Jupyter Notebook Examples¶

Interactive Jupyter notebooks for exploring the ProjectX Python SDK.

Available Notebooks¶

Getting Started¶

Basic Connection - First steps with the SDK
Trading Suite Setup - Complete trading environment setup
Market Data Exploration - Working with historical and real-time data

Trading Strategies¶

Simple Moving Average Strategy - Basic trend following
RSI Mean Reversion - Oversold/overbought trading
Volume Profile Trading - Key level identification

Technical Analysis¶

Indicator Showcase - All 59+ indicators demonstrated
Pattern Recognition - FVG and Order Block detection
Multi-Timeframe Analysis - Confluence across timeframes

Risk Management¶

Position Sizing - Kelly Criterion and fixed risk
Portfolio Analytics - Performance metrics and analysis
Risk Metrics - Sharpe, Sortino, and drawdown

Market Microstructure¶

OrderBook Analysis - Level 2 data exploration
Order Flow - Trade classification and imbalance
Spoofing Detection - Identifying manipulation patterns

Running the Notebooks¶

Prerequisites¶

# Install Jupyter and dependencies
pip install jupyter notebook ipywidgets plotly pandas

# Install the SDK
pip install project-x-py[all]

Environment Setup¶

Create a .env file in the notebooks directory:

PROJECT_X_API_KEY=your-api-key
PROJECT_X_USERNAME=your-username

Launch Jupyter¶

# Clone the repository
git clone https://github.com/TexasCoding/project-x-py.git
cd project-x-py/notebooks

# Start Jupyter
jupyter notebook

Notebook Features¶

Interactive Visualizations¶

Real-time chart updates with Plotly
Interactive order book visualization
Candlestick charts with indicators
Performance dashboards

Live Data Integration¶

Connect to real-time WebSocket feeds
Stream market data into notebooks
Place and monitor orders interactively
Real-time position tracking

Educational Content¶

Step-by-step explanations
Code cells with detailed comments
Markdown cells with theory
Exercise cells for practice

Best Practices¶

Safety First¶

# Always use paper trading for testing
suite = await TradingSuite.create(
    ["MNQ"],
    mode="paper"  # Paper trading mode
)

Memory Management¶

# Clean up resources in notebooks
try:
    # Your trading code here
    pass
finally:
    await suite.disconnect()

Async in Notebooks¶

# Use nest_asyncio for async support
import nest_asyncio
nest_asyncio.apply()

# Now you can use await directly
suite = await TradingSuite.create(["MNQ"])

Contributing Notebooks¶

We welcome notebook contributions! Please ensure:

Clear objectives - State what the notebook demonstrates
Runnable code - Test with paper trading account
Documentation - Explain concepts and code
Visualizations - Use charts to illustrate points
Safety warnings - Include risk disclaimers

Example Notebook Structure¶

# Cell 1: Setup
import asyncio
import nest_asyncio
from project_x_py import TradingSuite
import plotly.graph_objects as go
import pandas as pd

nest_asyncio.apply()

# Cell 2: Connect
suite = await TradingSuite.create(
    ["MNQ"],
    timeframes=["1min", "5min"],
    features=["orderbook"]
)

# Cell 3: Analysis
# Your strategy or analysis code

# Cell 4: Visualization
fig = go.Figure(data=[
    go.Candlestick(
        x=df['timestamp'],
        open=df['open'],
        high=df['high'],
        low=df['low'],
        close=df['close']
    )
])
fig.show()

# Cell 5: Cleanup
await suite.disconnect()

Resources¶

License¶

All notebooks are provided under the MIT License. Use at your own risk for educational purposes only.