InvestorMate: AI-Powered Stock Analysis in Python — And calling out open-source devs for feedback and contributions

Source: Dev.to

What is InvestorMate?

InvestorMate is a Python package for stock research and analysis. The idea is simple: one package, one import, and you can go from raw data to AI‑powered insights without juggling multiple libraries.

What you get today:

• AI‑powered analysis – Ask natural language questions about any stock using OpenAI, Claude, or Gemini
• Stock data – Prices, financials, news, and SEC filings via yfinance
• 60+ technical indicators – SMA, EMA, RSI, MACD, Bollinger Bands, and more
• 40+ financial ratios – ROIC, WACC, DuPont ROE, TTM metrics, etc.
• Stock screening – Value, growth, dividend, and custom screens
• Portfolio analysis – Allocation, Sharpe ratio, sector mix
• Backtesting – Strategy framework with examples (e.g., RSI)
• Correlation & sentiment – Correlation matrices and news sentiment

Quick example

from investormate import Investor, Stock

# AI‑powered analysis
investor = Investor(openai_api_key="sk-...")
result = investor.ask("AAPL", "Is Apple undervalued compared to its peers?")
print(result)

# Stock data and analysis
stock = Stock("AAPL")
print(f"Price: ${stock.price}")
print(f"P/E Ratio: {stock.ratios.pe}")
print(f"RSI: {stock.indicators.rsi()}")

Honest Assessment

What’s solid: Fundamentals, technicals, AI integration, screening, and backtesting are in good shape. The API is straightforward, and you can get useful results quickly.

What’s evolving: Data comes mainly from yfinance (no fallbacks yet), valuation methods (DCF, comps) aren’t built yet, and some areas (e.g., portfolio risk, SEC Edgar integration) are still on the roadmap. Details are in the ROADMAP.md.

Bottom line: It’s useful today for research and learning, and the project is actively being expanded toward a more robust, feature‑complete toolkit.

We Want Contributors

We’re a small team with a big vision: a Python package that can support serious financial research. We can’t get there alone, and we’d love your help.

• New to open source? See the CONTRIBUTING.md for setup steps, how to find issues, and how to open your first PR.
• Prefer docs? We need clearer guides, more examples, and better API documentation.
• Want to code? The roadmap lists robustness fixes, validation, tests, and new features.
• Have ideas? Open a GitHub Discussion — we read them and respond.

How to get started

1. Fork the repo and clone it locally.
2. Read the CONTRIBUTING.md for setup.
3. Check the ROADMAP.md for priorities.
4. Look for issues labeled good first issue, help wanted, or documentation.
5. Comment on an issue to claim it, then open a PR.

We review PRs within a few days, give feedback, and merge when things look good. Every contribution helps, whether it’s a bug fix, a doc update, or a new example.

Try It Out

pip install investormate

Then run the examples in the examples/ folder.

Links

• GitHub:
• PyPI:
• Contributing:
• Roadmap:

InvestorMate is for educational and research purposes only. It is not financial advice. Always verify information and consult a qualified financial advisor before making investment decisions.