Python Analysis Tool Reference

Python Analysis (`execute_python`) - Your Primary Tool

ALWAYS use execute_python() when the user asks for:

Technical indicators (RSI, MACD, Bollinger Bands, moving averages, etc.)
Chart visualizations or plots
Statistical calculations or market analysis
Pattern detection or trend analysis
Any computational analysis of price data

Why `execute_python()` is preferred:

Chart data (df) is automatically loaded from ChartStore (visible time range) when chart is visible
If no chart is visible (symbol is None), df will be None - but you can still load alternative data!
Full pandas/numpy/talib stack pre-imported
Use plot_ohlc(df) for instant professional candlestick charts
Access to 150+ indicators via indicator_registry
Access to DataStores and registry - order_store, chart_store, datasource_registry
Can load ANY symbol/timeframe using datasource_registry even when df is None
Results include plots as image URLs that are automatically displayed to the user
Prints and return values are included in the response

CRITICAL: Plots are automatically shown to the user

When you create a matplotlib figure (via plot_ohlc() or plt.figure()), it is automatically:

Saved as a PNG image
Returned in the response as a URL (e.g., /uploads/plot_abc123.png)
Displayed in the user's chat interface - they see the image immediately

You MUST use execute_python() with plot_ohlc() or matplotlib whenever the user wants to see a chart or plot.

IMPORTANT: Never use `get_historical_data()` for chart analysis

get_historical_data() requires manual timestamp calculation and is only for custom queries
When analyzing what the user is viewing, ALWAYS use execute_python() which automatically loads the correct data
The df DataFrame in execute_python() is pre-loaded with the exact time range the user is viewing

Example workflows:

Computing an indicator and plotting (when chart is visible)

execute_python("""
df['RSI'] = talib.RSI(df['close'], 14)
fig = plot_ohlc(df, title='Price with RSI')
df[['close', 'RSI']].tail(10)
""")

Multi-indicator analysis (when chart is visible)

execute_python("""
df['SMA20'] = df['close'].rolling(20).mean()
df['BB_upper'] = df['close'].rolling(20).mean() + 2 * df['close'].rolling(20).std()
df['BB_lower'] = df['close'].rolling(20).mean() - 2 * df['close'].rolling(20).std()
fig = plot_ohlc(df, title=f"{chart_context['symbol']} with Bollinger Bands")
print(f"Current price: {df['close'].iloc[-1]:.2f}")
print(f"20-period SMA: {df['SMA20'].iloc[-1]:.2f}")
""")

Loading alternative data (works even when chart not visible or for different symbols)

execute_python("""
from datetime import datetime, timedelta

# Get data source
binance = datasource_registry.get_source('binance')

# Load data for any symbol/timeframe
end_time = datetime.now()
start_time = end_time - timedelta(days=7)

result = await binance.get_history(
    symbol='ETH/USDT',
    interval='1h',
    start=int(start_time.timestamp()),
    end=int(end_time.timestamp())
)

# Convert to DataFrame
rows = [{'time': pd.to_datetime(bar.time, unit='s'), **bar.data} for bar in result.bars]
eth_df = pd.DataFrame(rows).set_index('time')

# Analyze and plot
eth_df['RSI'] = talib.RSI(eth_df['close'], 14)
fig = plot_ohlc(eth_df, title='ETH/USDT 1h - RSI Analysis')
print(f"ETH RSI: {eth_df['RSI'].iloc[-1]:.2f}")
""")

Access stores to see current state

execute_python("""
print(f"Current symbol: {chart_store.chart_state.symbol}")
print(f"Current interval: {chart_store.chart_state.interval}")
print(f"Number of orders: {len(order_store.orders)}")
""")

Only use `get_chart_data()` for:

Quick inspection of raw bar data
When you just need the data structure without analysis

Quick Reference: Common Tasks

User Request	Tool to Use	Example
"Show me RSI"	`execute_python()`	`df['RSI'] = talib.RSI(df['close'], 14); plot_ohlc(df)`
"What's the current price?"	`execute_python()`	`print(f"Current: {df['close'].iloc[-1]}")`
"Is this bullish?"	`execute_python()`	Compute SMAs, trend, and analyze
"Add Bollinger Bands"	`execute_python()`	Compute bands, use `plot_ohlc(df, title='BB')`
"Find swing highs"	`execute_python()`	Use pandas logic to detect patterns
"Plot ETH even though I'm viewing BTC"	`execute_python()`	Use `datasource_registry.get_source('binance')` to load ETH data
"What indicators exist?"	`search_indicators()`	Search by category or query
"What chart am I viewing?"	N/A - automatic	Chart info is in dynamic system prompt
"Check my orders"	`execute_python()`	`print(order_store.orders)`
"Read other stores"	`read_sync_state(store_name)`	For TraderState, StrategyState, etc.

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