[](https://colab.research.google.com/github/rmbell09-lang/tradesight/blob/main/intro_demo.ipynb)
[](https://pypi.org/project/tradesight/)
# π― TradeSight β Python Algorithmic Trading & Backtesting Strategy Lab
[](https://www.python.org/downloads/)
[](https://flask.palletsprojects.com/)
[](https://opensource.org/licenses/MIT)
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[](https://github.com/rmbell09-lang/tradesight)
[](https://github.com/rmbell09-lang/tradesight#strategies)
**Build, test, and evolve trading strategies with AI β entirely on your own machine. No cloud subscription. No data leaks. No monthly fees.**
TradeSight is a self-hosted Python app that runs AI-powered strategy tournaments overnight, backtests technical indicators, and executes paper trades via Alpaca β all from a local web dashboard.
---
## π€ Who Is This For?
- **Algorithmic trading hobbyists** who want to test strategies without risking real money
- **Python developers** exploring quantitative finance and AI-driven decision systems
- **Privacy-conscious traders** who don't want their strategies on someone else's server
- **Makers** building autonomous financial agents
---
## β¨ Features
| Feature | Description |
|---|---|
| 𧬠**AI Strategy Tournaments** | Automated overnight evolution of trading strategies β the best wins, rest are retired |
| π **15+ Technical Indicators** | MACD, RSI, Bollinger Bands, EMA crossovers, ATR, volume analysis, and more |
| πΈ **Paper Trading** | Connect Alpaca paper account β trade with fake money, track real P&L |
| π **Multi-Market Scanner** | Scan stocks + Polymarket prediction markets for signals simultaneously |
| π **Web Dashboard** | Real-time Flask interface β positions, signals, tournament results, logs |
| β° **Cron Automation** | Overnight strategy improvement runs automatically β wake up to new results |
| π **100% Local** | Runs on your machine. Your strategies stay yours. |
---
## π Quick Start
### Requirements
- Python 3.11+
- macOS or Linux (Windows via WSL)
- [Alpaca paper trading account](https://alpaca.markets/) (free, optional β demo mode works without it)
### Install
**macOS (Homebrew):**
```bash
brew tap rmbell09-lang/tradesight
brew install tradesight
```
**From source:**
```bash
git clone https://github.com/rmbell09-lang/tradesight.git
cd tradesight
pip install -r requirements.txt
```
### Run
```bash
python START_TRADESIGHT.py
```
Dashboard opens at **http://localhost:5000**
### Demo Mode (No API Keys Required)
TradeSight runs fully in demo mode with simulated market data β no Alpaca account needed to explore.
### Live Paper Trading (Optional)
1. Create a free [Alpaca paper account](https://alpaca.markets/)
2. Add your API keys to `config/api_keys.json`:
```json
{
"alpaca_key": "YOUR_KEY",
"alpaca_secret": "YOUR_SECRET",
"paper": true
}
```
---
## πΈ Dashboard
```
βββββββββββββββββββββββββββββββββββββββββββββββββββ
β TradeSight Dashboard [Localhost:5000] β
ββββββββββββ¬βββββββββββ¬ββββββββββββ¬ββββββββββββββββ€
β Markets βTournamentsβ Trading β Settings β
ββββββββββββ΄βββββββββββ΄ββββββββββββ΄ββββββββββββββββ€
β Active Signals: 3 Open Positions: 2 β
β Best Strategy: MACD Crossover (score: 0.72) β
β Paper P&L: -$113.96 (initial RSI strategy) β
β Next Tournament: Tonight @ 2:00 AM β
βββββββββββββββββββββββββββββββββββββββββββββββββββ
```
---
## π§ͺ Test Results
```
169/169 tests passing β
```
```bash
python -m pytest tests/ -v
```
---
## ποΈ Architecture
```
tradesight/
βββ src/
β βββ scanner.py # Multi-market signal scanner
β βββ strategy_lab/ # AI tournament engine
β βββ trading/ # Alpaca paper trade executor
β βββ indicators/ # 15+ technical indicators
β βββ automation/ # Overnight cron jobs
βββ web/ # Flask dashboard
βββ config/ # API keys + settings
βββ data/ # Price history cache
βββ tests/ # 169 unit tests
```
---
## π Live Paper Trading β April 2026
Real money-at-risk (on paper). Updated automatically. System has been live since March 2026.
