The Story of Making Software for Stocks｜The Joy of Development Begins with an Idea

Introduction

"It was just an idea..." — and suddenly a few lines of code turn into something you actually want to use.

That's exactly what happened here. A tiny spark to "try building my own stock tool" became a full-fledged app that pulls price data, draws charts, and calculates returns. This article walks through that journey: the development choices, why it was worth doing, and the lessons that surfaced.

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Why I Built a Stock App on a Whim

Curiosity > necessity

• Scrolling quotes on my phone stopped being satisfying.
• I kept thinking, "I'd trust the numbers more if I crunched them myself."
• It was the perfect excuse to play with Rust, WASM, TypeScript, and some APIs.

I didn't build it because I had to; I built it because I was curious. That light, low-stakes mindset is what kept the project moving.

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First: Grab the Data (search intent: free stock data)

Stooq's CSV API is almost too easy

• No API key required.
• Hit an endpoint like https://stooq.pl/q/d/l/?s=7203.jp&i=d and you get daily data.
• Works for both Japanese and U.S. tickers.
• Added a local CSV fallback so the app still works offline.

Search intent answer: "How do I get stock quotes for free?" → Use Stooq; it's fast, free, and doesn't need a key.

Insight: Zero-key APIs are perfect for prototyping — no sign-up friction, no quota stress.

Action: Pair Stooq with a local CSV cache and treat it like your own mini data lake.

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Next: Draw the Chart (search intent: charting library)

LightweightCharts for the win

• TradingView's LightweightCharts library
• Candlesticks render instantly
• A chart on screen in a few dozen lines
• Plays nicely with WASM data processing

Seeing the first chart appear is the "it actually works" moment.

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Offload Heavy Math to Rust/WASM (search intent: why WASM for stocks)

Why bother with WASM?

• Faster number crunching than plain JavaScript
• Return calculations (calc_return, calc_hold_return) live in Rust
• Runs safely off the main thread, so the UI stays snappy
• Scales if you later load more tickers or longer histories

Search intent answer: "Is WASM worth it?" → Yes, heavy calculations become lightweight and non-blocking.

Suggestion: Even if your dataset is small, moving logic to WASM early keeps the door open for bigger data later.

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Does This Even Make Sense?

Meaning shows up after you ship

• Building it yourself deepens your intuition for price movement.
• You gain a conviction that off-the-shelf tools can't provide.
• It becomes genuinely useful once you keep layering features.
• The skills transfer cleanly to other projects.

It's fine to start with "kind of." Ideas grow once you start shipping. If you demand meaning upfront, you'll never begin.

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Feature Roadmap

Clear next steps

• Smarter ticker search (JP/EN)
• Backtesting with historical data
• Benchmarks against S&P 500 and TOPIX
• Algorithm experiments that surface trade signals
• Mobile-first UI polish

Just listing the wishlist keeps momentum high.

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Summary

• An impulsive stock app became a full-fledged tool.
• Free data via Stooq's CSV API keeps setup frictionless.
• LightweightCharts plus Rust/WASM make charts fast and math faster.
• The meaning shows up after you start; just build the first version.

Next action → Pick one finance task you want to automate and code it. Idea-first projects tend to keep going.

Discover Blurb (short)

Built a stock tracker on a whim and turned it into a learning goldmine: free data from Stooq, instant charts with LightweightCharts, and high-speed math in Rust/WASM. If you're curious, pick one thing you want to automate and ship it — you'll be surprised how far a small idea can go.