculation engine: Keeping calculations separate from the UI makes the logic easier to test, review, and maintain.
Clear explanations: Showing a result is useful, but explaining the assumptions behind that result matters too.

I'm also treating legal accuracy as an ongoing responsibility, not something that can be solved by writing a calculation once and forgetting about it.

The results are estimates, not legal advice or a determination of what a particular employer owes.

The technical side

For the stack, I'm using technologies I wanted to explore in a real project rather than another tutorial.

Astro for the site and its page structure
React and TypeScript for interactive calculator functionality
Tailwind CSS v4 for styling
Supabase and Drizzle ORM for the database layer
Cloudflare for deployment

One architectural decision I'm paying particular attention to is separating the rules and calculation logic from the presentation layer.

When a rule changes, I don't want to hunt through UI components trying to figure out where a number was hardcoded. I want the relevant rule to be identifiable, testable, and associated with the period during which it applies.

That becomes especially important for a project dealing with laws and regulations, where a rule that was valid last year might not be valid today.

Of course, having a clean architecture doesn't automatically make the underlying legal data correct. Official sources still need to be checked, and the calculations need tests for the situations they're supposed to cover.

SEO is another challenge I'm thinking about

A calculator is useful, but people also need to be able to find it.

I'm working on making the site accessible through state-specific calculator pages and supporting content, rather than relying on a single homepage to answer every possible question.

That introduces another challenge: creating pages that actually help users instead of generating dozens of nearly identical URLs with different state names.

I'd rather have fewer pages with a clear purpose than a large number of pages that don't add much value.

It's also a reminder that building a useful web tool involves more than getting the core feature to work. Performance, accessibility, discoverability, maintainability, and trust all matter.

What I'm learning from the project

The biggest lesson so far is that the most interesting engineering problems aren't always the most visually impressive ones.

A calculator's interface might take only a small part of the development effort. The decisions behind the result can take much longer: how to represent rules, how to handle exceptions, how to test edge cases, and how to communicate uncertainty without confusing the user.

I'm also trying to avoid the temptation to make the project appear more complete than it is. For something that touches employment rules and money, being transparent about what a tool can and cannot determine is part of building it responsibly.

There is still plenty to improve, and that's part of the process.

If you're building a calculator, legal-information tool, or another small web product, I'd be interested to hear how you approach changing rules, edge cases, and keeping the results trustworthy.

You can check out the project here: OvertimePayRate.com

Thanks for reading!