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# Alpaca Trade API
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A comprehensive Python client library for Alpaca's commission-free trading API with support for both REST and streaming data interfaces. The library enables rapid development of trading algorithms, portfolio management systems, and market analysis tools with access to real-time and historical market data, account management, and order execution capabilities.
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## Package Information
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- **Package Name**: alpaca-trade-api
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- **Language**: Python
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- **Installation**: `pip install alpaca-trade-api`
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## Core Imports
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```python
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from alpaca_trade_api import REST, Stream, TimeFrame, TimeFrameUnit, AsyncRest
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from alpaca_trade_api.rest import APIError, Sort
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```
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For async operations:
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```python
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from alpaca_trade_api import AsyncRest
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```
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## Basic Usage
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```python
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import alpaca_trade_api as tradeapi
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# Initialize REST client
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api = tradeapi.REST('your-key-id', 'your-secret-key')
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# Get account information
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account = api.get_account()
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print(f"Account equity: ${account.equity}")
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# Submit a market order
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order = api.submit_order(
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    symbol='AAPL',
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    qty=10,
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    side='buy',
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    type='market',
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    time_in_force='day'
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)
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print(f"Order ID: {order.id}")
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# Get historical bars
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bars = api.get_bars('AAPL', tradeapi.TimeFrame.Day, '2023-01-01', '2023-01-31')
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for bar in bars:
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    print(f"{bar.timestamp}: Open=${bar.open}, Close=${bar.close}")
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```
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## Architecture
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The library follows a modular architecture:
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- **REST Client**: Synchronous HTTP client for account management, trading, and market data
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- **AsyncRest Client**: Asynchronous client optimized for market data operations
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- **Stream Client**: WebSocket client for real-time data feeds and trading updates
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- **Entity System**: Object representations of all API responses with pandas integration
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- **Configuration Layer**: Environment-based configuration for flexible deployment
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This design provides comprehensive access to Alpaca's trading platform while maintaining clean separation between synchronous trading operations, asynchronous data operations, and real-time streaming functionality.
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## Capabilities
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### Trading Operations
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Core trading functionality including account management, order execution, position management, and portfolio analytics. These operations form the foundation of algorithmic trading strategies and portfolio management systems.
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```python { .api }
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def get_account() -> Account: ...
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def submit_order(symbol: str, qty: float = None, side: str = "buy", type: str = "market", time_in_force: str = "day", **kwargs) -> Order: ...
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def list_orders(status: str = None, limit: int = None, symbols: List[str] = None, **kwargs) -> List[Order]: ...
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def replace_order(order_id: str, qty: str = None, limit_price: str = None, **kwargs) -> Order: ...
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def get_position(symbol: str) -> Position: ...
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def list_positions() -> List[Position]: ...
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def close_position(symbol: str, qty: float = None) -> Position: ...
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def close_all_positions() -> List[Position]: ...
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```
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[Trading Operations](./trading-operations.md)
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### Market Data Access
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Historical and real-time market data for stocks and cryptocurrencies including bars, trades, quotes, snapshots, and news. Supports multiple data feeds and provides pandas DataFrame integration for analysis workflows.
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```python { .api }
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def get_bars(symbol: Union[str, List[str]], timeframe: TimeFrame, start: str, end: str, **kwargs) -> BarsV2: ...
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def get_bars_iter(symbol: Union[str, List[str]], timeframe: TimeFrame, start: str, end: str, **kwargs) -> Iterator[BarV2]: ...
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def get_trades(symbol: Union[str, List[str]], start: str, end: str, **kwargs) -> TradesV2: ...
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def get_trades_iter(symbol: Union[str, List[str]], start: str, end: str, **kwargs) -> Iterator[TradeV2]: ...
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def get_quotes(symbol: Union[str, List[str]], start: str, end: str, **kwargs) -> QuotesV2: ...
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def get_quotes_iter(symbol: Union[str, List[str]], start: str, end: str, **kwargs) -> Iterator[QuoteV2]: ...
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def get_latest_bar(symbol: str, feed: str = None) -> BarV2: ...
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def get_snapshot(symbol: str, feed: str = None) -> SnapshotV2: ...
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def get_news(symbol: Union[str, List[str]] = None, start: str = None, end: str = None, **kwargs) -> NewsListV2: ...
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def get_news_iter(symbol: Union[str, List[str]] = None, start: str = None, end: str = None, **kwargs) -> Iterator[NewsV2]: ...
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```
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[Market Data](./market-data.md)
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### Real-time Streaming
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WebSocket streaming for real-time market data feeds and trading account updates. Supports subscription-based data streams with handler functions and decorator patterns for event processing.
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```python { .api }
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def subscribe_trades(handler: Callable, *symbols: str) -> None: ...
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def subscribe_quotes(handler: Callable, *symbols: str) -> None: ...
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def subscribe_bars(handler: Callable, *symbols: str) -> None: ...
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def subscribe_trade_updates(handler: Callable) -> None: ...
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def run() -> None: ...
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def stop() -> None: ...
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```
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[Streaming](./streaming.md)
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### Cryptocurrency Data
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Specialized market data operations for cryptocurrency trading pairs including trades, quotes, bars, and orderbook data. Supports multiple crypto exchanges with location-based data access.
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```python { .api }
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def get_crypto_bars(symbol: Union[str, List[str]], timeframe: TimeFrame, start: str, end: str, **kwargs) -> BarsV2: ...
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def get_crypto_bars_iter(symbol: Union[str, List[str]], timeframe: TimeFrame, start: str, end: str, **kwargs) -> Iterator[BarV2]: ...
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def get_crypto_trades(symbol: Union[str, List[str]], start: str, end: str, **kwargs) -> TradesV2: ...
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def get_crypto_trades_iter(symbol: Union[str, List[str]], start: str, end: str, **kwargs) -> Iterator[TradeV2]: ...
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def get_latest_crypto_orderbook(symbol: str, loc: str = None) -> OrderbookV2: ...
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def subscribe_crypto_trades(handler: Callable, *symbols: str) -> None: ...
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```
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[Cryptocurrency](./cryptocurrency.md)
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### Async Market Data
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Asynchronous market data operations optimized for high-performance data retrieval with pandas DataFrame outputs. Designed for concurrent data fetching and analysis workflows.
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```python { .api }
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async def get_bars_async(symbol: str, start: str, end: str, timeframe: TimeFrame, **kwargs) -> Tuple[str, pd.DataFrame]: ...
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async def get_trades_async(symbol: str, start: str, end: str, **kwargs) -> Tuple[str, pd.DataFrame]: ...
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async def get_quotes_async(symbol: str, start: str, end: str, **kwargs) -> Tuple[str, pd.DataFrame]: ...
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async def get_latest_trade_async(symbol: str) -> Tuple[str, TradeV2]: ...
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async def get_latest_quote_async(symbol: str) -> Tuple[str, QuoteV2]: ...
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```
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[Async Operations](./async-operations.md)
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## Types
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```python { .api }
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class TimeFrame:
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    def __init__(self, amount: int, unit: TimeFrameUnit): ...
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    @property
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    def amount(self) -> int: ...
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    @property  
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    def unit(self) -> TimeFrameUnit: ...
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class TimeFrameUnit(Enum):
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    Minute = "Min"
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    Hour = "Hour"
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    Day = "Day"
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    Week = "Week"
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    Month = "Month"
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class Sort(Enum):
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    Asc = "asc"
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    Desc = "desc"
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class APIError(Exception):
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    @property
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    def code(self) -> str: ...
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    @property
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    def status_code(self) -> int: ...
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    @property
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    def request(self): ...
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    @property
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    def response(self): ...
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```