**Current Portfolio:** $532 total value | **+6.43% total return** (+$32.15)
| Strategy | Trades | P&L | Win Rate |
|---|---|---|---|
| MACD Crossover | 1 | +$17.89 | 100% β
|
| VWAP Reversion | 1 | -$4.75 | 0% |
| RSI Mean Reversion | 5 | -$13.77 | 20% |
**Recent Closed Trades (Last 7 Days):**
| Symbol | Strategy | Entry | Exit | P&L |
|---|---|---|---|---|
| JPM | MACD Crossover | $242.94 | $303.24 | +$17.89 β
|
| SPY | RSI Mean Reversion | $596.36 | $649.79 | +$6.06 β
|
| AMZN | VWAP Reversion | $223.25 | $209.69 | -$4.75 |
| QQQ | RSI Mean Reversion | $590.06 | $565.22 | -$6.56 |
| GOOG | RSI Mean Reversion | $297.77 | $276.47 | -$13.28 |
> This is a live paper trading account connected to Alpaca. All prices are real market data; no real money at risk. System runs overnight tournaments to evolve strategy parameters automatically. Early RSI underperformance drove a regime-filter upgrade now in production.
---
## πΊοΈ Roadmap
- [x] Multi-indicator technical analysis (15+ indicators)
- [x] AI strategy tournament engine
- [x] Alpaca paper trading integration
- [x] Real-time web dashboard
- [x] Overnight automation (cron)
- [ ] Phase 1: Active stop-loss + take-profit execution
- [ ] Phase 1: Trailing stop with high-water mark
- [ ] Phase 2: Confluence strategy (multi-indicator entry gates)
- [ ] Phase 2: Market regime detection (bull/bear/sideways filter)
- [ ] Phase 3: Monte Carlo simulation for strategy validation
---
---
## π° Support Development
TradeSight is MIT-licensed and free to use. If it saved you time or you want the packaged strategy lab with setup guide and pre-tuned parameters:
**[Get TradeSight Strategy Lab on Gumroad β](https://qcautonomous.gumroad.com/l/zpkutz)** β $49 one-time
Includes: packaged download, setup walkthrough, pre-configured Alpaca integration, and strategy parameter reference.
## π Related Projects & Alternatives
TradeSight is similar to β but different from β these popular Python trading tools:
| Project | What It Does | How TradeSight Differs |
|---|---|---|
| [backtrader](https://github.com/mementum/backtrader) | Python backtesting framework | TradeSight adds AI strategy evolution + live paper trading web dashboard |
| [freqtrade](https://github.com/freqtrade/freqtrade) | Crypto trading bot | TradeSight focuses on **stocks** (Alpaca API) with overnight strategy tournaments |
| [vectorbt](https://github.com/polakowo/vectorbt) | Vectorized backtesting in notebooks | TradeSight is a self-hosted web app β no notebook required |
| [zipline-reloaded](https://github.com/stefan-jansen/zipline-reloaded) | Algorithmic trading library | TradeSight is a full app, not a library β no Python trading experience needed |
| [Jesse](https://github.com/jesse-ai/jesse) | Crypto strategy framework | TradeSight is for **stocks + prediction markets**, not crypto |
| [nautilus_trader](https://github.com/nautechsystems/nautilus_trader) | High-performance trading platform | TradeSight is simpler, self-hosted, built for hobbyists not HFT |
| [BillingWatch](https://github.com/rmbell09-lang/BillingWatch) | Self-hosted billing anomaly detection | Same maker β catch Stripe issues before they cost you |
> **Also useful for:** python trading bot Β· algorithmic trading python Β· paper trading software Β· free backtesting Β· stock trading python Β· quantitative finance Β· algo trading strategy tester Β· self-hosted trading platform Β· automated trading system Β· backtesting framework
---
## π License
MIT β free to use, modify, and build on.
---
## β If This Helped You
Star the repo β it helps other Python traders find it.
Got broken AI-generated code? β [Vibe Code Rescue](https://rmbell09-lang.github.io/tradesight/vibe-code-rescue.html)