Stock Module

The stock module provides market data access and analysis tools for stocks.

• Historical Data
  • Overview
  • Usage
  • Methods
  • Timeframes
  • Price Adjustments
  • Technical Analysis
  • Volume Analysis
  • Batch Operations
  • Error Handling
  • Performance Tips
• Historical Quotes
  • Overview
  • Usage
  • Parameters
  • Features
  • Feed Selection
  • Error Handling
• Historical Auctions
  • Overview
  • Usage
  • Parameters
  • Features
  • Pagination
  • Error Handling
• Company Logos
  • Overview
  • Usage
  • Parameters
  • Placeholder Images
  • Use Cases
  • Error Handling
  • Notes

Overview

The stock module includes:

• Assets: Stock asset information and metadata

• History: Historical price data and bars

• Quotes: Historical bid/ask quote data

• Auctions: Opening and closing auction data

• Logos: Company logo retrieval

• Screener: Screen for top gainers and losers

• Predictor: ML-based price predictions using Prophet

• Latest Quote: Real-time quote data

• Trades: Trade execution data

• Snapshots: Market snapshots

• Metadata: Market metadata, conditions, and exchanges

Features

Batch Operations

The stock module automatically handles batch operations for multiple symbols:

# Automatic batching for 200+ symbols
symbols = ["AAPL", "GOOGL", "MSFT", ...] # 500 symbols
quotes = api.stock.latest_quote.get_multiple(symbols)
# Automatically split into optimal batches

Feed Management

Automatic feed detection and fallback:

# Automatic feed selection
quote = api.stock.latest_quote.get("AAPL")
# Tries SIP → IEX → OTC based on subscription

# Manual feed selection
quote = api.stock.latest_quote.get("AAPL", feed="iex")

Quick Example

from py_alpaca_api import PyAlpacaAPI
import pendulum

api = PyAlpacaAPI(
    api_key="your_api_key",
    api_secret="your_secret_key"
)

# Get latest quote
quote = api.stock.latest_quote.get("AAPL")

# Get historical data
bars = api.stock.history.get_bars(
    symbol="AAPL",
    start=pendulum.now().subtract(days=30),
    end=pendulum.now(),
    timeframe="1Day"
)

# Get historical quotes with bid/ask spread
quotes = api.stock.quotes.get_historical_quotes(
    "AAPL",
    start="2024-01-01",
    end="2024-01-31"
)

# Get auction data
auctions = api.stock.auctions.get_auctions(
    "AAPL",
    start="2024-01-01",
    end="2024-01-31"
)

# Get company logo
logo_url = api.stock.logos.get_logo_url("AAPL")
logo_data = api.stock.logos.get_logo("AAPL")

# Get top gainers
gainers = api.stock.screener.get_gainers(top=10)