This is a submission for the Amazon Q Developer "Quack The Code" Challenge: Crushing the Command Line & Exploring Possibilities
What I Built 🛠️📈
I have built Stock Pulse. Stock Pulse is a Python tool that analyzes stocks using financial metrics, news trends, and AI-powered sentiment analysis. It provides investment recommendations (BUY, SELL, HOLD) with detailed reasoning based on comprehensive analysis.
I have used Amazon Q Developer CLI to Vibe Code this in under 1 hour without writing a single line of code. I have recorded my full vibe-coding session. It can be found in the Demo section below.
Features ✨
- 🔍 Analyze multiple stocks at once
- 💹 Fetch financial metrics and news data using yfinance
- 🤖 Utilize OpenAI's GPT-4o-mini model for intelligent analysis
- 📈 Generate investment signals with detailed reasoning
- ⚠️ Identify key factors and potential risks
- 💻 Command-line interface and Streamlit web UI
Screenshots 🖼️
Demo 🎬
Streamlit Link: here
Vibe-Coding Session Demo:
Code Repository 🗃️
mtwn105
/
stock-pulse
Feel the pulse of the market with AI-powered stock insights. Vibe Coded with Amazon Q Developer CLI in 1 hour!
Stock Pulse
Feel the pulse of the market with AI-powered stock insights.
Vibe Coded with Amazon Q Developer CLI in 1 hour!
Overview
Stock Pulse is a Python tool that analyzes stocks using financial metrics, news trends, and AI-powered sentiment analysis. It provides investment recommendations (BUY, SELL, HOLD) with detailed reasoning based on comprehensive analysis.
Features
- Analyze multiple stocks at once
- Fetch financial metrics and news data using yfinance
- Utilize OpenAI's GPT-4o-mini model for intelligent analysis
- Generate investment signals with detailed reasoning
- Identify key factors and potential risks
- Command-line interface and Streamlit web UI
Installation
-
Clone the repository:
git clone https://github.com/yourusername/stock-pulse.git cd stock-pulse -
Install dependencies using Poetry:
poetry install -
Create a
.envfile with your OpenAI API key:cp .env.example .envThen edit the
.envfile to add your OpenAI API key.
Usage
Command Line Interface
Analyze stocks using the command line:
# Analyze a single stock
poetry run python…How I Used Amazon Q Developer 🤖⚡
I have used Amazon Q Developer CLI to Vibe Code this project in under 1 hour without writing a single line of code manually.
Initial Prompt 📝
I kickstarted the development by giving Amazon Q a single, well-crafted prompt:
i want to create a stock analysis script in python using langchain and langgraph with using openai llm with gpt-4o-mini model.
use poetry for deps management. poetry is already installed on the system.
use yfinance tools from langchain for news and price data. use last 1 year price return.
also use other financial metrics from yfinance like roce, roe, etc. and llm will analyze and return recommendation with signal - BUY,SELL,HOLD and reasoning for it.
accept list of tickers as argument to the script.
use poetry to setup project and add deps. dont create pyproject.toml by yourself.
use python best practices and folder structure for a cli.
Amazon Q responded by generating an organized, ready-to-run CLI project using Poetry, fetching real-time stock data, and integrating GPT-4o-mini for analysis and recommendations.
Iterative Development with Q 🔁💡
I continued to use Amazon Q Developer CLI throughout the process for:
- Debugging and resolving errors by simply pasting the error logs into Q.
- Requesting code refactors and feature enhancements (e.g., adding streamlit UI or news items in output).
- Running Git commands and pushing my code without switching terminals.
Zero Manual Edits ✋❌
From project initialization to the final commit, I did not write or modify any code manually. Every change—big or small—was executed through Amazon Q Developer CLI.
To show full transparency and the incredible capability of Amazon Q, I’ve recorded my entire coding session, which you can find in the demo video above.
Why Amazon Q Was a Game-Changer 💥🎯
Amazon Q isn’t just another coding assistant—it’s an AI developer. It allowed me to stay in flow, innovate rapidly, and push creative boundaries, eliminating friction from the development lifecycle.
From initializing the project with Poetry to handling dependencies, coding logic, bug fixing, git commands, and even feature iterations—Amazon Q handled everything like a true coding copilot. I never had to touch the code manually.
I’ve also recorded my entire coding session (watch the demo video above) to showcase how seamlessly Q guided me through the entire development lifecycle.
Conclusion ✅🎉
Participating in the Amazon Q Developer "Quack The Code" Challenge was a fun and productive experience. I built an intelligent UI & CLI-based stock analysis tool using LangChain, LangGraph, and OpenAI—all within an hour—thanks to the power of Amazon Q Developer CLI.
This project proved that with the right tools and a powerful AI assistant like Amazon Q Developer, building complex and intelligent applications becomes fast, efficient, and even enjoyable.
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